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Table of Contents
Nature of Metrics
In Monasca, a metric type is uniquely identified by a name and a specific set of dimensions. The set of dimensions of a metric are a dictionary of (key, value) pairs. A measurement is a metric instance with a value and a timestamp. Measurements are searchable from the Monasca API by name and dimension (key, value).
Optionally, a measurement may also contain extra data about the value, which is known as value_meta. value_ meta is a dictionary of (key, value) pairs that contain textual data that relates to the value of the measurement. If value_meta is included with a measurement, it is returned when the measurement is read via the Monasca API. Unlike dimensions, value_meta is not searchable from the Monasca API, and it is ignored when computing statistics on measurements such as average.
Naming conventions
Common Naming Conventions
Metric Names
Although metric names in the Monasca API can be any string the Monasca Agent uses several naming conventions as follows:
- All lowercase characters.
- '.' is used to hierarchically group. This is done for compatibility with Graphite which assumes a '.' as a delimiter.
- '_' is used to separate words in long names that are not meant to be hierarchical.
System Dimensions
Dimensions are a dictionary of (key, value) pairs that can be used to describe metrics. Dimensions are supplied to the API by the Agent.
This section documents some of the common naming conventions for dimensions that should observed by the monitoring agents/checks to improve consistency and make it easier to create alarms and perform queries.
The agent will automatically add a hostname dimension; beyond that, dimensions are optional. Dimensions can be defined in the primary agent config and applied to all metrics, set per plugin configuration or set during collection.
The order of precedence (high to low) for all dimensions is:
-
Any dimension defined in an Agent plugin config file.
-
Any dimension defined in the Agent config file.
-
Any default dimension set in the plugin code itself.
If a dimension is defined in more than one place, the dimension will be set to the value of the highest precedence above. This allows dimensions to be overridden at any level, if desired.
Common Dimensions
| Name | Description |
|---|---|
| hostname | The FQDN of the host being measured. |
| observer_host | The FQDN of the host that runs a check against another host. |
| url | In the case of the http endpoint check the url of the http endpoint being checked. |
| device | The device name |
| service | The service name that owns this metric |
| component | The component name within the device that the metric comes from |
One way to add additional dimensions for all metrics is by using the --dimensions command line option to monasca-setup. This will populate /etc/monasca/agent/agent.yaml with dimensions to be included with all metrics. The syntax is a comma separated list of name/value pairs, 'name:value,name2:value2'
/etc/monasca/agent/agent.yaml
Main:
dimensions:
service: monitoring
hostname: mini-mon
Component Default Dimensions
| Component Name | Dimensions |
|---|---|
| Collector | component:monasca-agent |
| Kafka Consumer | component:kafka, service:kafka |
| LibVirt | device:disk[0].device, device:vnic[0].name |
| WMI Check | tag from the result if there's a tag_by value (e.g.: "name:jenkins") |
| Zookeeper | component:zookeeper, service:zookeeper |
| Redis | redis_host: localhost, redis_port: port |
OpenStack Specific Naming Conventions
This section documents some of the naming conventions that are used for monitoring OpenStack.
Metric Names
Where applicable, each metric name will list the name of the service (e.g. "compute"), component (e.g. nova-api) and the check (e.g. "process_exists"). For example, "nova.api.process_exists".
Dimensions
This section documents dimensions that are commonly used in monitoring OpenStack.
| Name | Description | Examples |
|---|---|---|
| region | An OpenStack region. | uswest and useast |
| zone | An OpenStack zone | Examples include 1, 2 or 3 |
| service | The name of the OpenStack service being measured. | compute or image or monitoring |
| component | The component in the OpenStack service being measured. | nova-api, nova-scheduler, mysql or rabbitmq. |
| resource_id | The resource ID of an OpenStack resource. | |
| tenant_name | The tenant name of the owner of an OpenStack resource. |
Cross-Tenant Metric Submission
If the owner of the VM is to receive his or her own metrics, the Agent needs to
be able to submit metrics on their behalf. This is called cross-tenant metric
submission. To be allowed to do that, the Agent's Keystone username and project
(tenant) has to be assigned to one of the delegate_authorized_roles. The
authorized roles are configured in monasca-api. The Agent's username is
contained as username in /etc/monasca/agent/agent.yaml, and passed to
monasca-setup as the -u parameter. The Agent's project name is also
contained in agent.yaml as project_name, and passed to monasca-setup as
the --project-name parameter.
In the below example, the Agent's Keystone username is "monasca-agent" and the Agent's Keystone project name is "mini-mon".
Example commands to add the Agent user/project to the monitoring-delegate role:
$ openstack role create monitoring-delegate
$ openstack role add --user monasca-agent --project mini-mon monitoring-delegate
Once the Agent's user and project are assigned to the monitoring-delegate group, the Agent can submit metrics for other tenants.
StatsD
The Monasca Agent ships with a StatsD daemon implementation. A StatsD client can be used to send metrics to the Forwarder via the StatsD daemon.
monasca-statsd will accept counters, gauges and timing values following the standard StatsD protocol. Dimensions are supported and compatible with the DogStatsD extension for tags. Support for the monasca-statsd Python client library is deprecated and might be removed in the future.
Statsd metrics are not bundled along with the metrics gathered by the Collector, but are flushed to the agent Forwarder on a separate schedule (every 10 seconds by default, rather than 60 seconds for Collector metrics).
Here is an example of metrics submitted using the standard statsd Python client library.
import statsd
statsd.increment('processed', 5) # Increment 'processed' metric by 5
statsd.timing('pipeline', 2468.34) # Pipeline took 2468.34 ms to execute
statsd.gauge('gaugething', 3.14159265) # 'gauge' would be the preferred metric type for Monitoring
StatsD Protocol Compatiblity
The moansca-statsd daemon supports the following parts of the StatsD protocol and its extensions:
StatsD 1.0
- counters
- gauges
- timings (no histograms)
DogStatsD
- dimensions/tags (
key:value, tags without value will be mapped to<tag>:True)
Monasca
- rates
Examples
The monasca-statsd library provides a Python-based implementation of a statsd client but also adds the ability to add dimensions to the statsd metrics for the client.
Here are some examples of how code can be instrumented using calls to monasca-statsd.
-
Import the module once it's installed.
from monascastatsd import monasca_statsd statsd = monasca_statsd.MonascaStatsd() -
Optionally, configure the host and port if you're running Statsd on a non-standard port.
statsd.connect('localhost', 8125) -
Increment a counter.
statsd.increment('page_views') With dimensions: statsd.increment('page_views', 5, dimensions={'Hostname': 'prod.mysql.abccorp.com'}) -
Record a gauge 50% of the time.
statsd.gauge('users_online', 91, sample_rate=0.5) With dimensions: statsd.gauge('users_online', 91, dimensions={'Origin': 'Dev', 'Environment': 'Test'}) -
Time a function call.
@statsd.timed('page.render') def render_page(): # Render things... -
Time a block of code.
with statsd.time('database_read_time', dimensions={'db_host': 'mysql1.mycompany.net'}): # Do something...
License
(C) Copyright 2015-2016 Hewlett Packard Enterprise Development LP