The Telemetry module offers several mechanisms from which the persisted data can be accessed. As described in and in the collected information can be stored in one or more database back ends, which are hidden by the Telemetry RESTful API. It is highly recommended not to access directly the database and read or modify any data in it. The API layer hides all the changes in the actual database schema and provides a standard interface to expose the samples, alarms and so forth.

The Telemetry module provides a RESTful API, from which the collected samples and all the related information can be retrieved, like the list of meters, alarm definitions and so forth. The Telemetry API URL can be retrieved from the service catalog provided by OpenStack Identity, which is populated during the installation process. The API access needs a valid token and proper permission to retrieve data, as described in . Further information about the available API endpoints can be found in the Telemetry API Reference.

The API provides some additional functionalities, like querying the collected data set. For the samples and alarms API endpoints, both simple and complex query styles are available, whereas for the other endpoints only simple queries are supported. After validating the query parameters, the processing is done on the database side in the case of most database back ends in order to achieve better performance.

Many of the API endpoints accept a query filter argument, which should be a list of data structures that consist of the following items: field op value type Regardless of the endpoint on which the filter is applied on, it will always target the fields of the Sample type. Several fields of the API endpoints accept shorter names than the ones defined in the reference. The API will do the transformation internally and return the output with the fields that are listed in the API reference. The fields are the following: project_id: project resource_id: resource user_id: user When a filter argument contains multiple constraints of the above form, a logical AND relation between them is implied.

The filter expressions of the complex query feature operate on the fields of Sample, Alarm and AlarmChange types. The following comparison operators are supported: = != < <= > >= The following logical operators can be used: and or not The not operator has different behavior in MongoDB and in the SQLAlchemy-based database engines. If the not operator is applied on a non existent metadata field then the result depends on the database engine. In case of MongoDB, it will return every sample as the not operator is evaluated true for every sample where the given field does not exist. On the other hand the SQL-based database engine will return an empty result because of the underlying join operation. Complex query supports specifying a list of orderby expressions. This means that the result of the query can be ordered based on the field names provided in this list. When multiple keys are defined for the ordering, these will be applied sequentially in the order of the specification. The second expression will be applied on the groups for which the values of the first expression are the same. The ordering can be ascending or descending. The number of returned items can be bounded using the limit option. The filter, orderby and limit fields are optional. As opposed to the simple query, complex query is available via a separate API endpoint. For more information see the Telemetry v2 Web API Reference.

The sample data can be used in various ways for several purposes, like billing or profiling. In external systems the data is often used in the form of aggregated statistics. The Telemetry API provides several built-in functions to make some basic calculations available without any additional coding. Telemetry supports the following statistics and aggregation functions: avg Average of the sample volumes over each period. cardinality Count of distinct values in each period identified by a key specified as the parameter of this aggregate function. The supported parameter values are: project_id resource_id user_id The aggregate.param option is required. count Number of samples in each period. max Maximum of the sample volumes in each period. min Minimum of the sample volumes in each period. stddev Standard deviation of the sample volumes in each period. sum Sum of the sample volumes over each period. The simple query and the statistics functionality can be used together in a single API request.

The Telemetry module provides a command line client, with which the collected data is available just as the alarm definition and retrieval options. The client uses the Telemetry RESTful API in order to execute the requested operations. To be able to use the ceilometer command, the python-ceilometerclient package needs to be installed and configured properly. For details about the installation process, see the Telemetry chapter in the OpenStack Installation Guide. The Telemetry module captures the user-visible resource usage data. Therefore the database will not contain any data without the existence of these resources, like VM images in the OpenStack Image service. Similarly to other OpenStack command line clients, the ceilometer client uses OpenStack Identity for authentication. The proper credentials and --auth_url parameter have to be defined via command line parameters or environment variables. This section provides some examples without the aim of completeness. These commands can be used for instance for validating an installation of Telemetry. To retrieve the list of collected meters, the following command should be used: $ ceilometer meter-list +------------------------+------------+------+------------------------------------------+----------------------------------+----------------------------------+ | Name | Type | Unit | Resource ID | User ID | Project ID | +------------------------+------------+------+------------------------------------------+----------------------------------+----------------------------------+ | cpu | cumulative | ns | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | cpu | cumulative | ns | c8d2e153-a48f-4cec-9e93-86e7ac6d4b0b | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | cpu_util | gauge | % | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | cpu_util | gauge | % | c8d2e153-a48f-4cec-9e93-86e7ac6d4b0b | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.device.read.bytes | cumulative | B | bb52e52b-1e42-4751-b3ac-45c52d83ba07-hdd | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.device.read.bytes | cumulative | B | bb52e52b-1e42-4751-b3ac-45c52d83ba07-vda | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.device.read.bytes | cumulative | B | c8d2e153-a48f-4cec-9e93-86e7ac6d4b0b-hdd | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.device.read.bytes | cumulative | B | c8d2e153-a48f-4cec-9e93-86e7ac6d4b0b-vda | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | ... | +------------------------+------------+------+------------------------------------------+----------------------------------+----------------------------------+ The ceilometer command was run with admin rights, which means that all the data is accessible in the database. For more information about access right see . As it can be seen on the above example, there are two VM instances existing in the system, as there are VM instance related meters on the top of the result list. The existence of these meters does not indicate that these instances are running at the time of the request. The result contains the currently collected meters per resource, in an ascending order based on the name of the meter. Samples are collected for each meter that is present in the list of meters, except in case of instances that are not running or deleted from the OpenStack Compute database. If an instance is no more existing and there is time_to_live value is set in the ceilometer.conf configuration file, then a group of samples are deleted in each expiration cycle. When the last sample is deleted for a meter, the database can be cleaned up by running ceilometer-expirer and the meter will not be present in the list above anymore. For more information about the expiration procedure see . The Telemetry API supports simple query on the meter endpoint. The query functionality has the following syntax: --query <field1><operator1><value1>;...;<field_n><operator_n><value_n> The following command needs to be invoked to request the meters of one VM instance: $ ceilometer meter-list --query resource=bb52e52b-1e42-4751-b3ac-45c52d83ba07 +-------------------------+------------+-----------+--------------------------------------+----------------------------------+----------------------------------+ | Name | Type | Unit | Resource ID | User ID | Project ID | +-------------------------+------------+-----------+--------------------------------------+----------------------------------+----------------------------------+ | cpu | cumulative | ns | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | cpu_util | gauge | % | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.ephemeral.size | gauge | GB | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.read.bytes | cumulative | B | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.read.bytes.rate | gauge | B/s | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.read.requests | cumulative | request | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.read.requests.rate | gauge | request/s | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.root.size | gauge | GB | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.write.bytes | cumulative | B | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.write.bytes.rate | gauge | B/s | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.write.requests | cumulative | request | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | disk.write.requests.rate| gauge | request/s | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | instance | gauge | instance | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | instance:m1.tiny | gauge | instance | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | memory | gauge | MB | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | | vcpus | gauge | vcpu | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | b6e62aad26174382bc3781c12fe413c8 | cbfa8e3dfab64a27a87c8e24ecd5c60f | +-------------------------+------------+-----------+--------------------------------------+----------------------------------+----------------------------------+ As it was described above, the whole set of samples can be retrieved that are stored for a meter or filtering the result set by using one of the available query types. The request for all the samples of the cpu meter without any additional filtering looks like the following: $ ceilometer sample-list --meter cpu +--------------------------------------+-------+------------+------------+------+---------------------+ | Resource ID | Meter | Type | Volume | Unit | Timestamp | +--------------------------------------+-------+------------+------------+------+---------------------+ | c8d2e153-a48f-4cec-9e93-86e7ac6d4b0b | cpu | cumulative | 5.4863e+11 | ns | 2014-08-31T11:17:03 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | cpu | cumulative | 5.7848e+11 | ns | 2014-08-31T11:17:03 | | c8d2e153-a48f-4cec-9e93-86e7ac6d4b0b | cpu | cumulative | 5.4811e+11 | ns | 2014-08-31T11:07:05 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | cpu | cumulative | 5.7797e+11 | ns | 2014-08-31T11:07:05 | | c8d2e153-a48f-4cec-9e93-86e7ac6d4b0b | cpu | cumulative | 5.3589e+11 | ns | 2014-08-31T10:27:19 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | cpu | cumulative | 5.6397e+11 | ns | 2014-08-31T10:27:19 | | ... | +--------------------------------------+-------+------------+------------+------+---------------------+ The result set of the request contains the samples for both instances ordered by the timestamp field in the default descending order. The simple query makes it possible to retrieve only a subset of the collected samples. The following command can be executed to request the cpu samples of only one of the VM instances: $ ceilometer sample-list --meter cpu --query resource=bb52e52b-1e42-4751-b3ac-45c52d83ba07 +--------------------------------------+------+------------+------------+------+---------------------+ | Resource ID | Name | Type | Volume | Unit | Timestamp | +--------------------------------------+------+------------+------------+------+---------------------+ | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | cpu | cumulative | 5.7906e+11 | ns | 2014-08-31T11:27:08 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | cpu | cumulative | 5.7848e+11 | ns | 2014-08-31T11:17:03 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | cpu | cumulative | 5.7797e+11 | ns | 2014-08-31T11:07:05 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | cpu | cumulative | 5.6397e+11 | ns | 2014-08-31T10:27:19 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | cpu | cumulative | 5.6207e+11 | ns | 2014-08-31T10:17:03 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | cpu | cumulative | 5.3831e+11 | ns | 2014-08-31T08:41:57 | | ... | +--------------------------------------+------+------------+------------+------+---------------------+ As it can be seen on the output above, the result set contains samples for only one instance of the two. The ceilometer query-samples command is used to execute rich queries. This command accepts the following parameters: --filter Contains the filter expression for the query in the form of: {complex_op: [{simple_op: {field_name: value}}]}. --orderby Contains the list of orderby expressions in the form of: [{field_name: direction}, {field_name: direction}]. --limit Specifies the maximum number of samples to return. For more information about complex queries see . As the complex query functionality provides the possibility of using complex operators, it is possible to retrieve a subset of samples for a given VM instance. To request for the first six samples for the cpu and disk.read.bytes meters, the following command should be invoked: $ ceilometer query-samples --filter '{"and": \ [{"=":{"resource":"bb52e52b-1e42-4751-b3ac-45c52d83ba07"}},{"or":[{"=":{"counter_name":"cpu"}}, \ {"=":{"counter_name":"disk.read.bytes"}}]}]}' --orderby '[{"timestamp":"asc"}]' --limit 6 +--------------------------------------+-----------------+------------+------------+------+---------------------+ | Resource ID | Meter | Type | Volume | Unit | Timestamp | +--------------------------------------+-----------------+------------+------------+------+---------------------+ | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | disk.read.bytes | cumulative | 385334.0 | B | 2014-08-30T13:00:46 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | cpu | cumulative | 1.2132e+11 | ns | 2014-08-30T13:00:47 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | cpu | cumulative | 1.4295e+11 | ns | 2014-08-30T13:10:51 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | disk.read.bytes | cumulative | 601438.0 | B | 2014-08-30T13:10:51 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | disk.read.bytes | cumulative | 601438.0 | B | 2014-08-30T13:20:33 | | bb52e52b-1e42-4751-b3ac-45c52d83ba07 | cpu | cumulative | 1.4795e+11 | ns | 2014-08-30T13:20:34 | +--------------------------------------+-----------------+------------+------------+------+---------------------+ The command line client library provides python bindings in order to use the Telemetry Python API directly from python programs. The first step in setting up the client is to create a client instance with the proper credentials: >>> import ceilometerclient.client >>> cclient = ceilometerclient.client.get_client(VERSION, username=USERNAME, password=PASSWORD, tenant_name=PROJECT_NAME, auth_url=AUTH_URL) The VERSION parameter can be 1 or 2, specifying the API version to be used. The method calls look like the following: >>> cclient.meters.list() [<Meter ...>, ...] >>> cclient.samples.list() [<Sample ...>, ...] For further details about the python-ceilometerclient package, see the Python bindings to the OpenStack Ceilometer API reference.

The Telemetry module provides several transport methods to forward the data collected to the ceilometer-collector service or to an external system. The consumers of this data are widely different, like monitoring systems, for which data loss is acceptable and billing systems, which require reliable data transportation. Telemetry provides methods to fulfill the requirements of both kind of systems, as it is described below. The publisher component makes it possible to persist the data into storage through the message bus or to send it to one or more external consumers. One chain can contain multiple publishers. To solve the above mentioned problem, the notion of multi-publisher can be configured for each datapoint within the Telemetry module, allowing the same technical meter or event to be published multiple times to multiple destinations, each potentially using a different transport. Publishers can be specified in the publishers section for each pipeline (for further details about pipelines see ) that is defined in the file called pipeline.yaml. The following publisher types are supported: notifier It can be specified in the form of notifier://?option1=value1&option2=value2. It emits data over AMQP using oslo.messaging. This is the recommended method of publishing. rpc It can be specified in the form of rpc://?option1=value1&option2=value2. It emits metering data over lossy AMQP. This method is synchronous and may experience performance issues. udp It can be specified in the form of udp://<host>:<port>/. It emits metering data for over UDP. file It can be specified in the form of file://path?option1=value1&option2=value2. This publisher records metering data into a file. If a file name and location is not specified, this publisher does not log any meters, instead it logs a warning message in the configured log file for Telemetry. kafka It can be specified in the form of kafka://kafka_broker_ip: kafka_broker_port?topic=kafka_topic &option1=value1. This publisher sends metering data to a kafka broker. If the topic parameter is missing, this publisher brings out metering data under a topic name, ceilometer. When the port number is not specified, this publisher uses 9092 as the broker's port. The following options are available for rpc and notifier. The policy option can be used by kafka publisher: per_meter_topic The value of it is 1. It is used for publishing the samples on additional metering_topic.sample_name topic queue besides the default metering_topic queue. policy It is used for configuring the behavior for the case, when the publisher fails to send the samples, where the possible predefined values are the following: default Used for waiting and blocking until the samples have been sent. drop Used for dropping the samples which are failed to be sent. queue Used for creating an in-memory queue and retrying to send the samples on the queue on the next samples publishing period (the queue length can be configured with max_queue_length, where 1024 is the default value). The following options are available for the file publisher: max_bytes When this option is greater than zero, it will cause a rollover. When the size is about to be exceeded, the file is closed and a new file is silently opened for output. If its value is zero, rollover never occurs. backup_count If this value is non-zero, an extension will be appended to the filename of the old log, as '.1', '.2', and so forth until the specified value is reached. The file that is written and contains the newest data is always the one that is specified without any extensions. The default publisher is notifier, without any additional options specified. A sample publishers section in the /etc/ceilometer/pipeline.yaml looks like the following: publishers: - udp://10.0.0.2:1234 - rpc://?per_meter_topic=1 - notifier://?policy=drop&max_queue_length=512