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Prometheus plugin support is emphasized in README.rst. Also formating of
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Table of Contents generated with DocToc

Standard Plugins
- Dot File Configuration
- Plugin Configuration
Detection Plugins
Agent Plugin Detail
License

Standard Plugins

Plugins are the way to extend the Monasca Agent. Plugins add additional functionality that allow the agent to perform checks on other applications, servers or services. Some plugins may have corresponding Detection Plugins to automatically detect, configure, and activate certain Agent plugins. This section describes the standard plugins that are delivered by default.

** Standard location for plugin YAML config files **

/etc/monasca/agent/conf.d/

The following plugins are delivered via setup as part of the standard plugin checks. See Customizations.md for how to write new plugins.

Setup Plugin Name	Dot File	Detail
a10
apache	/root/.apache.cnf	Apache web server
cacti
cAdvisor_host
cert_check
check_mk_local
couch
couchbase
cpu
crash
directory
disk
docker
elastic
file_size
gunicorn
haproxy
hdfs
host_alive
http_check
http_metrics
iis		Microsoft Internet Information Services
jenkins
json_plugin
kafka_consumer
kibana	kibana_install_dir/kibana.yml	Integration to Kibana
kubernetes
kubernetes_api
kyototycoon
libvirt
lighttpd
load
mcache
memory
mk_livestatus
mongo
mysql	/root/.my.cnf
nagios_wrapper
network
nginx		Tracks basic nginx metrics via the status module
ntp		Uses ntplib to grab a metric for the ntp offset
postfix		Provides metrics on the number of messages in a given postfix queue
postgres
process
prometheus
rabbitmq	/root/.rabbitmq.cnf
redisdb
riak
solidfire		Track cluster health and use stats
sqlserver
supervisord
swift_diags
tcp_check
varnish
vcenter
vcenter_slim		Tracks vm status only
vertica	/root/.vertica.cnf
wmi_check
zk		Apache Zookeeper

Dot File Configuration

Dot files, as referenced above, provide an added level of configuration to some component plugins. Here are a few examples:

apache

Example for apache process and server-status metrics (secure)
[client]
user=root
password=pass
url=https://localhost/server-status?auto
or
Example for apache process and server-status metrics (non-secure)
[client]
url=http://localhost/server-status?auto
or
Example for apache process metrics only
[client]
use_server_status_metrics=false

mysql

[client]
user=root
password=pass
host=server
socket=/var/run/mysqld/mysqld.sock
ssl_ca=/etc/ssl/certs/ca-certificates.crt

rabbitmq

[client]
user=guest
password=pass
nodes=rabbit@devstack
queues=conductor
exchanges=nova,cinder,ceilometer,glance,keystone,neutron,heat,ironic,openstack

Plugin Configuration

Each plugin has a corresponding YAML configuration file with the same stem name as the plugin script file.

The configuration file has the following structure:

init_config:
    key1: value1
    key2: value2

instances:
    - username: john_smith
      password: 123456
      dimensions:
          node_type: test
    - username: jane_smith
      password: 789012
      dimensions:
          node_type: production

init_config

In the init_config section you can specify an arbitrary number of global name:value pairs that will be available on every run of the check in self.init_config. Here you can specify a collection frequency specific to the plugin by setting collect_period. The global frequency at which all plugins are run is specified by the variable check_frequency defined in https://github.com/openstack/monasca-agent/blob/master/docs/Agent.md. Under normal and default conditions when a plugin runs all the metrics are collected and sent. For example, if check_frequency=30, by default the plugin will be run every 30 seconds and the metrics will be sent. The variable collect_period allows each plugins collect period to be further adjusted to a value greater than the frequency at which the plugin is run specified by check_frequency, such that when the collection run starts, the plugin might not be called. For example, if check_frequency=30 and collect_period=600, the plugin will be called and metrics sent every 600 seconds. This allows fewer metrics to be sent. The collect_period should be evenly divisible by the check_frequency. For example, if you want the plugin to collect and send metrics every 600 seconds (10 minutes), and the global check_frequency=30, then the collect_period should be set to 600. If the collect_period is not evenly divisible by the check_frequency then the collect_period will get rounded up to the nearest multiple of the check_frequency. For example, if the collect_period=45 and the global check_frequency=30, then the collect_period will get rounded up to 60 and the plugin will get called and send metrics every 60 seconds.

instances

The instances section is a list of instances that this check will be run against. Your actual check() method is run once per instance. The name:value pairs for each instance specify details about the instance that are necessary for the check.

dimensions

The instances section can also contain optional dimensions. These dimensions will be added to any metrics generated by the check for that instance.

Plugin Documentation

Your plugin should include an example YAML configuration file to be placed in /etc/monasca/agent/conf.d/ which has the name of the plugin YAML file plus the extension '.example', so the example configuration file for the process plugin would be at /usr/local/share/monasca/agent/conf.d/process.yaml.example. This file should include a set of example init_config and instances clauses that demonstrate how the plugin can be configured.

Detection Plugins

The monasca_setup library contains a number of detection plugins, which are located within the library at

monasca_setup/detection/plugins/

Some detection plugins activate a specific Agent plugin of the same name, and some leverage other general-purpose Agent plugins to monitor a particular service. There are three classes in total:

Plugin

The base class of detection plugins requires a separate Agent plugin of the same name.

ArgsPlugin

Any plugins which are configured by passing arguments, rather than relying on detection, may use the ArgsPlugin class.

ServicePlugin

This class covers Process, HTTP endpoints, Directory, and File monitoring. It is primarily used for monitoring OpenStack components. Note: There are existing default detection plugins for http_check.py, directory.py, and file_size.py that only require configuration.

A process can be monitored by process_names or by process_username. Pass in the process_names list argument when watching process by name. Pass in the process_username argument and component_name arguments when watching process by username. Watching by username is useful for groups of processes that are owned by a specific user. For process monitoring by process_username the component_name is required since it is used to initialize the instance name in process.yaml. component_name is optional for monitoring by process_name and all other checks.

An http endpoint connection can be checked by passing in the service_api_url and optional search_pattern parameters. The http check can be skipped by specifying the argument 'disable_http_check'

Directory size can be checked by passing in a directory_names list.

File size can be checked by passing in a file_dirs_names list where each directory name item includes a list of files. example: 'file_dirs_names': [('/var/log/monasca/api', ['monasca-api'])]

Note: service_name and component_name are optional (except component_name is required with process_username) arguments used for metric dimensions by all checks.

List of Detection Plugins

These are the detection plugins included with the Monasca Agent. See Customizations.md for how to write new detection plugins.

Detection Plugin Name	Type
a10	Plugin
apache	Plugin
barbican	ServicePlugin
bind	Plugin
cassandra	ServicePlugin
ceilometer	ServicePlugin
ceph	Plugin
cert_check	ArgsPlugin
check_mk_local	Plugin
cinder	ServicePlugin
cloudkitty	ServicePlugin
crash	Plugin
cue	ServicePlugin
designate	ServicePlugin
directory	ServicePlugin
file_size	ServicePlugin
freezer	Plugin (multiple)
glance	ServicePlugin
haproxy	Plugin
heat	ServicePlugin
host_alive	ArgsPlugin
http_check	ArgsPlugin
ironic	ServicePlugin
kafka_consumer	Plugin
keystone	ServicePlugin
libvirt	Plugin
magnum	ServicePlugin
mk_livestatus	Plugin
mon	Plugin (multiple)
mysql	Plugin
neutron	ServicePlugin
nova	ServicePlugin
ntp	Plugin
octavia	ServicePlugin
ovsvapp	ServicePlugin
postfix	Plugin
powerdns	Plugin
process	Plugin
rabbitmq	Plugin
supervisord	Plugin
swift	ServicePlugin
system	Plugin
trove	ServicePlugin
vcenter	Plugin
vertica	Plugin
zookeeper	Plugin
kibana	Plugin

Agent Plugin Detail

This section documents all the checks that are supplied by the Agent.

System Metrics

This section documents the system metrics that are sent by the Agent.

Docker environment:

For Docker environment you can enable the system plugins by adding cpu, disk, memory and load yaml files to the monasca-agent-collector container (mount plugin files to /plugins.d/cpu|disk|memory|load.yaml). Additionally you have to specify the path of the host process filesystem. In this case mount host root directory / to /rootfs in the container. Docker compose example:

volumes:
  - "/:/rootfs:ro"

Sample configurations:

cpu.yaml

init_config:
  process_fs_path: /rootfs/proc
instances:
- name: cpu_stats

disk.yaml

init_config:
  process_fs_path: /rootfs/proc
instances:
- name: disk_stats
  ignore_filesystem_types: iso9660,tmpfs,nsfs

memory.yaml

init_config:
  process_fs_path: /rootfs/proc
instances:
- name: memory_stats

load.yaml

init_config:
  process_fs_path: /rootfs/proc
instances:
- name: load_stats

CPU

Metric Name	Dimensions	Semantics
cpu.idle_perc		Percentage of time the CPU is idle when no I/O requests are in progress
cpu.wait_perc		Percentage of time the CPU is idle AND there is at least one I/O request in progress
cpu.stolen_perc		Percentage of stolen CPU time, i.e. the time spent in other OS contexts when running in a virtualized environment
cpu.system_perc		Percentage of time the CPU is used at the system level
cpu.user_perc		Percentage of time the CPU is used at the user level
cpu.total_logical_cores		Total number of logical cores available for an entire node (Includes hyper threading). NOTE: This is an optional metric that is only sent when send_rollup_stats is set to true.
cpu.percent		Percentage of time the CPU is used in total
cpu.idle_time		Time the CPU is idle when no I/O requests are in progress
cpu.wait_time		Time the CPU is idle AND there is at least one I/O request in progress
cpu.user_time		Time the CPU is used at the user level
cpu.system_time		Time the CPU is used at the system level
cpu.frequency_mhz		Maximum MHz value for the cpu frequency. NOTE: This value is dynamic, and driven by CPU governor depending on current resource need .

Load

Metric Name	Dimensions	Semantics
load.avg_1_min		The normalized (by number of logical cores) average system load over a 1 minute period
load.avg_5_min		The normalized (by number of logical cores) average system load over a 5 minute period
load.avg_15_min		The normalized (by number of logical cores) average system load over a 15 minute period

Memory

Metric Name	Dimensions	Semantics
mem.free_mb		Mbytes of free memory
mem.swap_free_perc		Percentage of free swap memory that is free
mem.swap_free_mb		Mbytes of free swap memory that is free
mem.swap_total_mb		Mbytes of total physical swap memory
mem.swap_used_mb		Mbytes of total swap memory used
mem.total_mb		Total Mbytes of memory
mem.usable_mb		Total Mbytes of usable memory
mem.usable_perc		Percentage of total memory that is usable
mem.used_buffers		Number of buffers in Mbytes being used by the kernel for block io
mem.used_cached		Mbytes of memory used for the page cache
mem.used_shared		Mbytes of memory shared between separate processes and typically used for inter-process communication
mem.used_real_mb		Mbytes of memory currently in use less mem.used_buffers and mem.used_cached

Disk

Metric Name	Dimensions	Semantics
disk.inode_used_perc	device, mount_point	The percentage of inodes that are used on a device
disk.space_used_perc	device, mount_point	The percentage of disk space that is being used on a device
disk.total_space_mb		The total amount of disk space in Mbytes aggregated across all the disks on a particular node. NOTE: This is an optional metric that is only sent when send_rollup_stats is set to true.
disk.total_used_space_mb		The total amount of used disk space in Mbytes aggregated across all the disks on a particular node. NOTE: This is an optional metric that is only sent when send_rollup_stats is set to true.
io.read_kbytes_sec	device	Kbytes/sec read by an io device
io.read_req_sec	device	Number of read requests/sec to an io device
io.read_time_sec	device	Amount of read time in seconds to an io device
io.write_kbytes_sec	device	Kbytes/sec written by an io device
io.write_req_sec	device	Number of write requests/sec to an io device
io.write_time_sec	device	Amount of write time in seconds to an io device

Network

The network check can be configured to submit its metrics in either bytes/sec or bits/sec. The default behavior is to submit bytes. To submit net.in_bits_sec and net.out_bits_sec rather than net.in_bytes_sec and net.out_bytes_sec, set the config option use_bits to true for the instance you want to configure.

Example configuration:

init_config: null
instances:
- built_by: System
  excluded_interface_re: lo.*|vnet.*|tun.*|ovs.*|br.*|tap.*|qbr.*|qvb.*|qvo.*
  name: network_stats
  send_rollup_stats: true
  use_bits: false

Metric Name	Dimensions	Semantics
net.in_bytes_sec	device	Number of network bytes received per second
net.out_bytes_sec	device	Number of network bytes sent per second
net.in_packets_sec	device	Number of network packets received per second
net.out_packets_sec	device	Number of network packets sent per second
net.in_errors_sec	device	Number of network errors on incoming network traffic per second
net.out_errors_sec	device	Number of network errors on outgoing network traffic per second
net.in_packets_dropped_sec	device	Number of inbound network packets dropped per second
net.out_packets_dropped_sec	device	Number of outbound network packets dropped per second
net.int_status	device	Network interface status

Monasca Agent

The Monasca Agent itself generates a small number of metrics.

Metric Name	Dimensions	Semantics
monasca.thread_count	service=monitoring component=monasca-agent	Number of threads that the collector is consuming for this collection run
monasca.emit_time_sec	service=monitoring component=monasca-agent	Amount of time that the forwarder took to send metrics to the Monasca API.
monasca.collection_time_sec	service=monitoring component=monasca-agent	Amount of time that the collector took for this collection run

Limiting System Metrics

It is possible to reduce the number of system metrics with certain configuration parameters.

Config Option	Values	Description
net_bytes_only	true/false	Sends bytes/sec metrics only, disabling packets/sec, packets_dropped/sec, and errors/sec.
cpu_idle_only	true/false	Sends idle_perc only, disabling wait/stolen/system/user metrics
send_io_stats	true/false	If true, sends I/O metrics for each disk device. If false, sends only disk space metrics.

These parameters may added to instances in the plugin .yaml configuration file, or added via monasca-setup like this:

$ monasca-setup -d system -a 'cpu_idle_only=true net_bytes_only=true send_io_stats=false' --overwrite

By default, all metrics are enabled.

A10

This section describes the A10 System Check.

init_config:

instances:
    - name: a10_system_check
        a10_device: a10_device_ip
        a10_username: admin
        a10_password: password

Metric Name	Dimensions	Semantics
a10.memory_total_mb	a10_device, service=networking	Total memory presented in MB
a10.memory_used_mb	a10_device, service=networking	Memory used presented in MB
a10.memory_free_mb	a10_device, service=networking	Free memory presented in MB
a10.memory_used	a10_device, service=networking	Realtime Memory Usage

Apache

This section describes the Apache Web Server check that can be performed by the Agent. The Apache check gathers metrics on the Apache Web Server. The Apache check requires a configuration file called apache.yaml to be available in the agent conf.d configuration directory. The config file must contain the server url, username and password (If you are using authentication) that you are interested in monitoring.

Sample config:

init_config:

instances:
  - apache_status_url: http://localhost/server-status?auto
    apache_user: root
    apache_password: password

If you want the monasca-setup program to detect and auto-configure the plugin for you, you must create the file /root/.apache.cnf with the information needed in the configuration yaml file before running the setup program. It should look something like this:

[client]
url=http://localhost/server-status?auto
user=root
password=password

The Apache checks return the following metrics:

Metric Name	Dimensions	Semantics
apache.performance.idle_worker_count	hostname, service=apache component=apache	The number of idle workers
apache.performance.busy_worker_count	hostname, service=apache component=apache	The number of workers serving requests
apache.performance.cpu_load_perc	hostname, service=apache component=apache	The current percentage of CPU used by each worker and in total by all workers combined
apache.net.total_kbytes	hostname, service=apache component=apache	Total Kbytes
apache.net.hits	hostname, service=apache component=apache	Total accesses
apache.net.kbytes_sec	hostname, service=apache component=apache	Total Kbytes per second
apache.net.requests_sec	hostname, service=apache component=apache	Total accesses per second

Cacti

See the example configuration for how to configure the Cacti plugin.

cAdvisor_host

This plugin collects metrics about a host from a given cAdvisor instance. This is useful in a container environment where the agent is running in a container but still wants to monitor the underlying hosts.

It connects to the cAdvisor instance and queries the stats API about the host.

There are two ways to configure the plugin.

Set cAdvisor url
Set kubernetes detect url to True. If true, the assumption is that the Agent is running in a Kubernetes container. The agent will obtain the cAdvisor url by first querying the Kubernetes API to ask which node it is running on and then from there hit the local cAdvisor on that node that is included in the kubelet.

As a result the plugin only supports getting data from one cAdvisor endpoint. So the config yaml file must only have one instance defined under instances. (Example shown below)

Sample config (passing in cAdvisor url):

init_config:
    # Timeout on GET requests to the cAdvisor endpoints
    connection_timeout: 3
instances:
    # Set to the url of the cAdvisor instance you want to connect to
    - cadvisor_url: "127.0.0.1:4194"

Sample config (setting Kubernetes detect cAdvisor url):

init_config:
    # Timeout on GET requests to the cAdvisor endpoints
    connection_timeout: 3
instances:
    # Set to the url of the cAdvisor instance you want to connect to
    - kubernetes_detect_cadvisor: True

Note if both a url and detect cAdvisor are both set it will by default use the url

The cAdvisor host check returns the following metrics:

Metric Name	Dimensions	Semantics
cpu.num_cores	hostname, unit	Number of cores of host
cpu.system_time	hostname, unit	Cumulative system CPU time consumed in core seconds
cpu.system_time_sec	hostname, unit	Rate of system CPU time consumed in core seconds per second
cpu.total_time	hostname, unit	Cumulative CPU time consumed in core seconds
cpu.total_time_sec	hostname, unit	Rate of CPU time consumed in core seconds per second
cpu.user_time	hostname, unit	Cumulative user cpu time consumed in core seconds
cpu.user_time_sec	hostname, unit	Rate of user CPU time consumed in core seconds per second
fs.total_bytes	hostname, device, unit	Number of bytes available
fs.usage_bytes	hostname, device, unit	Number of bytes consumed
fs.usage_perc	hostname, device, unit	Usage of fs as percentage
io.read_bytes	hostname, unit	Total number of bytes read by all devices
io.read_bytes_sec	hostname, unit	Total number of bytes read by all devices per second
io.write_bytes	hostname, unit	Total number of bytes written by all devices
io.write_bytes_sec	hostname, unit	Total number of bytes written by all devices per second
mem.cache_bytes	hostname, unit	Number of bytes of page cache memory
mem.swap_bytes	hostname, unit	Swap usage in memory in bytes
mem.used_bytes	hostname, unit	Current memory in use in bytes
mem.used_perc	hostname, unit	Current memory usage as percentage
mem.working_set_bytes	hostname, unit	Current working set of memory in bytes (total minus cache)
net.in_bytes	hostname, interface, unit	Total network bytes received by all interfaces
net.in_bytes_sec	hostname, interface, unit	Total number of network bytes received by all interfaces per second
net.in_dropped_packets	hostname, interface, unit	Total inbound network packets dropped by all interfaces
net.in_dropped_packets_sec	hostname, interface, unit	Total number of inbound network packets dropped by all interfaces per second
net.in_errors	hostname, interface, unit	Total network errors on incoming network traffic by all interfaces
net.in_errors_sec	hostname, interface, unit	Total number of network errors on incoming network traffic by all interfaces per second
net.in_packets	hostname, interface, unit	Total network packets received by all interfaces
net.in_packets_sec	hostname, interface, unit	Total number of network packets received by all interfaces per second
net.out_bytes	hostname, interface, unit	Total network bytes sent by all interfaces
net.out_bytes_sec	hostname, interface, unit	Total number of network bytes sent by all interfaces per second
net.out_dropped_packets	hostname, interface, unit	Total outbound network packets dropped by all interfaces
net.out_dropped_packets_sec	hostname, interface, unit	Total number of outbound network packets dropped by all interfaces per second
net.out_errors	hostname, interface, unit	Total network errors on outgoing network traffic by all interfaces
net.out_errors_sec	hostname, interface, unit	Total number of network errors on outgoing network traffic by all interfaces per second
net.out_packets	hostname, interface, unit	Total network packets sent by all interfaces
net.out_packets_sec	hostname, interface, unit	Total number of network packets sent by all interfaces per second

Cassandra Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the Cassandra service. Please note that no directories are monitored per default. directory_names argument can be passed to monasca-setup to change this behaviour.

The following Cassandra processes are monitored, if they exist when the monasca-setup script is run:

Cassandra Processes Monitored

cassandra

Example Cassandra Metrics

Component	Metric Name	Metric Type	Check Type	Dimensions	Plugin	Description
cassandra	process_pid_count	Gauge	Passive	service=cassandra, component=cassandra, process_user=cassandra	process	cassandra process pid count
cassandra	directory.files_count	Gauge	Active	service=cassandra, component=cassandra, path=/var/cassandra/data	cassandra data directory file count
cassandra	directory.size_bytes	Gauge	Active	service=cassandra, component=cassandra, path=/var/cassandra/data	cassandra data directory size
cassandra	directory.files_count	Gauge	Active	service=cassandra, component=cassandra, path=/var/cassandra/commitlog	cassandra commit log directory file count
cassandra	directory.size_bytes	Gauge	Active	service=cassandra, component=cassandra, path=/var/cassandra/commitlog	cassandra commit log directory size

Check_MK_Local

The Check_MK Agent can be extended through a series of local checks. This plugin parses the <<<local>>> output of check_mk_agent and converts them into Monasca metrics. It is installed by monasca-setup automatically when the check_mk_agent script is found to be installed on the system.

The default configuration is to submit metrics from all local checks returned by check_mk_agent. One metric will be submitted for the status code, and one additional metric for each performance measurement included in the result. The basic format of check_mk_agent local check output is:

<status> <item name> <performance data> <check output>

So if the output line is:

0 glance_registry response_time=0.004 glance_registry: status UP http://0.0.0.0:9191

the check_mk_local plugin for the Monasca Agent will return these metrics:

 Timestamp:  1430848955
 Name:       check_mk.glance_registry.status
 Value:      0
 Dimensions: hostname=devstack
             service=monitoring
 Value Meta: detail=glance_registry: status UP http://0.0.0.0:9191

and

 Timestamp:  1430852467
 Name:       check_mk.glance_registry.response_time
 Value:      0.006
 Dimensions: hostname=devstack
             service=monitoring
 Value Meta: None

The name of the metric starts with check_mk., includes the check_mk item name, and is followed by either status for the Nagios status code (0, 1, 2, or 3), or the name of the performance metric. The free-form output from the check is included in the meta field of the check status.

You may override these defaults in the configuration, which by default is /etc/monasca/agent/conf.d/check_mk_local.yaml.

init_config:
    mk_agent_path: /usr/bin/check_mk_agent

    custom:
      - mk_item: sirius-api
        discard: false
        dimensions: {'component': 'sirius'}
        metric_name_base: check_mk.sirius_api
      - mk_item: eon-api
        discard: true

instances:
    - {}

The custom section of init_config is optional and may be blank or removed entirely. In this section, you may add custom rules to Monasca metrics based on the check_mk item name.

mk_item - This is the name (2nd field) returned by check_mk_agent
discard - Exclude the metric from Monasca, True or False (if discard is not specified, the default is False)
dimensions - Extra dimensions to include, in {'name': 'value'} format.
metric_name_base - This represents the leftmost part of the metric name to use. Status and any performance metrics are appended following a dot, so ".status" and ".response_time" would be examples.

Because check_mk_agent can only return all local metrics at once, the check_mk_local plugin requires no instances to be defined in the configuration. It runs check_mk_agent once and processes all the results. This way, new check_mk local scripts can be added without having to modify the plugin configuration.

Ceph

This section describes the Ceph check that can be performed by the Agent. The Ceph check gathers metrics from multiple ceph clusters. The Ceph check requires a configuration file called ceph.yaml to be available in the agent conf.d configuration directory. The config file must contain the cluster name that you are interested in monitoring (defaults to ceph). Also, it is possible to configure the agent to collect only specific metrics about the cluster (usage, stats, monitors, osds or pools).

Requirements:

ceph-common
The user running monasca-agent must be able to execute ceph commands. This can be done by adding the monasca-agent user to the ceph group, and giving group read permission on the ceph.client.admin.keyring file.

  usermod -a -G ceph monasca-agent
  chmod 0640 /etc/ceph/ceph.client.admin.keyring

Alternatively, you can configure monasca-agent to use sudo using the use_sudo option. The example configuration below assumes you added the monasca-agent user to the ceph group which does not require using sudo.

Sample config:

init_config:

instances:
  - cluster_name: ceph
    use_sudo: False
    collect_usage_metrics: True
    collect_stats_metrics: True
    collect_mon_metrics: True
    collect_osd_metrics: True
    collect_pool_metrics: True

The Ceph checks return the following metrics:

Metric Name	Dimensions	Semantics
ceph.cluster.total_bytes	hostname, ceph_cluster, service=ceph	Total capacity of the cluster in bytes
ceph.cluster.total_used_bytes	hostname, ceph_cluster, service=ceph	Capacity of the cluster currently in use in bytes
ceph.cluster.total_avail_bytes	hostname, ceph_cluster, service=ceph	Available space within the cluster in bytes
ceph.cluster.objects.total_count	hostname, ceph_cluster, service=ceph	No. of rados objects within the cluster
ceph.cluster.utilization_perc	hostname, ceph_cluster, service=ceph	Percentage of available storage on the cluster
ceph.cluster.health_status	hostname, ceph_cluster, service=ceph	Health status of cluster, can vary between 3 states (err:2, warn:1, ok:0)
ceph.cluster.osds.down_count	hostname, ceph_cluster, service=ceph	Number of OSDs that are in DOWN state
ceph.cluster.osds.out_count	hostname, ceph_cluster, service=ceph	Number of OSDs that are in OUT state
ceph.cluster.osds.up_count	hostname, ceph_cluster, service=ceph	Number of OSDs that are in UP state
ceph.cluster.osds.in_count	hostname, ceph_cluster, service=ceph	Number of OSDs that are in IN state
ceph.cluster.osds.total_count	hostname, ceph_cluster, service=ceph	Total number of OSDs in the cluster
ceph.cluster.objects.degraded_count	hostname, ceph_cluster, service=ceph	Number of degraded objects across all PGs, includes replicas
ceph.cluster.objects.misplaced_count	hostname, ceph_cluster, service=ceph	Number of misplaced objects across all PGs, includes replicas
ceph.cluster.pgs.avg_per_osd	hostname, ceph_cluster, service=ceph	Average number of PGs per OSD in the cluster
ceph.cluster.pgs.total_count	hostname, ceph_cluster, service=ceph	Total no. of PGs in the cluster
ceph.cluster.pgs.scrubbing_count	hostname, ceph_cluster, service=ceph	Number of scrubbing PGs in the cluster
ceph.cluster.pgs.deep_scrubbing_count	hostname, ceph_cluster, service=ceph	Number of deep scrubbing PGs in the cluster
ceph.cluster.pgs.degraded_count	hostname, ceph_cluster, service=ceph	Number of PGs in a degraded state
ceph.cluster.pgs.stuck_degraded_count	hostname, ceph_cluster, service=ceph	No. of PGs stuck in a degraded state
ceph.cluster.pgs.unclean_count	hostname, ceph_cluster, service=ceph	Number of PGs in an unclean state
ceph.cluster.pgs.stuck_unclean_count	hostname, ceph_cluster, service=ceph	Number of PGs stuck in an unclean state
ceph.cluster.pgs.undersized_count	hostname, ceph_cluster, service=ceph	Number of undersized PGs in the cluster
ceph.cluster.pgs.stuck_undersized_count	hostname, ceph_cluster, service=ceph	Number of stuck undersized PGs in the cluster
ceph.cluster.pgs.stale_count	hostname, ceph_cluster, service=ceph	Number of stale PGs in the cluster
ceph.cluster.pgs.stuck_stale_count	hostname, ceph_cluster, service=ceph	Number of stuck stale PGs in the cluster
ceph.cluster.pgs.remapped_count	hostname, ceph_cluster, service=ceph	Number of PGs that are remapped and incurring cluster-wide movement
ceph.cluster.recovery.bytes_per_sec	hostname, ceph_cluster, service=ceph	Rate of bytes being recovered in cluster per second
ceph.cluster.recovery.keys_per_sec	hostname, ceph_cluster, service=ceph	Rate of keys being recovered in cluster per second
ceph.cluster.recovery.objects_per_sec	hostname, ceph_cluster, service=ceph	Rate of objects being recovered in cluster per second
ceph.cluster.client.read_bytes_per_sec	hostname, ceph_cluster, service=ceph	Rate of bytes being read by all clients per second
ceph.cluster.client.write_bytes_per_sec	hostname, ceph_cluster, service=ceph	Rate of bytes being written by all clients per second
ceph.cluster.client.read_ops	hostname, ceph_cluster, service=ceph	Total client read I/O ops on the cluster measured per second
ceph.cluster.client.write_ops	hostname, ceph_cluster, service=ceph	Total client write I/O ops on the cluster measured per second
ceph.cluster.cache.flush_bytes_per_sec	hostname, ceph_cluster, service=ceph	Rate of bytes being flushed from the cache pool per second
ceph.cluster.cache.evict_bytes_per_sec	hostname, ceph_cluster, service=ceph	Rate of bytes being evicted from the cache pool per second
ceph.cluster.cache.promote_ops	hostname, ceph_cluster, service=ceph	Total cache promote operations measured per second
ceph.cluster.slow_requests_count	hostname, ceph_cluster, service=ceph	Number of slow requests
ceph.cluster.quorum_size	hostname, ceph_cluster, service=ceph	Number of monitors in quorum
ceph.monitor.total_bytes	hostname, ceph_cluster, monitor, service=ceph	Total storage capacity of the monitor node
ceph.monitor.used_bytes	hostname, ceph_cluster, monitor, service=ceph	Storage of the monitor node that is currently allocated for use
ceph.monitor.avail_bytes	hostname, ceph_cluster, monitor, service=ceph	Total unused storage capacity that the monitor node has left
ceph.monitor.avail_perc	hostname, ceph_cluster, monitor, service=ceph	Percentage of total unused storage capacity that the monitor node has left
ceph.monitor.store.total_bytes	hostname, ceph_cluster, monitor, service=ceph	Total capacity of the FileStore backing the monitor daemon
ceph.monitor.store.sst_bytes	hostname, ceph_cluster, monitor, service=ceph	Capacity of the FileStore used only for raw SSTs
ceph.monitor.store.log_bytes	hostname, ceph_cluster, monitor, service=ceph	Capacity of the FileStore used only for logging
ceph.monitor.store.misc_bytes	hostname, ceph_cluster, monitor, service=ceph	Capacity of the FileStore used only for storing miscellaneous information
ceph.monitor.skew	hostname, ceph_cluster, monitor, service=ceph	Monitor clock skew
ceph.monitor.latency	hostname, ceph_cluster, monitor, service=ceph	Monitor's latency
ceph.osd.crush_weight	hostname, ceph_cluster, osd, service=ceph	OSD crush weight
ceph.osd.depth	hostname, ceph_cluster, osd, service=ceph	OSD depth
ceph.osd.reweight	hostname, ceph_cluster, osd, service=ceph	OSD reweight
ceph.osd.total_bytes	hostname, ceph_cluster, osd, service=ceph	OSD total bytes
ceph.osd.used_bytes	hostname, ceph_cluster, osd, service=ceph	OSD used storage in bytes
ceph.osd.avail_bytes	hostname, ceph_cluster, osd, service=ceph	OSD available storage in bytes
ceph.osd.utilization_perc	hostname, ceph_cluster, osd, service=ceph	OSD utilization
ceph.osd.variance	hostname, ceph_cluster, osd, service=ceph	OSD variance
ceph.osd.pgs_count	hostname, ceph_cluster, osd, service=ceph	OSD placement group count
ceph.osd.perf.commit_latency_seconds	hostname, ceph_cluster, osd, service=ceph	OSD commit latency in seconds
ceph.osd.perf.apply_latency_seconds	hostname, ceph_cluster, osd, service=ceph	OSD apply latency in seconds
ceph.osd.up	hostname, ceph_cluster, osd, service=ceph	OSD up status (up: 1, down: 0)
ceph.osd.in	hostname, ceph_cluster, osd, service=ceph	OSD in status (in: 1, out: 0)
ceph.osds.total_bytes	hostname, ceph_cluster, service=ceph	OSDs total storage in bytes
ceph.osds.total_used_bytes	hostname, ceph_cluster, service=ceph	OSDs total used storage in bytes
ceph.osds.total_avail_bytes	hostname, ceph_cluster, service=ceph	OSDs total available storage in bytes
ceph.osds.avg_utilization_perc	hostname, ceph_cluster, osd, service=ceph	OSDs average utilization in percent
ceph.pool.used_bytes	hostname, ceph_cluster, pool, service=ceph	Capacity of the pool that is currently under use
ceph.pool.used_raw_bytes	hostname, ceph_cluster, pool, service=ceph	Raw capacity of the pool that is currently under use, this factors in the size
ceph.pool.max_avail_bytes	hostname, ceph_cluster, pool, service=ceph	Free space for this ceph pool
ceph.pool.objects_count	hostname, ceph_cluster, pool, service=ceph	Total no. of objects allocated within the pool
ceph.pool.dirty_objects_count	hostname, ceph_cluster, pool, service=ceph	Total no. of dirty objects in a cache-tier pool
ceph.pool.read_io	hostname, ceph_cluster, pool, service=ceph	Total read i/o calls for the pool
ceph.pool.read_bytes	hostname, ceph_cluster, pool, service=ceph	Total read throughput for the pool
ceph.pool.write_io	hostname, ceph_cluster, pool, service=ceph	Total write i/o calls for the pool
ceph.pool.write	hostname, ceph_cluster, pool, service=ceph	Total write throughput for the pool
ceph.pool.quota_max_bytes	hostname, ceph_cluster, pool, service=ceph	Quota maximum bytes for the pool
ceph.pool.quota_max_objects	hostname, ceph_cluster, pool, service=ceph	Quota maximum objects for the pool
ceph.pool.total_bytes	hostname, ceph_cluster, pool, service=ceph	Total capacity of the pool in bytes
ceph.pool.utilization_perc	hostname, ceph_cluster, pool, service=ceph	Percentage of used storage for the pool
ceph.pool.client.read_bytes_sec	hostname, ceph_cluster, pool, service=ceph	Read bytes per second on the pool
ceph.pool.client.write_bytes_sec	hostname, ceph_cluster, pool, service=ceph	Write bytes per second on the pool
ceph.pool.client.read_ops	hostname, ceph_cluster, pool, service=ceph	Read operations per second on the pool
ceph.pool.client.write_ops	hostname, ceph_cluster, pool, service=ceph	Write operations per second on the pool
ceph.pool.recovery.objects_per_sec	hostname, ceph_cluster, pool, service=ceph	Objects recovered per second on the pool
ceph.pool.recovery.bytes_per_sec	hostname, ceph_cluster, pool, service=ceph	Bytes recovered per second on the pool
ceph.pool.recovery.keys_per_sec	hostname, ceph_cluster, pool, service=ceph	Keys recovered per second on the pool
ceph.pool.recovery.objects	hostname, ceph_cluster, pool, service=ceph	Objects recovered on the pool
ceph.pool.recovery.bytes	hostname, ceph_cluster, pool, service=ceph	Bytes recovered on the pool
ceph.pool.recovery.keys	hostname, ceph_cluster, pool, service=ceph	Keys recovered on the pool
ceph.pools.count	hostname, ceph_cluster, service=ceph	Number of pools on the cluster

Certificate Expiration (HTTPS)

An extension to the Agent provides the ability to determine the expiration date of the certificate for the URL. The metric is days until the certificate expires

default dimensions:

    url: url

A YAML file (cert_check.yaml) contains the list of urls to check. It also contains

The configuration of the certificate expiration check is done in YAML, and consists of two keys:

init_config
instances

The init_config section lists the global configuration settings, such as the Certificate Authority Certificate file, the ciphers to use, the period at which to output the metric and the url connection timeout (in seconds, floating-point number)

$ ls -l `which ping` -rwsr-xr-x 1 root root 35712 Nov 8 2011 /bin/ping

init_config:
  ca_certs: /etc/ssl/certs/ca-certificates.crt
  ciphers: HIGH:-aNULL:-eNULL:-PSK:RC4-SHA:RC4-MD5
  collect_period: 3600
  timeout: 1.0

The instances section contains the urls to check.

instances:
- built_by: CertificateCheck
  url: https://somehost.somedomain.net:8333
- built_by: CertificateCheck
  url: https://somehost.somedomain.net:9696

The certicate expiration checks return the following metrics

Metric Name	Dimensions	Semantics
https.cert_expire_days	url=supplied url being checked	The number of days until the certificate expires

There is a detection plugin that should be used to configure this extension. It is invoked as:

$ monasca-setup -d CertificateCheck -a urls=https://somehost.somedomain.net:8333,https://somehost.somedomain.net:9696

The urls option is a comma separated list of urls to check.

These options can be set if desired:

ca_certs: file containing the certificates for Certificate Authorities. The default is /etc/ssl/certs/ca-certificates.crt
ciphers: list of ciphers to use. default is HIGH:-aNULL:-eNULL:-PSK:RC4-SHA:RC4-MD5
collect_period: Integer time in seconds between outputting the metric. Since the metric is in days, it makes sense to output it at a slower rate. The default is 3600, once per hour
timeout: Float time in seconds before timing out the connect to the url. Increase if needed for very slow servers, but making this too long will increase the time this plugin takes to run if the server for the url is down. The default is 1.0 seconds

Congestion

This section describes the congestion check performed by monasca-agent. Congestion check collects metrics from special iptable chain created by the agent called congestion. Metric names that are cross-posted to the infrastructure project will have the ecn. prefix.

Configuration

The congestion check requires a configuration file called congestion.yaml to be available in the agent conf.d configuration directory. An example of the configuration is given below.

auth_url is the keystone endpoint for authentication.

cache_dir will be used to cache ecn metrics in a file called congestion_status.json.

enable_ecn optional method that activates ecn marking in each machine. When the transmission equipment in the network encounters a congestion in its queues, it will not mark packets until the ecn is enabled by the sender. enable_ecn method ensures that ecn marking is enabled for both the sender and the receiver. This method is optional because the end user could enable ecn by changing the value of tcp_ecn from 0 to 2 or running 'echo 2 > /proc/sys/net/ipv4/tcp_ecn' in each machine.

enable_vm optional method that gathers ecn metrics ecn.packets, ecn.bytes, and ecn.cong.rate of each VM hosted in a remote compute. By default the agent collects ecn metrics of computes, activating this method add fine-grained control of the congestion.

s_factor Smoothing factor used to compute ecn congestion rate.

collect_period Period of time in sec to collect metrics and used also in ecn congestion rate calculation.

password is the password for the nova user.

project_name is the project/tenant to POST ecn metrics.

region_name is used to add the region dimension to metrics.

username is the username capable of making administrative nova calls.

instances are not used and should be empty in congestion.yaml because the plugin runs against all computes.

Sample config (congestion.yaml):

init_config:
  auth_url: http://10.10.10.10/identity_admin
  cache_dir: /dev/shm
  enable_ecn: true
  enable_vm: true
  password: admin
  project_name: service
  region_name: RegionOne
  username: nova
  collect_period: 30
  s_factor = 0.1

instances:
 - {}

The congestion checks return the following metrics:

Metric Name	Dimensions	Semantics
ecn.packets	hostname, device, component=neutron, service=networking	Number of packets marked as Congestion Experienced
ecn.bytes	hostname, device, component=neutron, service=networking	Number of bytes marked as Congestion Experienced
ecn.cong.rate	hostname, device, component=neutron, service=networking	Congestion rate in kbps calculated using ecn.bytes value

There is a detection plugin that should be used to configure this plugin. It is invoked as:

$ monasca-setup -d congestion

You can check the current congestion status of the network by simply running:

$ sudo monasca-collector -v check congestion

Couch

See the example configuration for how to configure the Couch plugin.

Couchbase

See the example configuration for how to configure the Couchbase plugin.

Crash

Overview

The crash plugin provides metrics for crash dumps present on the system. Currently, it only returns the number of crash dumps found plus the date-/timestamp of the most recent crash in a value_meta dictionary.

Metrics

Only one metric is provided at the moment with a hostname dimension.

Name	Description	value_meta
crash.dump_count	Number of crash dumps found	{'latest': u'<date-/timestamp>'}

Configuration

The monasca-setup program will configure the Crash plugin if a crash kernel is loaded. The default directory where the plugin will look for crash dumps is /var/crash.

Sample config:

init_config:
  crash_dir: /var/crash

instances:
  - name: crash_stats

Directory Checks

This section describes the directory check that can be performed by the Agent. Directory checks are used for gathering the total size of all the files under a specific directory. A YAML file (directory.yaml) contains the list of directory names to check. A Python script (directory.py) runs checks each host in turn to gather stats. Note: for sparse file, directory check is using its resident size instead of the actual size.

Similar to other checks, the configuration is done in YAML, and consists of two keys: init_config and instances. The former is not used by directory check, while the later contains one or more sets of directory names to check on. Directory check will sum the size of all the files under the given directory recursively.

Sample config:

init_config: null
instances:
- built_by: Directory
  directory: /var/log/monasca/agent
- built_by: Directory
  directory: /etc/monasca/agent

The directory checks return the following metrics:

Metric Name	Dimensions
directory.size_bytes	path, hostname, service
directory.files_count	path, hostname, service

Docker

This plugin gathers metrics on docker containers.

A YAML file (docker.yaml) contains the url of the docker api to connect to and the root of docker that is used for looking for docker proc metrics.

For this check the user that is running the monasca agent (usually the mon-agent user) must be a part of the docker group

Also if you want to want to attach kubernetes dimensions to each metric you can set add_kubernetes_dimensions to true in the yaml file. This will set the pod_name and namespace.

Sample config:

Without kubernetes dimensions

init_config:
  docker_root: /
  socket_timeout: 5
instances:
  - url: "unix://var/run/docker.sock"

With kubernetes dimensions

init_config:
  docker_root: /
  socket_timeout: 5
instances:
  - url: "unix://var/run/docker.sock"
    add_kubernetes_dimensions: True

Note this plugin only supports one instance in the config file.

The docker check return the following metrics:

Metric Name	Metric Type	Dimensions	Optional_dimensions (set if add_kubernetes_dimensions is true and container is running under kubernetes)	Semantics
container.containers.running_count	Gauge	hostname		Number of containers running on the host
container.cpu.system_time	Gauge	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The total time the CPU has executed system calls on behalf of the processes in the container
container.cpu.system_time_sec	Rate	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The rate the CPU is executing system calls on behalf of the processes in the container
container.cpu.user_time	Gauge	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The total time the CPU is under direct control of the processes in this container
container.cpu.user_time_sec	Rate	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The rate the CPU is under direct control of the processes in this container
container.cpu.utilization_perc	Gauge	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The percentage of CPU used by the container
container.io.read_bytes	Gauge	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The total amount bytes read from the processes in the container
container.io.read_bytes_sec	Rate	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The rate of bytes read from the processes in the container
container.io.write_bytes	Gauge	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The total amount bytes written from the processes in the container
container.io.write_bytes_sec	Rate	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The rate of bytes written from the processes in the container
container.mem.cache	Gauge	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The amount of cached memory that belongs to the container's processes
container.mem.rss	Gauge	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The amount of non-cached memory used by the container's processes
container.mem.swap	Gauge	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The amount of swap memory used by the processes in the container
container.mem.used_perc	Gauge	hostname, name, image	kubernetes_pod_name, kubernetes_namespace	The percentage of memory used out of the given limit of the container
container.net.in_bytes	Gauge	hostname, name, image, interface	kubernetes_pod_name, kubernetes_namespace	The total amount of bytes received by the container per interface
container.net.in_bytes_sec	Rate	hostname, name, image, interface	kubernetes_pod_name, kubernetes_namespace	The rate of bytes received by the container per interface
container.net.out_bytes	Gauge	hostname, name, image, interface	kubernetes_pod_name, kubernetes_namespace	The total amount of bytes sent by the container per interface
container.net.out_bytes_sec	Rate	hostname, name, image, interface	kubernetes_pod_name, kubernetes_namespace	The rate of bytes sent by the container per interface

Elasticsearch Checks

This section describes the Elasticsearch check that can be performed by the Agent. The Elasticsearch check requires a configuration file called elastic.yaml to be available in the agent conf.d configuration directory.

Sample config:

init_config:
instances:
-   url: http://127.0.0.1:9200

The Elasticsearch checks return the following metrics:

Metric Name	Dimensions	Semantics
elasticsearch.docs.count	url, hostname, service=monitoring	The total number of docs including nested documents.
elasticsearch.docs.deleted	url, hostname, service=monitoring	The number of deleted docs.
elasticsearch.store.size	url, hostname, service=monitoring	The filesystem storage size.
elasticsearch.indexing.index.total	url, hostname, service=monitoring
elasticsearch.indexing.index.time	url, hostname, service=monitoring
elasticsearch.indexing.index.current	url, hostname, service=monitoring
elasticsearch.indexing.delete.total	url, hostname, service=monitoring
elasticsearch.indexing.delete.time	url, hostname, service=monitoring
elasticsearch.indexing.delete.current	url, hostname, service=monitoring
elasticsearch.get.total	url, hostname, service=monitoring
elasticsearch.get.time	url, hostname, service=monitoring
elasticsearch.get.current	url, hostname, service=monitoring
elasticsearch.get.exists.total	url, hostname, service=monitoring
elasticsearch.get.exists.time	url, hostname, service=monitoring
elasticsearch.get.missing.total	url, hostname, service=monitoring
elasticsearch.get.missing.time	url, hostname, service=monitoring
elasticsearch.search.query.total	url, hostname, service=monitoring
elasticsearch.search.query.time	url, hostname, service=monitoring
elasticsearch.search.query.current	url, hostname, service=monitoring
elasticsearch.search.fetch.total	url, hostname, service=monitoring
elasticsearch.search.fetch.time	url, hostname, service=monitoring
elasticsearch.search.fetch.current	url, hostname, service=monitoring
elasticsearch.merges.current	url, hostname, service=monitoring
elasticsearch.merges.current.docs	url, hostname, service=monitoring
elasticsearch.merges.current.size	url, hostname, service=monitoring
elasticsearch.merges.total	url, hostname, service=monitoring
elasticsearch.merges.total.time	url, hostname, service=monitoring
elasticsearch.merges.total.docs	url, hostname, service=monitoring
elasticsearch.merges.total.size	url, hostname, service=monitoring
elasticsearch.refresh.total	url, hostname, service=monitoring
elasticsearch.refresh.total.time	url, hostname, service=monitoring
elasticsearch.flush.total	url, hostname, service=monitoring
elasticsearch.flush.total.time	url, hostname, service=monitoring	The elasticsearch flush time.
elasticsearch.process.open_fd	url, hostname, service=monitoring	The number of open files descriptors on the machine.
elasticsearch.transport.rx_count	url, hostname, service=monitoring
elasticsearch.transport.tx_count	url, hostname, service=monitoring
elasticsearch.transport.rx_size	url, hostname, service=monitoring
elasticsearch.transport.tx_size	url, hostname, service=monitoring
elasticsearch.transport.server_open	url, hostname, service=monitoring
elasticsearch.thread_pool.bulk.active	url, hostname, service=monitoring	The number of active threads for bulk operations.
elasticsearch.thread_pool.bulk.threads	url, hostname, service=monitoring	The total number of threads for bulk operations.
elasticsearch.thread_pool.bulk.queue	url, hostname, service=monitoring	The number of tasks in queue of thread pool used for bulk operations.
elasticsearch.thread_pool.bulk.rejected	url, hostname, service=monitoring	The number of rejected tasks of thread pool used for bulk operations.
elasticsearch.thread_pool.flush.active	url, hostname, service=monitoring	The number of active threads for flush operations.
elasticsearch.thread_pool.flush.threads	url, hostname, service=monitoring	The total number of threads for flush operations.
elasticsearch.thread_pool.flush.queue	url, hostname, service=monitoring	The number of tasks in queue of thread pool used for flush operations.
elasticsearch.thread_pool.flush.rejected	url, hostname, service=monitoring	The number of rejected tasks of thread pool used for flush operations.
elasticsearch.thread_pool.generic.active	url, hostname, service=monitoring	The number of active threads for generic operations (i.e. node discovery).
elasticsearch.thread_pool.generic.threads	url, hostname, service=monitoring	The total number of threads for generic operations (i.e. node discovery).
elasticsearch.thread_pool.generic.queue	url, hostname, service=monitoring	The number of tasks in queue of thread pool used for generic operations.
elasticsearch.thread_pool.generic.rejected	url, hostname, service=monitoring	The number of rejected tasks of thread pool used for generic operations.
elasticsearch.thread_pool.get.active	url, hostname, service=monitoring	The number of active threads for get operations.
elasticsearch.thread_pool.get.threads	url, hostname, service=monitoring	The total number of threads for get operations.
elasticsearch.thread_pool.get.queue	url, hostname, service=monitoring	The number of tasks in queue of thread pool used for get operations.
elasticsearch.thread_pool.get.rejected	url, hostname, service=monitoring	The number of rejected tasks of thread pool used for get operations.
elasticsearch.thread_pool.index.active	url, hostname, service=monitoring	The number of active threads for indexing operations.
elasticsearch.thread_pool.index.threads	url, hostname, service=monitoring	The total number of threads for indexing operations.
elasticsearch.thread_pool.index.queue	url, hostname, service=monitoring	The number of tasks in queue of thread pool used for indexing operations.
elasticsearch.thread_pool.index.rejected	url, hostname, service=monitoring	The number of rejected tasks of thread pool used for indexing operations.
elasticsearch.thread_pool.management.active	url, hostname, service=monitoring	The number of active threads for management operations.
elasticsearch.thread_pool.management.threads	url, hostname, service=monitoring	The total number of threads for management operations.
elasticsearch.thread_pool.management.queue	url, hostname, service=monitoring	The number of tasks in queue of thread pool used for management operations.
elasticsearch.thread_pool.management.rejected	url, hostname, service=monitoring	The number of rejected tasks of thread pool used for management operations.
elasticsearch.thread_pool.merge.active	url, hostname, service=monitoring	The number of active threads for merging operation.
elasticsearch.thread_pool.merge.threads	url, hostname, service=monitoring	The total number of threads for merging operation.
elasticsearch.thread_pool.merge.queue	url, hostname, service=monitoring	The number of tasks in queue of thread pool used for merge operations.
elasticsearch.thread_pool.merge.rejected	url, hostname, service=monitoring	The number of rejected tasks of thread pool used for merge operations.
elasticsearch.thread_pool.percolate.active	url, hostname, service=monitoring	The number of active threads for percolate operations.
elasticsearch.thread_pool.percolate.threads	url, hostname, service=monitoring	The total number of threads for percolate operations.
elasticsearch.thread_pool.percolate.queue	url, hostname, service=monitoring	The number of tasks in queue of thread pool used for percolate operations.
elasticsearch.thread_pool.percolate.rejected	url, hostname, service=monitoring	The number of rejected tasks of thread pool used for percolate operations.
elasticsearch.thread_pool.refresh.active	url, hostname, service=monitoring	The number of active threads for refresh operations.
elasticsearch.thread_pool.refresh.threads	url, hostname, service=monitoring	The total number of threads for refresh operations.
elasticsearch.thread_pool.refresh.queue	url, hostname, service=monitoring	The number of tasks in queue of thread pool used for refresh operations.
elasticsearch.thread_pool.refresh.rejected	url, hostname, service=monitoring	The number of rejected tasks of thread pool used for refresh operations.
elasticsearch.thread_pool.search.active	url, hostname, service=monitoring	The number of active threads for search operations.
elasticsearch.thread_pool.search.threads	url, hostname, service=monitoring	The total number of threads for search operations.
elasticsearch.thread_pool.search.queue	url, hostname, service=monitoring	The number of tasks in queue of thread pool used for search operations.
elasticsearch.thread_pool.search.rejected	url, hostname, service=monitoring	The number of rejected tasks of thread pool used for search operations.
elasticsearch.thread_pool.snapshot.active	url, hostname, service=monitoring	The number of active threads for snapshot operations.
elasticsearch.thread_pool.snapshot.threads	url, hostname, service=monitoring	The total number of threads for snapshot operations.
elasticsearch.thread_pool.snapshot.queue	url, hostname, service=monitoring	The number of tasks in queue of thread pool used for snapshot operations.
elasticsearch.thread_pool.snapshot.rejected	url, hostname, service=monitoring	The number of rejected tasks of thread pool used for snapshot operations.
elasticsearch.http.current_open	url, hostname, service=monitoring	Current number of opened HTTP connections.
elasticsearch.http.total_opened	url, hostname, service=monitoring	Max number of HTTP connections.
jvm.gc.concurrent_mark_sweep.count	url, hostname, service=monitoring
jvm.gc.concurrent_mark_sweep.collection_time	url, hostname, service=monitoring
jvm.gc.par_new.count	url, hostname, service=monitoring	ParNew count.
jvm.gc.par_new.collection_time	url, hostname, service=monitoring	ParNew pauses time.
jvm.mem.heap_committed	url, hostname, service=monitoring	The allocated amount of heap memory.
jvm.mem.heap_used	url, hostname, service=monitoring	The amount of heap memory which is actually in use.
jvm.mem.non_heap_committed	url, hostname, service=monitoring	The allocated amount of non-heap memory.
jvm.mem.non_heap_used	url, hostname, service=monitoring	The amount of non-heap memory which is actually in use.
jvm.threads.count	url, hostname, service=monitoring	Current number of live daemon and non-daemon threads.
jvm.threads.peak_count	url, hostname, service=monitoring	Peak live thread count since the JVM started or the peak was reset.
elasticsearch.number_of_nodes	url, hostname, service=monitoring	Number of nodes.
elasticsearch.number_of_data_nodes	url, hostname, service=monitoring	Number of data nodes.
elasticsearch.active_primary_shards	url, hostname, service=monitoring	Indicates the number of primary shards in your cluster. This is an aggregate total across all indices.
elasticsearch.active_shards	url, hostname, service=monitoring	Aggregate total of all shards across all indices, which includes replica shards.
elasticsearch.relocating_shards	url, hostname, service=monitoring	Shows the number of shards that are currently moving from one node to another node.
elasticsearch.initializing_shards	url, hostname, service=monitoring	The count of shards that are being freshly created.
elasticsearch.unassigned_shards	url, hostname, service=monitoring	The number of unassigned shards from the master node.
elasticsearch.cluster_status	url, hostname, service=monitoring	Cluster health status.

Additional links

List of available thread pools

File Size

This section describes the file size check that can be performed by the Agent. File size checks are used for gathering the size of individual files or the size of each file under a specific directory. The agent supports additional functionality through the use of Python scripts. A YAML file (file_size.yaml) contains the list of file directory names and file names to check. A Python script (file_size.py) runs checks each host in turn to gather stats.

Similar to other checks, the configuration is done in YAML, and consists of two keys: init_config and instances. The former is not used by file_size, while the later contains one or more sets of file directory name and file names to check, plus optional parameter recursive. When recursive is true and file_name is set to '*', file_size check will take all the files under the given directory recursively.

Sample config:

init_config: null
instances:
- built_by: FileSize
  directory_name: /var/log/monasca/agent/
  file_names:
  - '*'
  recursive: false
- built_by: FileSize
  directory_name: /var/log/monasca/api
  file_names:
  - monasca-api.log
  - request.log
  recursive: false
- built_by: FileSize
  directory_name: /var/log/monasca/notification
  file_names:
  - notification.log
  recursive: false

The file_size checks return the following metrics:

Metric Name	Dimensions
file.size_bytes	file_name, directory_name, hostname, service

GearmanD

See the example configuration for how to configure the GearmandD plugin.

Gunicorn

See the example configuration for how to configure the Gunicorn plugin.

HAProxy

See the example configuration for how to configure the HAProxy plugin.

HDFS

See the example configuration for how to configure the HDFS plugin.

Host Alive

An extension to the Agent can provide basic "aliveness" checks of other systems, verifying that the remote host (or device) is online. This check currently provides two methods of determining connectivity:

ping (ICMP)
SSH (banner test, port 22 by default)

Of the two, the SSH check provides a more comprehensive test of a remote system's availability, since it checks the banner returned by the remote host. A server in the throes of a kernel panic may still respond to ping requests, but would not return an SSH banner. It is suggested, therefore, that the SSH check be used instead of the ping check when possible.

A YAML file (host_alive.yaml) contains the list of remote hosts to check, including the host name and testing method (either 'ping' or 'ssh'). A Python script (host_alive.py) runs checks against each host in turn, returning a 0 on success and a 1 on failure in the result sent through the Forwarder and on the Monitoring API.

Because the Agent itself does not run as root, it relies on the system ping command being suid root in order to function.

The configuration of the host alive check is done in YAML, and consists of two keys:

init_config
instances

The init_config section lists the global configuration settings, such as SSH port, SSH connection timeout (in seconds, floating-point number), and ping timeout (in seconds, integer).

$ ls -l `which ping` -rwsr-xr-x 1 root root 35712 Nov 8 2011 /bin/ping

init_config:
    ssh_port: 22

    # ssh_timeout is a floating-point number of seconds
    ssh_timeout: 0.5

    # ping_timeout is an integer number of seconds
    ping_timeout: 1

The instances section contains the hostname/IP to check, and the type of check to perform, which is either ssh or ping.

    # alive_test can be either "ssh" for an SSH banner test (port 22)
    # or "ping" for an ICMP ping test instances:
  - name: ssh to somehost
    host_name: somehost.somedomain.net
    alive_test: ssh

  - name: ping gateway
    host_name: gateway.somedomain.net
    alive_test: ping

  - name: ssh to 192.168.0.221
    host_name: 192.168.0.221
    alive_test: ssh

To handle the case where the target system has multiple IP Addresses and the network name to be used for liveness checking is not the same as the usual name used to identify the server in Monasca, an additional target_hostname parameter can be configured. It is the network hostname or IP Address to check instead of host_name. The hostname dimension will always be set to the value of host_name even if target_hostname is specified. A dimension target_hostname will be added with the value of target_hostname if it is different from host_name.

To simplify configuring multiple checks, when the host_alive detection plugin is configured, hostname can be a comma separated list. Instances will be created for each value. target_hostname can also be a comma separated list, however, empty values for an individual entry can be given if there is no target_hostname for a given hostname entry.

Here is an example of configuring target_hostname :

  - name: ping somenode
    host_name: somenode
    target_hostname: somenode.mgmt.net
    alive_test: ssh

The host alive checks return the following metrics

Metric Name	Dimensions	Semantics
host_alive_status	observer_host=fqdn of checking host, hostname=supplied hostname being checked, target_hostname=the network hostname or IP Address to check instead of host_name; only added if different than hostname, test_type=ping or ssh	Status of remote host(device) is online or not. (0=online, 1=offline)

Also in the case of an error the value_meta contains an error message.

The default dimensions are:

   observer_host: fqdn
   hostname: fqdn | supplied
   target_hostname: Set to target_hostname only if that is different than host_name
   test_type: ping | ssh | Unrecognized alive_test

default value_meta

   error: error_message

HTTP (endpoint status)

This section describes the http endpoint check that can be performed by the Agent. Http endpoint checks are checks that perform simple up/down checks on services, such as HTTP/REST APIs. An agent, given a list of URLs, can dispatch an http request and report to the API success/failure as a metric.

default dimensions:

    url: endpoint

default value_meta

    error: error_message

The Agent supports additional functionality through the use of Python scripts. A YAML file (http_check.yaml) contains the list of URLs to check (among other optional parameters). A Python script (http_check.py) runs checks each host in turn, returning a 0 on success and a 1 on failure in the result sent through the Forwarder and on the Monitoring API.

Similar to other checks, the configuration is done in YAML, and consists of two keys: init_config and instances. In the former, you can provide Keystone configuration for checks to retrieve token for authentication that will be used for all checks. While the later contains one or more URLs to check, plus optional parameters like a timeout, username/password, pattern to match against the HTTP response body, whether or not to include the HTTP response in the metric (as a 'detail' dimension), whether or not to also record the response time, and more. If the endpoint being checked requires authentication, there are two options. First, a username and password supplied in the instance options will be used by the check for authentication. Alternately, the check can retrieve a keystone token for authentication. Specific keystone information can be provided for all checks in init_config section, or if it's not provided there, the information from the agent config will be used. DEPRECATED: providing Keystone configuration in each instance.

Sample config:

init_config:
    keystone_config:
        keystone_url: http://endpoint.com/v3/
        project_name: project
        username: user
        password: password

instances:
    url: http://192.168.0.254/healthcheck
    timeout: 1
    include_content: true
    collect_response_time: true
    match_pattern: '.*OK.*OK.*OK.*OK.*OK'

The http_status checks return the following metrics:

Metric Name	Dimensions	Semantics
http_status	url, detail	The status of the http endpoint call (0 = success, 1 = failure)
http_response_time	url	The response time in seconds of the http endpoint call

HTTP Metrics

This section describes the http metrics check that can be performed by the agent. Http metrics checks are checks that retrieve metrics from any url returning a json formatted response. An agent, given a list of URLs, can dispatch an http request and parse the desired metrics from the json response.

default dimensions:

    url: endpoint

default value_meta

    error: error_message

Similar to other checks, the configuration is done in YAML (http_metrics.yaml), and consists of two keys: init_config and instances. The former is not used by http_metrics, while the later contains one or more URLs to check, plus optional parameters like a timeout, username/password, whether or not to also record the response time, and a whitelist of metrics to collect. The whitelist should consist of a name, path, and type for each metric to be collected. The name is what the metric will be called when it is reported. The path is a string of keys separated by '/' where the metric value resides in the json response. The type is how you want the metric to be recorded (gauge, counter, histogram, rate, set). A gauge will store and report the value it find with no modifications. A counter will increment itself by the value it finds. A histogram will store values and return the calculated max, median, average, count, and percentiles. A rate will return the difference between the last two recorded samples divided by the interval between those samples in seconds. A set will record samples and return the number of unique values in the set. If the endpoint being checked requires authentication, there are two options. First, a username and password supplied in the instance options will be used by the check for authentication. Alternately, the check can retrieve a keystone token for authentication. Specific keystone information can be provided for each check, otherwise the information from the agent config will be used.

init_config:

instances:
       url: http://192.168.0.254/metrics
       timeout: 1
       collect_response_time: true
       whitelist:
              name: jvm.memory.total.max,
              path: gauges/jvm.memory.total.max/value
              type: gauge

InfluxDB

Auto-detection for InfluxDB plugin comes with two checks enabled:

process monitoring with following configuration

{
    'detailed': True,
    'search_string': ['influxd'],
    'exact_match': False,
    'name': 'influxd',
    'dimensions': {
        'component': 'influxdb',
        'service': 'influxdb'
    }
}

http_check monitoring

{
    'name': 'influxdb',
    'url': 'http://127.0.0.1:8086/ping'
}

InfluxDB does expose internal metrics on its own, however
they are subject to extend influxdb auto-detection capabilities
in future

InfluxDB-Relay

InfluxDB-Relay does not expose any internal metrics on its own, however auto-detection plugin configures two checks on behalf of it:

process monitoring with following configuration

{
    'detailed': True,
    'search_string': ['influxdb-relay'],
    'exact_match': False,
    'name': 'influxdb-relay',
    'dimensions': {
        'component': 'influxdb-relay',
        'service': 'influxdb'
    }
}

http_check monitoring

{
    'name': 'influxdb-relay',
    'url': 'http://127.0.0.1:9096/ping'
}

IIS

See the example configuration for how to configure the IIS plugin.

Jenkins

See the example configuration for how to configure the Jenkins plugin.

JsonPlugin

This plugin allows you to report metrics by simply writing the metrics to a file. The plugin reads the file and sends the metrics to Monasca.

Simple Reporting

The simplest approach is to create a file in the /var/cache/monasca_json_plugin directory. The file should contain a list of metrics in JSON format as shown in the following example. The file must have a ".json" extension in the name.

Simple Example -- /var/cache/monasca_json_plugin/my-metrics-file.json:

[
   {"name": "metric1", "value": 10.1, "timestamp": 1475596165},
   {"name": "metric2", "value": 12.3, "timestamp": 1475596165}
]

In the above example, the "name", "value" and "timestamp" of each measurement is reported. The following keys are available:

Key	Description
name	Required. The name of the metric. The key "metric" may be used instead of "name".
value	Required. The value of the measurement. This is a floating point number.
timestamp	Optional (if replace_timestamps is true; see below); otherwise required. The time of the measurement. Uses UNIX time epoch value. Note: this is seconds, not mulliseconds, since the epoch.
dimensions	Optional. Dimensions of the metric as a set of key/value pairs.
value_meta	Optional. Value meta of the metric as a set of key/value pairs.

Writing and Locking the Metrics File

You should take an exclusive lock on the file while you write new metrics (this plugin takes a shared lock). You must close or flush the file after writing new data to make sure the data is written to the file.

Example of writing metrics file:

metric_data = [{"name": "metric1", "value": 10.1, "timestamp": time.time()}]
max_retries = 10
delay = 0.02
attempts = 0
with open('/var/cache/monasca_json_plugin/my-metrics-file.json', 'w') as fd:
    while True:
        attempts += 1
        try:
            fcntl.flock(fd, fcntl.LOCK_EX | fcntl.LOCK_NB)
            break
        except IOError as err:
            if (err.errno not in [errno.EWOULDBLOCK, errno.EACCES] or
                    attempts > max_retries):
                raise
        time.sleep(delay * attempts)
    fd.write(json.dumps(metric_data))

Additional Directives

You can add additional directives to the JSON file as shown in the following example:

Additional Directives Example:

{
   "replace_timestamps": false,
   "stale_age": 300,
   "measurements": [
      {"name": "metric1", "value": 10.1, "timestamp": 1475596165, "dimensions": {"path": "/tmp"}},
      {"name": "metric2", "value": 12.3, "timestamp": 1475596165, "value_meta": {"msg": "hello world"}}
   ]
}

The additional directives are described in the following table. The directives are optional.

Directive	Description
replace_timestamps	If true, the timestamps are ignored. Instead, the timestamp of the measurement is set to the current time. Default is false.
stale_age	The number of seconds after which metrics are considered stale. This stops measurements from a file that is not updating from being reported to Monasca. It defaults to 4 minutes.

The main purpose of the stale_age directive is to detect if the JSON file stops updating (e.g., due to a bug or system failure). See the description of the monasca.json_plugin.status metric below.

The main purpose of the replace_timestamps directive is where the mechanism to write the JSON file runs infrequently or erratically. Every time Monasca Agent runs, the metrics are reported with the current time -- whether or not the file is updated. In this mode, you do not need to supply a timestamp (in fact, any timestamp you include is ignored). Also the stale_age directive is also ignored.

Custom JSON file locations

To use the built-in /var/cache/monasca_json_plugin directory, your application must be able to create and write files to that directory. If this is not possible, you can write the JSON file(s) to a different file path. An example of this configuration is in the example configuration.

The Monasca Agent user must be able to read the files.

The monasca.json_plugin.status Metric

The plugin reports a metric called "monasca.json_plugin.status". A single metric is reported by the JSON plugin. If there are problems, you can examine the value_meta. It will contain a list of problem paths/messages. You to create an alarm to trigger if there is a problem processing any JSON file.

The monasca.json_plugin.status metric has the following information:

Field	Description
name	"monasca.json_plugin.status" -- the name of the metric
value	A value of 0.0 is normal -- there are no issues processing all JSON files. A value of 1.0 indicates there is a problem.
value_meta	Value meta is only present when the value is 1.0. The value meta contains a "msg" key indicating the problem.

The value_meta/msg reports problems such as:

Failure to open the JSON file
Invalid JSON syntax
That metrics are older than the stale_age

Kafka Checks

This section describes the Kafka check that can be performed by the Agent. The Kafka check requires a configuration file called kafka_consumer.yaml to be available in the agent conf.d configuration directory.

Sample config:

init_config:

instances:
- built_by: Kafka
  consumer_groups:
    1_metrics:
      metrics: []
    thresh-event:
      events: []
    thresh-metric:
      metrics: []
  kafka_connect_str: 192.168.10.6:9092
  name: 192.168.10.6:9092
  per_partition: false

The Kafka checks return the following metrics:

Metric Name	Dimensions	Semantics
kafka.broker_offset	topic, service, component, partition, hostname	broker offset
kafka.consumer_offset	topic, service, component, partition, consumer_group, hostname	consumer offset
kafka.consumer_lag	topic, service, component, partition, consumer_group, hostname	consumer offset lag from broker offset

Kubernetes

This plugin collects metrics about containers (optionally) and pods on a kubernetes node.

The plugin collects metrics on a kubernetes node by going to the kubelet on the node to get all pod data. Included in that is containers configured under each pod and metadata about each.

It then goes to cAdvisor to get all docker container metrics and metadata associated with it. The plugin then does a comparison of the containers collected from cAdvisor and the containers defined from the kubelet.

If a container is defined to be apart of a pod it will take the metadata from the kubelet as dimensions (so it can get all of the kuberenetes associated tags), if it is not apart of a pod it will set the dimensions from the cAdvisor metadata.

When setting the kubernetes configuration there is a parameter "kubernetes_labels" where it will look for kubernetes tags that are user defined to use as dimensions for pod/container metrics. By default it will look for the label 'app'.

For each pod that we detect we will also aggregate container metrics that belong to that pod to output pod level metrics.

The kubernetes node that the plugin will connect to can be configured in two different ways. The first being setting the host variable in the instance. The other being setting the derive_host to True under the instance. We derive the host by first using the kubernetes environment variables to get the api url (assuming we are running in a kubernetes container). Next we use the container's pod name and namespace (passed in as environment variables to the agents container - see kubernetes example yaml file) with the api url to hit the api to get the pods metadata including the host it is running on. That is the host we use.

If derive_host is set to true the plugin will also hit the API when the owner of a Kubernetes pod is a replicaset (taken from the kubelet) to see if it is under a deployment.

Also by default we will not report the container metrics due to throughput it generates. If you want the container metrics you can set the configuration parameter "report_container_metrics" to True.

Sample configs:

Without custom labels and host being manually set:

init_config:
    # Timeout on GET requests
    connection_timeout: 3
    report_container_metrics: False
instances:
    # Set to the host that the plugin will use when connecting to cAdvisor/kubelet
    - host: "127.0.0.1"
      cadvisor_port: 4194
      kublet_port: 10255

With custom labels and host being manually set:

init_config:
    # Timeout on GET requests
    connection_timeout: 3
    report_container_metrics: False
instances:
    # Set to the host that the plugin will use when connecting to cAdvisor/kubelet
    - host: "127.0.0.1"
      cadvisor_port: 4194
      kublet_port: 10255
      kubernetes_labels: ['k8s-app', 'version']

With custom labels and derive host being set:

instances:
    # Set to the host that the plugin will use when connecting to the Kubernetes API
    - host: "127.0.0.1"
      kubernetes_api_port: 8080
      kubernetes_labels: ['k8s-app', 'version']

With custom labels and derive api url set to True:

init_config:
    # Timeout on GET requests
    connection_timeout: 3
    report_container_metrics: False
instances:
    - derive_host: True
      cadvisor_port: 4194
      kublet_port: 10255
      kubernetes_labels: ['k8s-app', 'version']

Note this plugin only supports one instance in the config file.

The kubernetes check returns the following metrics (note that for containers running under kubernetes and pod metrics can also have dimensions set from the configuration option 'kubernetes_labels' which by default will include 'app')

Note the container metrics will only be reported when the report_container_metrics is True with the exception of container.mem.usage_percent which will be reported based on the flag report_container_mem_percent.

Common Container metrics between containers running underneath kubernetes and standalone:

Metric Name	Dimensions if owned by a kubernetes pod	Dimensions if running standalone from kubernetes	Semantics
container.cpu.system_time	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Cumulative system CPU time consumed in core seconds
container.cpu.system_time_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname	Rate of system CPU time consumed in core seconds
container.cpu.total_time	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Cumulative CPU time consumed in core seconds
container.cpu.total_time_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Rate of CPU time consumed in core seconds
container.cpu.user_time	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Cumulative user cpu time consumed in core seconds
container.cpu.user_time_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Rate of user CPU time consumed in core seconds
container.fs.total_bytes	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of bytes available
container.fs.usage_bytes	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of bytes consumed
container.fs.writes	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Cumulative number of completed writes
container.fs.writes_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of completed writes per a second
container.fs.reads	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Cumulative number of completed reads
container.fs.reads_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of completed reads per a second
container.fs.io_current	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of i/o operations in progress
container.mem.cache_bytes	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of bytes of page cache memory
container.mem.rss_bytes	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Size of rss in bytes
container.mem.swap_bytes	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Swap usage in memory in bytes
container.mem.used_bytes	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Current memory in use in bytes
container.mem.working_set_bytes	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Current working set memory in bytes (total minus cache)
container.mem.fail_count	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of memory usage limit hits
container.net.in_bytes	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Total network bytes received
container.net.in_bytes_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of network bytes received per second
container.net.in_dropped_packets	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Total inbound network packets dropped
container.net.in_dropped_packets_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of inbound network packets dropped per second
container.net.in_errors	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Total network errors on incoming network traffic
container.net.in_errors_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of network errors on incoming network traffic per second
container.net.in_packets	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Total network packets received
container.net.in_packets_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of network packets received per second
container.net.out_bytes	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Total network bytes sent
container.net.out_bytes_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of network bytes sent per second
container.net.out_dropped_packets	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Total outbound network packets dropped
container.net.out_dropped_packets_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of outbound network packets dropped per second
container.net.out_errors	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Total network errors on outgoing network traffic
container.net.out_errors_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of network errors on outgoing network traffic per second
container.net.out_packets	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Total network packets sent
container.net.out_packets_sec	image, container_name, pod_name, namespace, unit	image, container_name, hostname, unit	Number of network packets sent per second

Container metrics specific to containers running under kubernetes:

Metric Name	Dimensions	Semantics
container.ready_status	image, name, pod_name, namespace	Ready status of the container defined by the ready probe
container.restart_count	image, name, pod_name, namespace	Restart count of the container
container.cpu.limit	image, name, pod_name, namespace	Limit in CPU cores for the container
container.memory.limit_bytes	image, name, pod_name, namespace	Limit of memory in bytes for the container
container.request.cpu	image, name, pod_name, namespace	Amount of CPU cores requested by the container
container.request.memory_bytes	image, name, pod_name, namespace	Amount of memory in bytes requested by the container
container.mem.usage_percent	image, name, pod_name, namespace	Percentage of memory used out of defined container limit.

Kubelet Metrics:

Metric Name	Dimensions	Semantics
kubelet.health_status	hostname	Health status of the kubelet api

Pod Metrics:

Metric Name	Dimensions	Semantics
pod.cpu.system_time	pod_name, namespace	Cumulative system CPU time consumed in core seconds
pod.cpu.system_time_sec	pod_name, namespace	Rate of system CPU time consumed in core seconds
pod.cpu.total_time	pod_name, namespace	Cumulative CPU time consumed in core seconds
pod.cpu.total_time_sec	pod_name, namespace	Rate of CPU time consumed in core seconds
pod.cpu.user_time	pod_name, namespace	Cumulative user cpu time consumed in core seconds
pod.cpu.user_time_sec	pod_name, namespace	Rate of user CPU time consumed in core seconds
pod.mem.cache_bytes	pod_name, namespace	Number of bytes of page cache memory
pod.mem.fail_count	pod_name, namespace	Number of memory usage limit hits
pod.mem.rss_bytes	pod_name, namespace	Size of rss in bytes
pod.mem.swap_bytes	pod_name, namespace	Swap usage in memory in bytes
pod.mem.used_bytes	pod_name, namespace	Current memory in use in bytes
pod.mem.working_set_bytes	pod_name, namespace	Current working set memory in bytes (total minus cache)
pod.net.in_bytes	pod_name, namespace	Total network bytes received
pod.net.in_bytes_sec	pod_name, namespace	Number of network bytes received per second
pod.net.in_dropped_packets	pod_name, namespace	Total inbound network packets dropped
pod.net.in_dropped_packets_sec	pod_name, namespace	Number of inbound network packets dropped per second
pod.net.in_errors	pod_name, namespace	Total network errors on incoming network traffic
pod.net.in_errors_sec	pod_name, namespace	Number of network errors on incoming network traffic per second
pod.net.in_packets	pod_name, namespace	Total network packets received
pod.net.in_packets_sec	pod_name, namespace	Number of network packets received per second
pod.net.out_bytes	pod_name, namespace	Total network bytes sent
pod.net.out_bytes_sec	pod_name, namespace	Number of network bytes sent per second
pod.net.out_dropped_packets	pod_name, namespace	Total outbound network packets dropped
pod.net.out_dropped_packets_sec	pod_name, namespace	Number of outbound network packets dropped per second
pod.net.out_errors	pod_name, namespace	Total network errors on outgoing network traffic
pod.net.out_errors_sec	pod_name, namespace	Number of network errors on outgoing network traffic per second
pod.net.out_packets	pod_name, namespace	Total network packets sent
pod.net.out_packets_sec	pod_name, namespace	Number of network packets sent per second
pod.restart_count	pod_name, namespace	Aggregated restart count of the pod's containers
pod.phase	pod_name, namespace	Current phase of the pod. See table below for mapping

There is also additional Kubernetes dimensions for the Container and Pod metrics depending on the owner for the pod:

Owner	Dimension Name	Notes
ReplicationController	replication_controller
ReplicaSet	replica_set
DaemonSet	daemon_set
StatefulSet	stateful_set
Deployment	deployment	Only will be set if derive_host is set to true as it needs to connect to the API to see if the ReplicaSet is under a deployment
Job	job

Pod Phase Mapping:

Metric Value	Phase
0	Succeeded
1	Running
2	Pending
3	Failed
4	Unknown

Kubernetes_API

This plugin collects metrics from the kubernetes api on kubernetes components, nodes, deployments and replication controllers.

When setting the kubernetes configuration there is a parameter "kubernetes_labels" where it will look for kubernetes tags that are user defined to use as dimensions for replication controller and deployment metrics.

There are two ways you can configure the plugin to connect to the kubernetes api. Either by setting the host and port or by setting the derive_api_url to True. If deriving the plugin sets the kubernetes api url by looking at the environment variables. (This should be used if the agent is running in a kubernetes container)

Sample configs:

instances:
    - derive api url: True
      kubernetes_labels: ['k8s-app', 'version']

Note this plugin only supports one instance in the config file.

Metrics (Note for replication controller and deployment metrics they can also have custom dimensions set from the configuration option 'kubernetes_labels')

Metric Name	Dimensions	Semantics
kubernetes.api.health_status		Health status of the api
kubernetes.component_status	component_name	Status of cluster's components
kubernetes.node.out_of_disk	hostname	The node is out of disk
kubernetes.node.memory_pressure	hostname	Available memory on the node has satisfied an eviction threshold
kubernetes.node.disk_pressure	hostname	Available disk space and inodes on either the node’s root filesystem or image filesystem has satisfied an eviction threshold
kubernetes.node.ready_status	hostname	The ready status of the kubernetes node
kubernetes.node.allocatable.memory_bytes	hostname, unit	Total allocatable memory in bytes available for scheduling on the node
kubernetes.node.allocatable.cpu	hostname, unit	Total allocatable cpu cores available for scheduling on the node
kubernetes.node.allocatable.pods	hostname	Total allocatable pods available for scheduling on the node
kubernetes.node.capacity.memory_bytes	hostname, unit	Total memory on the node
kubernetes.node.capacity.cpu	hostname, unit	Total amount of cpu cores on the node
kubernetes.node.capacity.pods	hostname	Total amount of pods that could be run on the node
kubernetes.deployment.available_replicas	deployment, namespace	The number of available replicas for the deployment
kubernetes.deployment.replicas	deployment, namespace	The number of replicas for the deployment
kubernetes.deployment.unavailable_replicas	deployment, namespace	The number of unavailable replicas for the deployment
kubernetes.deployment.updated_replicas	deployment, namespace	The number of updated replicas for the deployment
kubernetes.replication.controller.ready_replicas	replication_controller, namespace	The number of ready replicas for the replication controller
kubernetes.replication.controller.replicas	replication_controller, namespace	The number of replicas for the replication controller

KyotoTycoon

See the example configuration for how to configure the KyotoTycoon plugin.

Libvirt VM Monitoring

Complete documentation of the Libvirt VM monitoring plugin can be found in the Libvirt.md document.

Open vSwitch Neutron Router Monitoring

Complete documentation of the Open vSwitch Neutron Router monitoring plugin can be found in the Ovs.md document.

Lighttpd

See the example configuration for how to configure the Lighttpd plugin.

LXC

An agent that provides LXC cgroup data. This agent does not require sudo.

Requirements:

Sample config:

init_config:

instances:
    - container: all
      cpu: True
      mem: True
      swap: True
      blkio: True
      net: True

The LXC checks return the following metrics:

Metric Name	Dimensions	Semantics
blkio.read	hostname, container_name, service=lxc	number of bytes read from the disk to the cgroup(container)
blkio.write	hostname, container_name, service=lxc	number of bytes written from the cgroup(container) to the disk
blkio.async	hostname, container_name, service=lxc	number of asynchronous bytes
blkio.sync	hostname, container_name, service=lxc	number of synchronous bytes
blkio.total	hostname, container_name, service=lxc	total number of bytes
cpuacct.usage	hostname, container_name, service=lxc	reports the total CPU time (in nanoseconds) consumed
cpuacct.usage_percpu.cpu{X}	hostname, container_name, service=lxc	reports the total CPU time (in nanoseconds) consumed by cpu X
cpuacct.user	hostname, container_name, service=lxc	CPU time consumed by tasks in user mode. Unit defined by the USER_HZ variable
cpuacct.system	hostname, container_name, service=lxc	CPU time consumed by tasks in kernel mode. Unit defined by the USER_HZ variable
memory.cache	hostname, container_name, service=lxc	page cache, including tmpfs (shmem), in bytes
memory.rss	hostname, container_name, service=lxc	anonymous and swap cache, not including tmpfs (shmem), in bytes
memory.mapped_file	hostname, container_name, service=lxc	size of memory-mapped mapped files, including tmpfs (shmem), in bytes
memory.pgpgin	hostname, container_name, service=lxc	number of pages paged into memory
memory.pgpgout	hostname, container_name, service=lxc	number of pages paged out of memory
memory.swap	hostname, container_name, service=lxc	swap usage in bytes
memory.active_anon	hostname, container_name, service=lxc	anonymous and swap cache on LRU list, in bytes
memory.inactive_anon	hostname, container_name, service=lxc	anonymous and swap cache on inactive LRU list, in bytes
memory.active_file	hostname, container_name, service=lxc	file-backed memory on active LRU list, in bytes
memory.inactive_file	hostname, container_name, service=lxc	file-backed memory on inactive LRU list, in bytes
memory.unevictable	hostname, container_name, service=lxc	memory that cannot be reclaimed, in bytes
memory.hierarchical_memory_limit	hostname, container_name, service=lxc	memory limit for the hierarchy that contains the memory cgroup, in bytes
memory.hierarchical_memsw_limit	hostname, container_name, service=lxc	memory plus swap limit for the hierarchy that contains the memory cgroup, in bytes
memory.usage_in_bytes	hostname, container_name, service=lxc	memory usage, in bytes
memory.memsw.usage_in_bytes	hostname, container_name, service=lxc	swap memory usage, in bytes
net.rx.bytes	hostname, container_name, service=lxc, iface	number of received bytes
net.rx.packets	hostname, container_name, service=lxc, iface	number of received packets
net.rx.errs	hostname, container_name, service=lxc, iface	number of received error packets
net.rx.drop	hostname, container_name, service=lxc, iface	number of received dropped packets
net.rx.fifo	hostname, container_name, service=lxc, iface	number of received fifo packets
net.rx.frame	hostname, container_name, service=lxc, iface	number of received frame packets
net.rx.compressed	hostname, container_name, service=lxc, iface	number of received compressed bytes
net.rx.multicast	hostname, container_name, service=lxc, iface	number of received multicast packets
net.tx.bytes	hostname, container_name, service=lxc, iface	number of transferred bytes
net.tx.packets	hostname, container_name, service=lxc, iface	number of transferred packets
net.tx.errs	hostname, container_name, service=lxc, iface	number of transferred error packets
net.tx.drop	hostname, container_name, service=lxc, iface	number of transferred dropped packets
net.tx.fifo	hostname, container_name, service=lxc, iface	number of transferred fifo packets
net.tx.frame	hostname, container_name, service=lxc, iface	number of transferred frame packets
net.tx.compressed	hostname, container_name, service=lxc, iface	number of transferred compressed bytes
net.tx.multicast	hostname, container_name, service=lxc, iface	number of transferred multicast packets
running_containers	hostname, service=lxc	number of running containers

Mcache

See the example configuration for how to configure the Mcache plugin.

MK Livestatus

MK Livestatus is a Nagios Event Broker, allowing access to Nagios host and service data through a socket query. The Monasca Agent mk_livestatus plugin is a way to access Nagios data and commit it to Monasca. Possible use cases of this plugin include:

A way to evaluate Monasca with identical metrics to Nagios, providing an apples-to-apples comparison
A gentle migration from Nagios to Monasca, where both monitoring processes can exist simultaneously during Nagios decommissioning
A turnkey solution for rapidly converting an existing Nagios installation to Monasca, where the Nagios infrastructure can remain indefinitely

The mk_livestatus plugin will be installed during monasca-setup if a Nagios/Icinga configuration is found, the MK Livestatus broker_module is installed, and the livestatus socket can be accessed. The monasca-agent user will need read access to the socket file in order to function, and a message to this effect will be included in monasca-setup output if the socket exists but monasca-agent cannot read it.

The configuration file (/etc/monasca/agent/conf.d/mk_livestatus.yaml by default) allows for a level of customization of both host and service checks.

Service checks
- name - (Required) Monasca metric name to assign
- check_type - (Required) "service" (as opposed to "host" below)
- display_name - (Required) Name of the check as seen in Nagios
- host_name - (Optional) Limit Monasca metrics of this check to the specified host name (as seen in Nagios).
- dimensions - (Optional) Extra Monasca dimensions to include, in {'key': 'value'} format
Host checks
- name - (Required) Monasca metric name to assign
- check_type - (Required) "host" (as opposed to "service" above)
- host_name - (Optional) Limit Monasca metrics of this check to the specified host name (as seen in Nagios).
- dimensions - (Optional) Extra Monasca dimensions to include, in {'key': 'value'} format

If host_name is not specified, metrics for all hosts will be reported.

This configuration example shows several ways to specify instances:

init_config:
    # Specify the path to the mk_livestatus socket
    socket_path: /var/lib/icinga/rw/live

instances:

    # One service on one host
    - name:           nagios.check_http_status
      check_type:     service
      display_name:   HTTP
      host_name:      web01.example.net

    # One service on all hosts
    - name:           nagios.process_count_status
      check_type:     service
      display_name:   Total Processes

    # One service on all hosts with extra dimensions
    - name:           nagios.check_http_status
      check_type:     service
      display_name:   HTTP
      dimensions:     { 'group': 'webservers' }

    # All services on all hosts
    # These will be assigned metric names automatically, based on display_name
    - check_type:     service

    # One host
    - name:           nagios.host_status
      check_type:     host
      host_name:      web01.example.net

    # All hosts
    - name:           nagios.host_status
      check_type:     host

Mongo

See the example configuration for how to configure the Mongo plugin.

MySQL Checks

This section describes the mySQL check that can be performed by the Agent. The mySQL check also supports MariaDB. The mySQL check requires a configuration file called mysql.yaml to be available in the agent conf.d configuration directory.

Sample config: defaults_file: /root/.my.cnf

[client]
host=padawan-ccp-c1-m1-mgmt
user=root
password=pass

Note

Be assured that the password is set properly. As default monasca-agent expects password without quotation marks. Otherwise monasca-setup returns an error about inability to connect to MySQL with given password.

Instance variables can be passed via command line arguments to the monasca-setup -d mysql command. The instance config files are built by the detection plugin.

init_config:
Example clear connect:
instances:
- built_by: MySQL
  name: padawan-ccp-c1-m1-mgmt
  pass: secretpass
  port: 3306
  server: padawan-ccp-c1-m1-mgmt
  user: root

Example ssl connect:
instances:
- built_by: MySQL
  name: padawan-ccp-c1-m1-mgmt
  pass: secretpass
  port: 3306
  server: padawan-ccp-c1-m1-mgmt
  ssl_ca: /etc/ssl/certs/ca-certificates.crt
  user: root

Almost metrics show the server status variables in MySQL or MariaDB. The others are calculated by the server status variables of MySQL or MariaDB. For details of the server status variables, please refer the documents of MySQL or MariaDB. The mySQL checks return the following metrics:

Metric Name	Dimensions	Semantics
mysql.performance.questions	hostname, mode, service=mysql	Corresponding to "Question" of the server status variable.
mysql.performance.qcache_hits	hostname, mode, service=mysql	Corresponding to "Qcache_hits" of the server status variable.
mysql.performance.open_files	hostname, mode, service=mysql	Corresponding to "Open_files" of the server status variable.
mysql.performance.created_tmp_tables	hostname, mode, service=mysql	Corresponding to "Created_tmp_tables" of the server status variable.
mysql.performance.user_time	hostname, mode, service=mysql	The CPU user time for DB's performance, in seconds.
mysql.performance.com_replace_select	hostname, mode, service=mysql	Corresponding to "Com_replace_select" of the server status variable.
mysql.performance.kernel_time	hostname, mode, service=mysql	The kernel time for DB's performance, in seconds.
mysql.performance.com_insert	hostname, mode, service=mysql	Corresponding to "Com_insert" of the server status variable.
mysql.performance.threads_connected	hostname, mode, service=mysql	Corresponding to "Threads_connected" of the server status variable.
mysql.performance.com_update_multi	hostname, mode, service=mysql	Corresponding to "Com_update_multi" of the server status variable.
mysql.performance.table_locks_waited	hostname, mode, service=mysql	Corresponding to "Table_locks_waited" of the server status variable.
mysql.performance.com_insert_select	hostname, mode, service=mysql	Corresponding to "Com_insert_select" of the server status variable.
mysql.performance.slow_queries	hostname, mode, service=mysql	Corresponding to "Slow_queries" of the server status variable.
mysql.performance.com_delete	hostname, mode, service=mysql	Corresponding to "Com_delete" of the server status variable.
mysql.performance.com_select	hostname, mode, service=mysql	Corresponding to "Com_select" of the server status variable.
mysql.performance.queries	hostname, mode, service=mysql	Corresponding to "Queries" of the server status variable.
mysql.performance.created_tmp_files	hostname, mode, service=mysql	Corresponding to "Created_tmp_files" of the server status variable.
mysql.performance.com_update	hostname, mode, service=mysql	Corresponding to "Com_update" of the server status variable.
mysql.performance.com_delete_multi	hostname, mode, service=mysql	Corresponding to "Com_delete_multi" of the server status variable.
mysql.performance.created_tmp_disk_tables	hostname, mode, service=mysql	Corresponding to "Created_tmp_disk_tables" of the server status variable.
mysql.innodb.mutex_spin_rounds	hostname, mode, service=mysql	Corresponding to spinlock rounds of the server status variable.
mysql.innodb.current_row_locks	hostname, mode, service=mysql	Corresponding to current row locks of the server status variable.
mysql.innodb.mutex_os_waits	hostname, mode, service=mysql	Corresponding to the OS waits of the server status variable.
mysql.innodb.buffer_pool_used	hostname, mode, service=mysql	The number of used pages, in bytes. This value is calculated by subtracting "Innodb_buffer_pool_pages_total" away from "Innodb_buffer_pool_pages_free" of the server status variable.
mysql.innodb.data_writes	hostname, mode, service=mysql	Corresponding to "Innodb_data_writes" of the server status variable.
mysql.innodb.data_reads	hostname, mode, service=mysql	Corresponding to "Innodb_data_reads" of the server status variable.
mysql.innodb.row_lock_waits	hostname, mode, service=mysql	Corresponding to "Innodb_row_lock_waits" of the server status variable.
mysql.innodb.os_log_fsyncs	hostname, mode, service=mysql	Corresponding to "Innodb_os_log_fsyncs" of the server status variable.
mysql.innodb.buffer_pool_total	hostname, mode, service=mysql	The total size of buffer pool, in bytes. This value is calculated by multiplying "Innodb_buffer_pool_pages_total" and "Innodb_page_size" of the server status variable.
mysql.innodb.row_lock_time	hostname, mode, service=mysql	Corresponding to "Innodb_row_lock_time" of the server status variable.
mysql.innodb.mutex_spin_waits	hostname, mode, service=mysql	Corresponding to the spin waits of the server status variable.
mysql.innodb.buffer_pool_free	hostname, mode, service=mysql	The number of free pages, in bytes. This value is calculated by multiplying "Innodb_buffer_pool_pages_free" and "Innodb_page_size" of the server status variable.
mysql.net.max_connections	hostname, mode, service=mysql	Corresponding to "Max_used_connections" of the server status variable.
mysql.net.connections	hostname, mode, service=mysql	Corresponding to "Connections" of the server status variable.

Nagios Wrapper

The Agent can run Nagios plugins. A YAML file (nagios_wrapper.yaml) contains the list of Nagios checks to run, including the check name, command name with parameters, and desired interval between iterations. A Python script (nagios_wrapper.py) runs each command in turn, captures the resulting exit code (0 through 3, corresponding to OK, warning, critical and unknown), and sends that information to the Forwarder, which then sends to the Monitoring API. Currently, the Agent can only send the exit code from a Nagios plugin. Any accompanying text is not sent.

default dimensions:

    observer_host: fqdn
    target_host: fqdn | supplied

default value_meta

    0, 1, 2, 3, 4
    OK, Warning, Critical, Unknown
    error: error_message

Similar to all plugins, the configuration is done in YAML, and consists of two keys: init_config and instances.

init_config contains global configuration options:

init_config:
  # Directories where Nagios checks (scripts, programs) may live
  check_path: /usr/lib/nagios/plugins:/usr/local/bin/nagios

  # Where to store last-run timestamps for each check
  temp_file_path: /dev/shm/

instances contains the list of checks to run.

instances:
  - name: load
    check_command: check_load -r -w 2,1.5,1 -c 10,5,4

  - name: disk
    check_command: check_disk -w 15\% -c 5\% -A -i /srv/node
    check_interval: 300

name value is the name of the metric.
check_command is the full command to run. Specifying the full path is optional if the checks are located somewhere in check_path. These above examples are a copy-and-paste from existing service checks in /etc/cron.d/servicecheck-* files, so migration is fairly easy.
check_interval (optional) If unspecified, the checks will be run at the regular collector interval, which is 60 seconds by default. You may not want to run some checks that frequently, especially if they are resource-intensive, so check_interval lets you force a delay, in seconds, between iterations of that particular check. The state for these are stored in temp_file_path with file names like nagios_wrapper_19fe42bc7cfdc37a2d88684013e66c7b.pck where the hash is an md5sum of the 'name' value (to accommodate odd characters that the filesystem may not like).

Nginx

See the example configuration for how to configure the Nginx plugin.

NTP

This section describes the Network Time Protocol checks that can be performed by the Agent. The NTP checks monitors time offset between NTP server and your own server. The NTP checks requires a configuration file called ntp.yaml to be available in the agent conf.d configuration directory. The config file must contain the hostname and port number, version information, timeout(These are optional params) that you are interested in monitoring.

Sample config:

init_config:

instances:
  - host: pool.ntp.org
    port: ntp
    version: 3
    timeout: 5

The NTP checks return the following metrics:

Metric Name	Dimensions	Semantics
ntp.offset	hostname, ntp_server	Time offset in seconds
ntp.connection_status	hostname, ntp_server	Value of ntp server connection status (0=Healthy)

Postfix Checks

This section describes the Postfix checks that can be performed by the Agent. The Postfix checks gathers metrics on the Postfix. The Postfix checks requires a configuration file called postfix.yaml to be available in the agent conf.d configuration directory. The config file must contain the name, directory and queue that you are interested in monitoring.

NOTE: The user running monasca-agent must have passwordless sudo access for the find command to run the postfix check. Here's an example:

 example /etc/sudoers entry:
          monasca-agent ALL=(ALL) NOPASSWD:/usr/bin/find

Sample config:

init_config:

instances:
    - name: /var/spool/postfix
      directory: /var/spool/postfix
      queues:
          - incoming
          - active
          - deferred

The Postfix return the following metrics:

Metric Name	Dimensions	Semantics
postfix.queue_size	queue	A total number of queues

PostgreSQL

This section describes the PostgreSQL checks that can be performed by the Agent. The PostgreSQL checks requires a configuration file called postgres.yaml to be available in the agent conf.d configuration directory.

Sample config:

init_config:

instances:
   -   host: localhost
       port: 5432
       username: my_username
       password: my_password
       dbname: db_name

If you want to track per-relation (table), you need to add relations keys and specify the list.

       relations:
            - my_table
            - my_other_table

Each metrics show statistics collected in PostgreSQL. The PostgreSQL checks return the following metrics:

Metric Name	Dimensions	Semantics
postgresql.connections	hostname, db, service=postgres	Value of the "numbackends" of "pg_stat_database".
postgresql.commits	hostname, db, service=postgres	Value of the "xact_commit" of "pg_stat_database".
postgresql.rollbacks	hostname, db, service=postgres	Value of the "xact_rollback" of "pg_stat_database".
postgresql.disk_read	hostname, db, service=postgres	Value of the "blks_read" of "pg_stat_database".
postgresql.buffer_hit	hostname, db, service=postgres	Value of the "blks_hit" of "pg_stat_database".
postgresql.rows_returned	hostname, db, service=postgres	Value of the "tup_returned" of "pg_stat_database".
postgresql.rows_fetched	hostname, db, service=postgres	Value of the "tup_fetched" of "pg_stat_database".
postgresql.deadlocks	hostname, db, service=postgres	Value of the "deadlocks" of "pg_stat_database". This is supported only in PostgreSQL 9.2 or later.
postgresql.temp_bytes	hostname, db, service=postgres	Value of the "temp_bytes" of "pg_stat_database". This is supported only in PostgreSQL 9.2 or later.
postgresql.temp_files	hostname, db, service=postgres	Value of the "temp_files" of "pg_stat_database". This is supported only in PostgreSQL 9.2 or later.
postgresql.seq_scans	hostname, db, service=postgres, table	Value of the "seq_scan" of "pg_stat_user_tables"
postgresql.seq_rows_read	hostname, db, service=postgres, table	Value of the "seq_tup_read" of "pg_stat_user_tables"
postgresql.index_scans	hostname, db, service=postgres, table, index	Value of the "idx_scan" of "pg_stat_user_tables" or "pg_stat_user_indexes"
postgresql.index_rows_fetched	hostname, db, service=postgres, table, index	Value of the "idx_tup_fetch" of "pg_stat_user_tables" or "pg_stat_user_indexes"
postgresql.rows_inserted	hostname, db, service=postgres, table	Value of the "n_tup_ins" of "pg_stat_user_tables" or "pg_stat_database"
postgresql.rows_updated	hostname, db, service=postgres, table	Value of the "n_tup_upd" of "pg_stat_user_tables" or "pg_stat_database"
postgresql.rows_deleted	hostname, db, service=postgres, table	Value of the "n_tup_del" of "pg_stat_user_tables" or "pg_stat_database"
postgresql.rows_hot_updated	hostname, db, service=postgres, table	Value of the "n_tup_hot_upd" of "pg_stat_user_tables"
postgresql.live_rows	hostname, db, service=postgres, table	Value of the "n_live_tup" of "pg_stat_user_tables"
postgresql.dead_rows	hostname, db, service=postgres, table	Value of the "n_dead_tup" of "pg_stat_user_tables"
postgresql.index_rows_read	hostname, db, service=postgres, table, index	Value of the "idx_tup_read" of "pg_stat_user_indexes"

Process Checks

Process checks can be performed to both verify that a set of named processes are running on the local system and collect/send system level metrics on those processes. The YAML file process.yaml contains the list of processes that are checked.

The processes that are monitored can be filtered using a pattern to specify the matching process names or distinctly identified by process name or by the username that owns the process.

A Python script process.py runs each execution cycle to check that required processes are alive. If the process is running a value of 0 is sent, otherwise a value of 1 is sent to the Monasca API.

Each process entry consists of one primary key: name. Either search_string or username must be set but you can not set both. Optionally, if an exact match on search_string is required the exact_match boolean can be added to the entry and set to True.

To grab more process metrics beside the process.pid_count, which only shows that the process is up and running, the configuration option detailed must be set to true.

Sample monasca-setup: Monitor by process_names:

monasca-setup -d ProcessCheck -json \
         '{"process_config":[{"process_names":["monasca-notification","monasca-api"],"dimensions":{"service":"monitoring"}}]}'

Monitor by process_username:

monasca-setup -d ProcessCheck -json \
         '{"process_config":[{"process_username":"dbadmin","dimensions":{"service":"monitoring","component":"vertica"}}]}'

Multiple entries in one call:

monasca-setup -d ProcessCheck -json \
         '{"process_config":[{"process_names":["monasca-notification","monasca-api"],"dimensions":{"service":"monitoring"}},
                             {"process_names":["elasticsearch"],"dimensions":{"service":"logging"}},
                             {"process_username":"dbadmin","dimensions":{"service":"monitoring","component":"vertica"}}]}'

Using a yaml config file:

monasca-setup -d ProcessCheck -a "conf_file_path=/home/stack/myprocess.yaml"

Example yaml input file format for process check by process names:


process_config:
- process_names:
  - monasca-notification
  - monasca-api
  dimensions:
    service: monitoring

Example yaml input file format for multiple process_names entries:


process_config:
- process_names:
  - monasca-notification
  - monasca-api
  dimensions:
    service: monitoring
- process_names:
  - elasticsearch
  dimensions:
    service: logging
- process_names:
  - monasca-thresh
  exact_match: 'true'
  dimensions:
    service: monitoring
    component: thresh

Sample successfully built process.yaml:

init_config: null
instances:
- built_by: ProcessCheck
  detailed: true
  dimensions:
    component: monasca-api
    service: monitoring
  exact_match: false
  name: monasca-api
  search_string:
  - monasca-api

- built_by: ProcessCheck
  detailed: true
  dimensions:
    component: monasca-notification
    service: monitoring
  exact_match: false
  name: monasca-notification
  search_string:
  - monasca-notification

- built_by: ProcessCheck
  detailed: true
  dimensions:
    component: vertica
    service: monitoring
  name: vertica
  username: dbadmin

Docker environment:

For Docker environment you can enable the process plugin by adding proccess.yaml to the monasca-agent-collector container (mount plugin file to /plugins.d/process.yaml). Additionally you have to specify the path of the host process filesystem. In this case mount host root directory / to /rootfs in the container. Sample configuration:

init_config:
  process_fs_path: /rootfs/proc
instances:
- name: monasca-collector
  detailed: true
  dimensions:
    service: monasca-collector
  exact_match: false
  search_string:
  - monasca-collector

The process checks return the following metrics ( if detailed is set to true, otherwise process.pid_count is only returned ):

Metric Name	Dimensions	Semantics
process.mem.rss_mbytes	process_name, service, component	Amount of physical memory allocated to a process, including memory from shared libraries in Mbytes
process.io.read_count	process_name, service, component	Number of reads by a process
process.io.write_count	process_name, service, component	Number of writes by a process
process.io.read_kbytes	process_name, service, component	Kbytes read by a process
process.io.write_kbytes	process_name, service, component	Kbytes written by a process
process.thread_count	process_name, service, component	Number of threads a process is using
process.cpu_perc	process_name, service, component	Percentage of cpu being consumed by a process
process.open_file_descriptors	process_name, service, component	Number of files being used by a process
process.pid_count	process_name, service, component	Number of processes that exist with this process name

On Linux, if the Agent is not run as root or the owner of the process the io metrics and the open_file_descriptors metric will fail to be reported if the mon-agent user does not have permission to get it for the process.

Prometheus

This plugin is for scraping metrics from endpoints that are created by prometheus client libraries - https://prometheus.io/docs/instrumenting/clientlibs/

It can be configured in two ways. One being manually setting all the endpoints that you want to scrape. The other being running in a Kubernetes environment where we autodetect on either services or pods based on annotations set.

Manually Configuring Endpoints

In this instance the plugin goes to a configured list of prometheus client endpoints and scrapes the posted metrics from each.

When configuring each endpoint you can define a set of dimensions that is attached to each metric being scraped.

By default we grab the defined labels on each metric as dimensions.

Example yaml file:

init_config:
  # Timeout on connections to each endpoint
  timeout: 3
instances:
  - metric_endpoint: "http://127.0.0.1:8000"
    # Dimensions to add to every metric coming out of the plugin
    default_dimensions:
        app: my_app

  - metric_endpoint: "http://127.0.0.1:9000"

Running in a Kubernetes Environment with autodetection

There are two ways for the autodetection to be set up. One for auto detecting based on pods and the other auto detecting for services. In both cases it is looking for the annotations set for the Kubernetes service or pod.

The annotations the plugin is looking for are -

prometheus.io/scrape: Only scrape pods that have a value of 'true'
prometheus.io/path: If the metrics path is not '/metrics' override this.
prometheus.io/port: Scrape the pod on the indicated port instead of the default of '9102'.
monasca.io/usek8slabels: Attach Kubernetes labels of the pod that is being scraped. Default to 'true'
monasca.io/whitelist: Yaml list of metric names to whitelist against on detected endpoint
monasca.io/metric_types: Yaml dictionary where key is metric name and value is desired type from 'rate' or 'counter'. Metric name will be appended with '_rate' or '_counter' respectively. If not specified, the scraped value will be passed without modification.
monasca.io/report_pod_label_owner: If the metrics that are scraped contain pod as a label key we will attempt to get the pod owner and attach that to the metric as another dimension. Very useful for other scraping from other solutions that monitor k8s (Ex. kube-state-metrics). Default to 'false'

These annotations are pulled from the Kubelet for pod autodetection and the Kubernetes API for the service auto detection

There is also configuration parameter of "kubernetes_labels" where it will look for Kubernetes tags to use as dimensions for metrics coming out. By default that will be set to "app"

Example yaml file (by pod):

init_config:
  timeout: 3
  auto_detect_endpoints: True
  detect_method: "pod"
instances:
- kubernetes_labels: ['app']

Example yaml file (by service):

init_config:
  timeout: 3
  auto_detect_endpoints: True
  detect_method: "service"
instances:
- kubernetes_labels: ['app']

Example k8s manifest annotation section:

annotations:
  prometheus.io/scrape: "true"
  prometheus.io/port: "8080"
  monasca.io/usek8slabels: "false"
  monasca.io/whitelist: |
    - storage
    - cpu
    - memory
  monasca.io/metric_types: "{storage: rate}"

NOTE This Plugin can only have one configured instance

RabbitMQ Checks

This section describes the RabbitMQ check that can be performed by the Agent. The RabbitMQ check gathers metrics on Nodes, Exchanges and Queues from the rabbit server. The RabbitMQ check requires a configuration file called rabbitmq.yaml to be available in the agent conf.d configuration directory. The config file must contain the names of the Exchanges and Queues that you are interested in monitoring.

NOTE: The agent RabbitMQ plugin requires the RabbitMQ Management Plugin to be installed. The management plugin is included in the RabbitMQ distribution. To enable it, use the rabbitmq-plugins command like this:

rabbitmq-plugins enable rabbitmq_management

Sample config:

init_config:

instances:
  - exchanges: [nova, cinder, ceilometer, glance, keystone, neutron, heat]
    nodes: [rabbit@devstack]
    queues: [conductor]
    rabbitmq_api_url: http://localhost:15672/api
    rabbitmq_user: guest
    rabbitmq_pass: guest

If you want the monasca-setup program to detect and auto-configure the plugin for you, you must pass watch_api=true to the plugin, for example:

monasca-setup \
  --detection_plugins rabbitmq \
  --detection_args "watch_api=true"

Additionally, you must create the file /root/.rabbitmq.cnf with the information needed in the configuration yaml file before running the setup program. It should look something like this:

[client]
user=guest
password=pass
nodes=rabbit@devstack
queues=conductor
exchanges=nova,cinder,ceilometer,glance,keystone,neutron,heat

Alternatively, the arguments can be passed on the command line, but note that all arguments must be passed in this case - the configuration file will not be read:

monasca-setup \
  --detection_plugins rabbitmq \
  --detection_args \
    "watch_api=true
     user=guest
     password=pass
     nodes=rabbit@devstack
     queues=conductor
     exchanges=nova,cinder,ceilometer,glance,keystone,neutron,heat"

For more details of each metric, please refer the RabbitMQ documentation. The RabbitMQ checks return the following metrics:

Metric Name	Dimensions	Check Type	Description
rabbitmq.node.fd_used	hostname, node, service=rabbitmq	Node	Value of the "fd_used" field in the response of /api/nodes
rabbitmq.node.sockets_used	hostname, node, service=rabbitmq	Node	Value of the "sockets_used" field in the response of /api/nodes
rabbitmq.node.run_queue	hostname, node, service=rabbitmq	Node	Value of the "run_queue" field in the response of /api/nodes
rabbitmq.node.mem_used	hostname, node, service=rabbitmq	Node	Value of the "mem_used" field in the response of /api/nodes
rabbitmq.exchange.messages.received_count	hostname, exchange, vhost, type, service=rabbitmq	Exchange	Value of the "publish_in" field of "message_stats" object
rabbitmq.exchange.messages.received_rate	hostname, exchange, vhost, type, service=rabbitmq	Exchange	Value of the "rate" field of "message_stats/publish_in_details" object
rabbitmq.exchange.messages.published_count	hostname, exchange, vhost, type, service=rabbitmq	Exchange	Value of the "publish_out" field of "message_stats" object
rabbitmq.exchange.messages.published_rate	hostname, exchange, vhost, type, service=rabbitmq	Exchange	Value of the "rate" field of "message_stats/publish_out_details" object
rabbitmq.queue.consumers	hostname, queue, vhost, service=rabbitmq	Queue	Number of consumers
rabbitmq.queue.memory	hostname, queue, vhost, service=rabbitmq	Queue	Bytes of memory consumed by the Erlang process associated with the queue, including stack, heap and internal structures
rabbitmq.queue.active_consumers	hostname, queue, vhost, service=rabbitmq	Queue
rabbitmq.queue.messages	hostname, queue, vhost, service=rabbitmq	Queue	Sum of ready and unacknowledged messages (queue depth)
rabbitmq.queue.messages.rate	hostname, queue, vhost, service=rabbitmq	Queue	Value of the "rate" field of "message_details" object
rabbitmq.queue.messages.ready	hostname, queue, vhost, service=rabbitmq	Queue	Number of messages ready to be delivered to clients
rabbitmq.queue.messages.ready_rate	hostname, queue, vhost, service=rabbitmq	Queue	Value of the "rate" field of "message_ready_details" object
rabbitmq.queue.messages.publish_count	hostname, queue, vhost, service=rabbitmq	Queue	Value of the "publish" field of "message_stats" object
rabbitmq.queue.messages.publish_rate	hostname, queue, vhost, service=rabbitmq	Queue	Value of the "rate" field of "message_stats/publish_details" object
rabbitmq.queue.messages.deliver_count	hostname, queue, vhost, service=rabbitmq	Queue	Value of the "deliver" field of "message_stats" object
rabbitmq.queue.messages.deliver_rate	hostname, queue, vhost, service=rabbitmq	Queue	Value of the "rate" field of "message_stats/deliver_details" object
rabbitmq.queue.messages.redeliver_count	hostname, queue, vhost, service=rabbitmq	Queue	Value of the "redeliver" field of "message_stats" object
rabbitmq.queue.messages.redeliver_rate	hostname, queue, vhost, service=rabbitmq	Queue	Value of the "rate" field of "message_stats/redeliver_details" object
rabbitmq.queue.messages.unacknowledged	hostname, queue, vhost, service=rabbitmq	Queue	Number of messages delivered to clients but not yet acknowledged
rabbitmq.queue.messages.unacknowledged_rate	hostname, queue, vhost, service=rabbitmq	Queue	Value of the "rate" field of "message_stats/messages_unacknowledged_details" object
rabbitmq.queue.messages.deliver_get_count	hostname, queue, vhost, service=rabbitmq	Queue	Value of the "deliver_get" field of "message_stats" object
rabbitmq.queue.messages.deliver_get_rate	hostname, queue, vhost, service=rabbitmq	Queue	Value of the "rate" field of "message_stats/deliver_get_details" object
rabbitmq.queue.messages.ack_count	hostname, queue, vhost, service=rabbitmq	Queue
rabbitmq.queue.messages.ack_rate	hostname, queue, vhost, service=rabbitmq	Queue

RedisDB

See the example configuration for how to configure the plugin.

Riak

See the example configuration for how to configure the Riak plugin.

SolidFire

The SolidFire checks require a matching solidfire.yaml to be present. Currently the checks report a mixture of cluster utilization and health metrics. Multiple clusters can be monitored via separate instance stanzas in the config file.

Sample config:

instances:
    - name: cluster_rack_d
      username: cluster_admin
      password: secret_password
      mvip: 192.168.1.1

The SolidFire checks return the following metrics:

Metric Name	Dimensions	Semantics
solidfire.active_cluster_faults	service=solidfire, cluster	Amount of active cluster faults, such as failed drives
solidfire.cluster_utilization	service=solidfire, cluster	Overall cluster IOP utilization
solidfire.num_iscsi_sessions	service=solidfire, cluster	Amount of active iSCSI sessions connected to the cluster
solidfire.iops.avg_5_sec	service=solidfire, cluster	Average IOPs over the last 5 seconds
solidfire.iops.avg_utc	service=solidfire, cluster	Average IOPs since midnight UTC
solidfire.iops.peak_utc	service=solidfire, cluster	Peak IOPS since midnight UTC
solidfire.iops.max_available	service=solidfire, cluster	Theoretical maximum amount of IOPs
solidfire.active_block_bytes	service=solidfire, cluster	Amount of space consumed by the block services, including cruft
solidfire.active_meta_bytes	service=solidfire, cluster	Amount of space consumed by the metadata services
solidfire.active_snapshot_bytes	service=solidfire, cluster	Amount of space consumed by the metadata services for snapshots
solidfire.provisioned_bytes	service=solidfire, cluster	Total number of provisioned bytes
solidfire.unique_blocks_used_bytes	service=solidfire, cluster	Amount of space the unique blocks take on the block drives
solidfire.max_block_bytes	service=solidfire, cluster	Maximum amount of bytes allocated to the block services
solidfire.max_meta_bytes	service=solidfire, cluster	Maximum amount of bytes allocated to the metadata services
solidfire.max_provisioned_bytes	service=solidfire, cluster	Max provisionable space if 100% metadata space used
solidfire.max_overprovisioned_bytes	service=solidfire, cluster	Max provisionable space * 5, artificial safety limit
solidfire.unique_blocks	service=solidfire, cluster	Number of blocks(not always 4KiB) stored on block drives
solidfire.non_zero_blocks	service=solidfire, cluster	Number of 4KiB blocks with data after the last garbage collection
solidfire.zero_blocks	service=solidfire, cluster	Number of 4KiB blocks without data after the last garbage collection
solidfire.thin_provision_factor	service=solidfire, cluster	Thin provisioning factor, (nonZeroBlocks + zeroBlocks) / nonZeroBlocks
solidfire.deduplication_factor	service=solidfire, cluster	Data deduplication factor, nonZeroBlocks / uniqueBlocks
solidfire.compression_factor	service=solidfire, cluster	Data compression factor, (uniqueBlocks * 4096) / uniqueBlocksUsedSpace
solidfire.data_reduction_factor	service=solidfire, cluster	Aggregate data reduction efficiency, thin_prov * dedup * compression

SQLServer

See the example configuration for how to configure the SQLServer plugin.

Supervisord

See the example configuration for how to configure the Supervisord plugin.

Swift Diags

See the example configuration for how to configure the Swift Diags plugin.

TCP Check

See the example configuration for how to configure the TCP Check plugin.

Varnish

See the example configuration for how to configure the Varnish plugin.

VCenter

This plugin provides metrics for VMware ESX clusters. It connects to vCenter server with its credentials and collects the configured cluster's performance data.

Sample Config

init_config: {}
instances:
    - vcenter_ip: <vcenter-ip or fqdn>
        username: <vcenter-user>
        password: <vcenter-password>
        clusters: <[cluster-name-list]> # e.g: [cluster-1, cluster-2]

ESX Cluster Metrics

Below are the list of metrics collected by this plugin from the configured cluster:

Metric Name	Description
vcenter.cpu.total_mhz	Total amount of CPU resources of all hosts in the cluster, as measured in megahertz. ESX counter name: cpu.totalmhz.average
vcenter.cpu.used_mhz	Sum of the average CPU usage values, in megahertz, of all virtual machines in the cluster. ESX counter name: cpu.usagemhz.average
vcenter.cpu.used_perc	CPU usage in percent, during the interval
vcenter.cpu.total_logical_cores	Aggregated number of CPU threads. ESX counter name: numCpuThreads
vcenter.mem.total_mb	Total amount of machine memory of all hosts in the cluster that is available for guest memory and guest overhead memory. ESX counter name: mem.consumed.average
vcenter.mem.used_mb	A cluster's consumed memory consists of guest consumed memory and overhead memory. It does not include host-specific overhead memory. ESX counter name: mem.consumed.average
vcenter.mem.used_perc	A cluster's consumed memory in percentage
vcenter.disk.total_space_mb	Aggregation of maximum capacities of datastores connected to the hosts of a cluster, in megabytes. ESX counter name: summary.capacity
vcenter.disk.total_used_space_mb	Aggregation of all available capacities of datastores connected to the hosts of a cluster, in megabytes. ESX counter name: summary.freeSpace
vcenter.disk.total_used_space_perc	Aggregation of all available capacities of datastores connected to the hosts of a cluster, in percent

ESX Cluster Dimensions

    "vcenter_ip": <vcenter-ip or fqdn>,
    "cluster": <cluster-name>,
    "host_type": "compute_node",
    "role": "esx",
    "id": <cluster-name>-<vcenter-ip or fqdn>

VCenter Slim

This plugin provides exclusively vm status metrics for VMware ESX clusters. Includes configuration for which annotations to add to dimensions via allowed_keys (collects annotations with that key, if available) and key_map (replaces annotation key when creating dimension). In the example below, the resulting metrics will have a dimension of 'tenant_id' with the value from the 'project_id' annotation.

Sample Config

init_config:
  vcenter_ip: "127.0.0.1"
  vcenter_user: "joe"
  vcenter_password: "12345"
  vcenter_port: 443
  retry_count: 3
  poll_interval: 0.5
  vcenter_max_objects: 100000
  allowed_keys:
  - project_id
  key_map:
    project_id: tenant_id

instances:
  # this plugin doesn't support instances, this section will be ignored (but is still required for structure)

Metric Name	Description
vm.status	The connection status of the vm. Value is 0 if the vm can be managed normally, 1 for all other states

Vertica Checks

This section describes the vertica check that can be performed by the Agent. The vertica check requires a configuration file called vertica.yaml to be available in the agent conf.d configuration directory.

Sample config:

init_config:

instances:
    user: mon_api
    password: password
    service: monasca (optional, defaults to vertica)
    timeout: 3 (optional, defaults to 3 seconds)

Metric Name	Dimensions	Semantics
vertica.license_usage_percent	hostname, service=vertica	Percentage of the license size taken up.
vertica.connection_status	hostname, node_name, service=vertica	Value of DB connection status (0=Healthy).
vertica.node_status	hostname, node_name, service=vertica	Status of node connection (0=UP).
vertica.projection.ros_count	hostname, node_name, projection_name, service=vertica	The number of ROS containers in the projection.
vertica.projection.tuple_mover_mergeouts	hostname, node_name, projection_name, service=vertica	Number of current tuple mover mergeouts on this projection.
vertica.projection.tuple_mover_moveouts	hostname, node_name, projection_name, service=vertica	Number of current tuple mover moveout on this projection.
vertica.projection.wos_used_bytes	hostname, node_name, projection_name, service=vertica	The number of WOS bytes in the projection.).
vertica.resource.disk_space_rejections	hostname, node_name, service=vertica	The number of rejected disk write requests.
vertica.resource.pool.memory_inuse_kb	hostname, node_name, resource_pool, service=vertica	Amount of memory, in kilobytes, acquired by requests running against this pool.
vertica.resource.pool.memory_size_actual_kb	hostname, node_name, resource_pool, service=vertica	Current amount of memory, in kilobytes, allocated to the pool by the resource manager.
vertica.resource.pool.rejection_count	hostname, node_name, resource_pool, service=vertica	Number of resource rejections for this pool
vertica.resource.pool.running_query_count	hostname, node_name, resource_pool, service=vertica	Number of queries actually running using this pool.
vertica.resource.request_queue_depth	hostname, node_name, service=vertica	The cumulative number of requests for threads, file handles, and memory.
vertica.resource.resource_rejections	hostname, node_name, service=vertica	The number of rejected plan requests.
vertica.resource.wos_used_bytes	hostname, node_name, service=vertica	The size of the WOS in bytes.

WMI Check

ZooKeeper

This section describes the Zookeeper check that can be performed by the Agent. The Zookeeper check requires a configuration file called zk.yaml to be available in the agent conf.d configuration directory. The Zookeeper check parses the result of zookeeper's stat admin command.

Sample config:

init_config:

instances:
  - host: localhost
    port: 2181
    timeout: 3

The Zookeeper checks return the following metrics:

Metric Name	Dimensions	Semantics
zookeeper.max_latency_sec	hostname, mode, service=zookeeper	Maximum latency in second
zookeeper.min_latency_sec	hostname, mode, service=zookeeper	Minimum latency in second
zookeeper.avg_latency_sec	hostname, mode, service=zookeeper	Average latency in second
zookeeper.out_bytes	hostname, mode, service=zookeeper	Sent bytes
zookeeper.outstanding_bytes	hostname, mode, service=zookeeper	Outstanding bytes
zookeeper.in_bytes	hostname, mode, service=zookeeper	Received bytes
zookeeper.connections_count	hostname, mode, service=zookeeper	Number of connections
zookeeper.node_count	hostname, mode, service=zookeeper	Number of nodes
zookeeper.zxid_count	hostname, mode, service=zookeeper	Count number
zookeeper.zxid_epoch	hostname, mode, service=zookeeper	Epoch number

Kibana

This section describes the Kibana check that can be performed by the Agent. The Kibana check requires a configuration file containing Kibana configuration (it is the same file Kibana is using).

Check is accessing status endpoint (curl -XGET http://localhost:5601/api/status) of Kibana, which means it can work only with Kibana >= 4.2.x, that was first to introduce this capability.

Sample config:

init_config:
  url: http://localhost:5601/api/status
instances:
- built_by: Kibana
  metrics:
    - heap_size
    - heap_used
    - load
    - req_sec
    - resp_time_avg
    - resp_time_max

The Kibana checks return the following metrics:

Metric Name	Dimensions	Semantics
kibana.load_avg_1m	hostnam, version, service=monitoring	The average kibana load over a 1 minute period, for more details see here
kibana.load_avg_5m	hostnam, version, service=monitoring	The average kibana load over a 5 minutes period, for more details see here
kibana.load_avg_15m	hostnam, version, service=monitoring	The average kibana load over a 15 minutes period, for more details see here
kibana.heap_size_mb	hostnam, version, service=monitoring	Total heap size in MB
kibana.heap_used_mb	hostnam, version, service=monitoring	Used heap size in MB
kibana.req_sec	hostnam, version, service=monitoring	Requests per second to Kibana server
kibana.resp_time_avg_ms	hostnam, version, service=monitoring	The average response time of Kibana server in ms
kibana.resp_time_max_ms	hostnam, version, service=monitoring	The maximum response time of Kibana server in ms

OpenStack Monitoring

The monasca-setup script when run on a system that is running OpenStack services, configures the Agent to send the following list of metrics:

The setup program creates process checks for each process that is part of an OpenStack service. A few sample metrics from the process check are provided. For the complete list of process metrics, see the [Process Checks](#Process Checks) section.
Additionally, an http_status check will be setup on the api for the service, if there is one.

PLEASE NOTE: The monasca-setup program will only install checks for OpenStack services it detects when it is run. If an additional service is added to a particular node or deleted, monasca-setup must be re-run to add monitoring for the additional service or remove the service that is no longer there.

Nova Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Nova service.

The following nova processes are monitored, if they exist when the monasca-setup script is run:

Nova Processes Monitored

nova-compute
nova-conductor
nova-cert
nova-network
nova-scheduler
nova-novncproxy
nova-xvpncproxy
nova-consoleauth
nova-objectstore
nova-api

Example Nova Metrics

Component	Metric Name	Metric Type	Check Type	Dimensions	Plugin	Description	Notes
nova-compute	processes.process_pid_count	Gauge	Passive	service=nova, component=nova-compute	process	nova-compute process exists	This is only one of the process checks performed
nova-api	processes.process_pid_count	Gauge	Passive	service=nova, component=nova-api	process	nova-api process pid count	This is only one of the process checks performed
nova-api	http_status	Gauge	Active	service=nova, component=nova-api url=url_to_nova_api	http_status	nova-api http endpoint is alive	This check should be executed on multiple systems.

Swift Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Swift service.

The following swift processes are monitored, if they exist when the monasca-setup script is run:

Swift Processes Monitored

swift-container-updater
swift-account-auditor
swift-object-replicator
swift-container-replicator
swift-object-auditor
swift-container-auditor
swift-account-reaper
swift-container-sync
swift-account-replicator
swift-object-updater
swift-object-server
swift-account-server
swift-container-server
swift-proxy-server

Example Swift Metrics

Component	Metric Name	Metric Type	Check Type	Dimensions	Plugin	Description	Notes
swift-container-updater	processes.process_pid_count	Gauge	Passive	service=swift, component=swift-container-updater	process	swift-container-updater process exists	This is only one of the process checks performed
swift-proxy-server	processes.process_pid_count	Gauge	Passive	service=swift, component=swift-proxy-server	process	swift-proxy-server process pid count	This is only one of the process checks performed
swift-proxy-server	http_status	Gauge	Active	service=swift, component=swift-proxy-server url=url_to_swift_proxy_server	http_status	swift-proxy-server http endpoint is alive	This check should be executed on multiple systems.

Glance Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Glance service.

The following glance processes are monitored, if they exist when the monasca-setup script is run:

Glance Processes Monitored

glance-registry
glance-api

Example Glance Metrics

Component	Metric Name	Metric Type	Check Type	Dimensions	Plugin	Description	Notes
glance-registry	processes.process_pid_count	Gauge	Passive	service=glance, component=glance-registry	process	glance-registry process exists	This is only one of the process checks performed
glance-api	processes.process_pid_count	Gauge	Passive	service=glance, component=glance-api	process	glance-api process pid count	This is only one of the process checks performed
glance-api	http_status	Gauge	Active	service=glance, component=glance-api url=url_to_glance_api	http_status	glance-api http endpoint is alive	This check should be executed on multiple systems.

Cinder Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Cinder service.

The following cinder processes are monitored, if they exist when the monasca-setup script is run:

Cinder Processes Monitored

cinder-volume
cinder-scheduler
cinder-api

Example Cinder Metrics

Component	Metric Name	Metric Type	Check Type	Dimensions	Plugin	Description	Notes
cinder-volume	processes.process_pid_count	Gauge	Passive	service=cinder, component=cinder-volume	process	cinder-volume process exists	This is only one of the process checks performed
cinder-api	processes.process_pid_count	Gauge	Passive	service=cinder, component=cinder-api	process	cinder-api process pid count	This is only one of the process checks performed
cinder-api	http_status	Gauge	Active	service=cinder, component=cinder-api url=url_to_cinder_api	http_status	cinder-api http endpoint is alive	This check should be executed on multiple systems.

Neutron Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Neutron service.

The following neutron processes are monitored, if they exist when the monasca-setup script is run:

Neutron Processes Monitored

neutron-server
neutron-openvswitch-agent
neutron-rootwrap
neutron-dhcp-agent
neutron-vpn-agent
neutron-metadata-agent
neutron-metering-agent
neutron-ns-metadata-proxy

Example Neutron Metrics

Component	Metric Name	Metric Type	Check Type	Dimensions	Plugin	Description	Notes
neutron-server	processes.process_pid_count	Gauge	Passive	service=neutron, component=neutron-server	process	neutron-server process exists	This is only one of the process checks performed
neutron-ns-metadata-proxy	processes.process_pid_count	Gauge	Passive	service=neutron, component=neutron-ns-metadata-proxy	process	neutron-ns-metadata-proxy process pid count	This is only one of the process checks performed
neutron-ns-metadata-proxy	http_status	Gauge	Active	service=neutron, component=neutron-ns-metadata-proxy url=url_to_neutron_api	http_status	neutron-ns-metadata-proxy http endpoint is alive	This check should be executed on multiple systems.

Keystone Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Keystone service.

The following keystone processes are monitored, if they exist when the monasca-setup script is run:

Keystone Processes Monitored

keystone-all

Example Keystone Metrics

Component	Metric Name	Metric Type	Check Type	Dimensions	Plugin	Description	Notes
keystone-all	processes.process_pid_count	Gauge	Passive	service=keystone, component=keystone-all	process	keystone-all process pid count	This is only one of the process checks performed
keystone-all	http_status	Gauge	Active	service=keystone, component=keystone-all url=url_to_keystone_api	http_status	keystone-all http endpoint is alive	This check should be executed on multiple systems.

Ceilometer Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Ceilometer service.

The following ceilometer processes are monitored, if they exist when the monasca-setup script is run:

Ceilometer Processes Monitored

ceilometer-agent-compute
ceilometer-agent-central
ceilometer-agent-notification
ceilometer-collector
ceilometer-alarm-notifier
ceilometer-alarm-evaluator
ceilometer-api

Example Ceilometer Metrics

Component	Metric Name	Metric Type	Check Type	Dimensions	Plugin	Description	Notes
ceilometer-agent-compute	processes.process_pid_count	Gauge	Passive	service=ceilometer, component=ceilometer-agent-compute	process	ceilometer-agent-compute process exists	This is only one of the process checks performed
ceilometer-api	processes.process_pid_count	Gauge	Passive	service=ceilometer, component=ceilometer-api	process	ceilometer-api process pid count	This is only one of the process checks performed
ceilometer-api	http_status	Gauge	Active	service=ceilometer, component=ceilometer-api url=url_to_ceilometer_api	http_status	ceilometer-api http endpoint is alive	This check should be executed on multiple systems.

Freezer Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Freezer service.

The following Freezer processes are monitored, if they exist when the monasca-setup script is run:

Freezer Processes Monitored

freezer-scheduler
freezer-api

Example Freezer Metrics

Component	Metric Name	Metric Type	Check Type	Dimensions	Plugin	Description	Notes
freezer-api	processes.process_pid_count	Gauge	Passive	service=backup, component=freezer-api	process	freezer-api process pid count	This is only one of the process checks performed
freezer-api	http_status	Gauge	Active	service=backup, component=freezer-api url=url_to_freezer_api	http_status	freezer-api http endpoint is alive	This check should be executed on multiple systems.
freezer-scheduler	processes.process_pid_count	Gauge	Passive	service=backup, component=freezer-scheduler	process	freezer-scheduler process pid count	This is only one of the process checks performed

Magnum Checks

This section documents a sampling of the metrics generated by the checks setup automatically by the monasca-setup script for the OpenStack Magnum service.

The following Magnum processes are monitored, if they exist when the monasca-setup script is run:

Magnum Processes Monitored

magnum-api
magnum-controller

Example Magnum Metrics

Component	Metric Name	Metric Type	Check Type	Dimensions	Plugin	Description	Notes
magnum-api	processes.process_pid_count	Gauge	Passive	service=container-infra, component=magnum-api	process	magnum-api process pid count	This is only one of the process checks performed
magnum-api	http_status	Gauge	Active	service=container-infra, component=magnum-api url=url_to_magnum_api	http_status	magnum-api http endpoint is alive	This check should be executed on multiple systems
magnum-controller	processes.process_pid_count	Gauge	Passive	service=container-infra, component=magnum-conductor	process	magnum-conductor process pid count	This is only one of the process checks performed

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Standard Plugins

Dot File Configuration

Plugin Configuration

init_config

instances

dimensions

Plugin Documentation

Detection Plugins

Plugin

ArgsPlugin

ServicePlugin

List of Detection Plugins

Agent Plugin Detail

System Metrics

CPU

Load

Memory

Disk

Network

Monasca Agent

Limiting System Metrics

A10

Apache

Cacti

cAdvisor_host

Cassandra Checks

Cassandra Processes Monitored

Example Cassandra Metrics

Check_MK_Local

Ceph

Certificate Expiration (HTTPS)

Congestion

Configuration

Couch

Couchbase

Crash

Overview

Metrics

Configuration

Directory Checks

Docker

Elasticsearch Checks

Additional links

File Size

GearmanD

Gunicorn

HAProxy

HDFS

Host Alive

HTTP (endpoint status)

HTTP Metrics

InfluxDB

InfluxDB-Relay

IIS

Jenkins

JsonPlugin

Simple Reporting

Writing and Locking the Metrics File

Additional Directives

Custom JSON file locations

The monasca.json_plugin.status Metric

Kafka Checks

Kubernetes

Kubernetes_API

KyotoTycoon

Libvirt VM Monitoring

Open vSwitch Neutron Router Monitoring

Lighttpd

LXC

Mcache

MK Livestatus

Mongo

MySQL Checks

Note

Nagios Wrapper

Nginx

NTP

Postfix Checks

PostgreSQL

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