============
 V2 Web API
============

Resources
=========

.. rest-controller:: ceilometer.api.controllers.v2.resources:ResourcesController
   :webprefix: /v2/resources

.. autotype:: ceilometer.api.controllers.v2.resources.Resource
   :members:

Meters
======

.. rest-controller:: ceilometer.api.controllers.v2.meters:MetersController
   :webprefix: /v2/meters

.. rest-controller:: ceilometer.api.controllers.v2.meters:MeterController
   :webprefix: /v2/meters

.. autotype:: ceilometer.api.controllers.v2.meters.Meter
   :members:

.. autotype:: ceilometer.api.controllers.v2.meters.OldSample
   :members:

Samples and Statistics
======================

.. rest-controller:: ceilometer.api.controllers.v2.samples:SamplesController
   :webprefix: /v2/samples

.. autotype:: ceilometer.api.controllers.v2.samples.Sample
   :members:

.. autotype:: ceilometer.api.controllers.v2.meters.Statistics
   :members:

When a simple statistics request is invoked (using GET /v2/meters/<meter_name>/statistics),
it will return the standard set of *Statistics*: *avg*, *sum*, *min*, *max*, and *count*.

.. note::

   If using Ceilometer data for statistics, it's recommended to use a backend
   such as Gnocchi_ rather than Ceilometer's interface. Gnocchi is designed
   specifically for this use case by providing a light-weight, aggregated model.
   As they manage data differently, the API models returned by Ceilometer and Gnocchi
   are different. The Gnocchi API can be found here_.

.. _Gnocchi: http://docs.openstack.org/developer/gnocchi/
.. _here: http://docs.openstack.org/developer/gnocchi/rest.html

Selectable Aggregates
+++++++++++++++++++++

The Statistics API has been extended to include the aggregate functions
*stddev* and *cardinality*. You can explicitly select these functions or any
from the standard set by specifying an aggregate function in the statistics
query::

    GET /v2/meters/<meter_name>/statistics?aggregate.func=<name>&aggregate.param=<value>

(where aggregate.param is optional).

Duplicate aggregate function and parameter pairs are silently discarded from the statistics query. Partial duplicates, in the sense of the same function but differing parameters, for example::

    GET /v2/meters/<meter_name>/statistics?aggregate.func=cardinality&aggregate.param=resource_id&aggregate.func=cardinality&aggregate.param=project_id

are, on the other hand, both allowed by the API and supported by the storage drivers.  See the :ref:`functional-examples` section for more detail.

.. note::

   Currently only *cardinality* needs aggregate.param to be specified.

.. autotype:: ceilometer.api.controllers.v2.meters.Aggregate
   :members:

Capabilities
============

The Capabilities API allows you to directly discover which functions from the
V2 API functionality, including the selectable aggregate functions, are
supported by the currently configured storage driver. A capabilities query
returns a flattened dictionary of properties with associated boolean values -
a 'False' or absent value means that the corresponding feature is not
available in the backend.

.. rest-controller:: ceilometer.api.controllers.v2.capabilities:CapabilitiesController
   :webprefix: /v2/capabilities

.. autotype:: ceilometer.api.controllers.v2.capabilities.Capabilities
   :members:

Events and Traits
=================

.. rest-controller:: ceilometer.api.controllers.v2.events:EventTypesController
   :webprefix: /v2/event_types

.. rest-controller:: ceilometer.api.controllers.v2.events:TraitsController
   :webprefix: /v2/event_types/(event_type)/traits

.. rest-controller:: ceilometer.api.controllers.v2.events:EventsController
   :webprefix: /v2/events

.. autotype:: ceilometer.api.controllers.v2.events.Event
   :members:

.. autotype:: ceilometer.api.controllers.v2.events.Trait
   :members:

.. autotype:: ceilometer.api.controllers.v2.events.TraitDescription
   :members:

Filtering Queries
=================

Ceilometer's REST API currently supports two types of queries. The Simple
Query functionality provides simple filtering on several fields of the
*Sample* type. Complex Query provides the possibility to specify queries
with logical and comparison operators on the fields of *Sample*.

You may also apply filters based on the values of one or more of the
*resource_metadata* field, which you can identify by using *metadata.<field>*
syntax in either type of query. Note, however, that given the free-form
nature of *resource_metadata* field, there is no practical or consistent way
to validate the query fields under *metadata* domain like it is done for
all other fields.

.. note::

   The API call will return HTTP 200 OK status for both of the
   following cases: when a query with *metadata.<field>* does not match its
   value, and when *<field>* itself does not exist in any of the records being
   queried.

Simple Query
++++++++++++

Many of the endpoints above accept a query filter argument, which
should be a list of Query data structures. Whatever the endpoint you
want to apply a filter on, you always filter on the fields of the *Sample*
type (for example, if you apply a filter on a query for statistics,
you won't target *duration_start* field of *Statistics*, but *timestamp*
field of *Sample*). See :ref:`api-queries` for how to query the API.

.. autotype:: ceilometer.api.controllers.v2.base.Query
   :members:

Event Query
+++++++++++

Event query is similar to simple query, its type EventQuery is actually
a subclass of Query, so EventQuery has every attribute Query has.
But there are some differences. If a field is one of the following:
event_type, message_id, start_timestamp, end_timestamp, then this field
will be applied on event, otherwise it will be treated as trait name and
applied on trait. See :ref:`api-queries` for how to query the API.

.. autotype:: ceilometer.api.controllers.v2.events.EventQuery
   :members:

Complex Query
+++++++++++++

The filter expressions of the Complex Query feature operate on the fields
of *Sample*. The following comparison operators are
supported: *=*, *!=*, *<*, *<=*, *>*, *>=* and *in*; and the following logical
operators can be used: *and* *or* and *not*. The field names are validated
against the database models. See :ref:`api-queries` for how to query the API.

.. note::

   The *not* operator has different meaning in MongoDB and in SQL DB engine.
   If the *not* operator is applied on a non existent metadata field then
   the result depends on the DB engine. For example, if
   {"not": {"metadata.nonexistent_field" : "some value"}} filter is used in a query
   the MongoDB will return every Sample object as *not* operator evaluated true
   for every Sample where the given field does not exists. See more in the MongoDB doc.
   On the other hand, SQL based DB engine will return empty result as the join operation
   on the metadata table will return zero rows as the on clause of the join which
   tries to match on the metadata field name is never fulfilled.

Complex Query supports defining the list of orderby expressions in the form
of [{"field_name": "asc"}, {"field_name2": "desc"}, ...].

The number of the returned items can be bounded using the *limit* option.

The *filter*, *orderby* and *limit* are all optional fields in a query.

.. rest-controller:: ceilometer.api.controllers.v2.query:QuerySamplesController
   :webprefix: /v2/query/samples

.. autotype:: ceilometer.api.controllers.v2.query.ComplexQuery
   :members:

Links
=====

.. autotype:: ceilometer.api.controllers.v2.base.Link
   :members:

API and CLI query examples
==========================

CLI Queries
+++++++++++

Ceilometer CLI Commands::

     $ ceilometer --debug --os-username <username_here> --os-password <password_here> --os-auth-url http://localhost:5000/v2.0/ --os-tenant-name admin  meter-list

.. note::

   The *username*, *password*, and *tenant-name* options are required to be
   present in these arguments or specified via environment variables. Note that
   the in-line arguments will override the environment variables.

.. _api-queries:

API Queries
+++++++++++

Ceilometer API calls:

.. note::

   To successfully query Ceilometer you must first get a project-specific
   token from the Keystone service and add it to any API calls that you
   execute against that project. See the
   `OpenStack credentials documentation <http://docs.openstack.org/api/quick-start/content/index.html#getting-credentials-a00665>`_
    for additional details.

A simple query to return a list of available meters::

     curl -H 'X-Auth-Token: <inserttokenhere>' \
       "http://localhost:8777/v2/meters"

A query to return the list of resources::

     curl -H 'X-Auth-Token: <inserttokenhere>' \
       "http://localhost:8777/v2/resources"

A query to return the list of samples, limited to a specific meter type::

     curl -H 'X-Auth-Token: <inserttokenhere>' \
       "http://localhost:8777/v2/meters/disk.root.size"

A query using filters (see: `query filter section <http://docs.openstack.org/developer/ceilometer/webapi/v2.html#filtering-queries>`_)::

     curl -H 'X-Auth-Token: <inserttokenhere>' \
       "http://localhost:8777/v2/meters/instance?q.field=metadata.event_type&q.value=compute.instance.delete.start"

Additional examples::

     curl -H 'X-Auth-Token: <inserttokenhere>' \
       "http://localhost:8777/v2/meters/disk.root.size?q.field=resource_id&q.op=eq&q.value=<resource_id_here>"

or::

     curl -H 'X-Auth-Token: <inserttokenhere>' \
       "http://localhost:8777/v2/meters/instance?q.field=metadata.event_type&q.value=compute.instance.exists"

You can specify multiple filters by using an array of queries (order matters)::

     curl -H 'X-Auth-Token: <inserttokenhere>' \
       "http://localhost:8777/v2/meters/instance"\
       "?q.field=metadata.event_type&q.value=compute.instance.exists"\
       "&q.field=timestamp&q.op=gt&q.value=2013-07-03T13:34:17"

A query to find the maximum value and standard deviation (*max*, *stddev*) of
the CPU utilization for a given instance (identified by *resource_id*)::

     curl -H 'X-Auth-Token: <inserttokenhere>' \
       "http://localhost:8777/v2/meters/cpu_util/statistics?aggregate.func=max&aggregate.func=stddev"\
       "&q.field=resource_id&q.op=eq&q.value=64da755c-9120-4236-bee1-54acafe24980"

.. note::

   If any of the requested aggregates are not supported by the storage driver,
   a HTTP 400 error code will be returned along with an appropriate error
   message.

JSON based example::

     curl -X GET -H "X-Auth-Token: <inserttokenhere>" -H "Content-Type: application/json"
     -d '{"q": [{"field": "timestamp", "op": "ge", "value": "2014-04-01T13:34:17"}]}'
       http://localhost:8777/v2/meters/instance

JSON based example with multiple filters::

     curl -X GET -H "X-Auth-Token: <inserttokenhere>" -H "Content-Type: application/json"
      -d '{"q": [{"field": "timestamp", "op": "ge", "value": "2014-04-01T13:34:17"},
        {"field": "resource_id", "op": "eq", "value": "4da2b992-0dc3-4a7c-a19a-d54bf918de41"}]}'
        http://localhost:8777/v2/meters/instance

.. _functional-examples:

Functional examples
+++++++++++++++++++

The examples below are meant to help you understand how to query the
Ceilometer API to build custom meters report. The query parameters should
be encoded using one of the above methods, e.g. as the URL parameters or
as JSON encoded data passed to the GET request.

Get the list of samples about instances running for June 2013::

     GET /v2/meters/instance
     q: [{"field": "timestamp",
          "op": "ge",
          "value": "2013-06-01T00:00:00"},
         {"field": "timestamp",
          "op": "lt",
           "value": "2013-07-01T00:00:00"}]


Get the list of samples about instances running for June 2013 for a particular
project::

    GET /v2/meters/instance
    q: [{"field": "timestamp",
         "op": "ge",
         "value": "2013-06-01T00:00:00"},
        {"field": "timestamp",
         "op": "lt",
         "value": "2013-07-01T00:00:00"},
        {"field": "project_id",
         "op": "eq",
         "value": "8d6057bc-5b90-4296-afe0-84acaa2ef909"}]

Now you may want to have statistics on the meters you are targeting.
Consider the following example where you are getting the list of samples
about CPU utilization of a given instance (identified by its *resource_id*)
running for June 2013::

    GET /v2/meters/cpu_util
    q: [{"field": "timestamp",
         "op": "ge",
         "value": "2013-06-01T00:00:00"},
        {"field": "timestamp",
         "op": "lt",
         "value": "2013-07-01T00:00:00"},
        {"field": "resource_id",
         "op": "eq",
         "value": "64da755c-9120-4236-bee1-54acafe24980"}]

You can have statistics on the list of samples requested (*avg*, *sum*, *max*,
*min*, *count*) computed on the full duration::

    GET /v2/meters/cpu_util/statistics
    q: [{"field": "timestamp",
         "op": "ge",
         "value": "2013-06-01T00:00:00"},
        {"field": "timestamp",
         "op": "lt",
         "value": "2013-07-01T00:00:00"},
        {"field": "resource_id",
         "op": "eq",
         "value": "64da755c-9120-4236-bee1-54acafe24980"}]

You may want to aggregate samples over a given period (10 minutes for
example) in order to get an array of the statistics computed on smaller
durations::

    GET /v2/meters/cpu_util/statistics
    q: [{"field": "timestamp",
         "op": "ge",
         "value": "2013-06-01T00:00:00"},
        {"field": "timestamp",
         "op": "lt",
         "value": "2013-07-01T00:00:00"},
        {"field": "resource_id",
         "op": "eq",
         "value": "64da755c-9120-4236-bee1-54acafe24980"}]
    period: 600

The *period* parameter aggregates by time range. You can also aggregate by
field using the *groupby* parameter. Currently, the *user_id*, *resource_id*,
*project_id*, and *source* fields are supported. Below is an example that uses
a query filter and group by aggregation on *project_id* and *resource_id*::

    GET /v2/meters/instance/statistics
    q: [{"field": "user_id",
        "op": "eq",
        "value": "user-2"},
        {"field": "source",
         "op": "eq",
         "value": "source-1"}]
    groupby: ["project_id", "resource_id"]

The statistics will be returned in a list, and each entry of the list will be
labeled with the group name. For the previous example, the first entry might
have *project_id* be "project-1" and *resource_id* be "resource-1", the second
entry have *project_id* be "project-1" and *resource_id* be "resource-2", and
so on.

You can request both period and group by aggregation in the same query::

    GET /v2/meters/instance/statistics
    q: [{"field": "source",
        "op": "eq",
        "value": "source-1"}]
    groupby: ["project_id"]
    period: 7200

Note that period aggregation is applied first, followed by group by
aggregation. Order matters because the period aggregation determines the time
ranges for the statistics.

Below is a real-life query::

    GET /v2/meters/image/statistics
    groupby: ["project_id", "resource_id"]

With the return values::

    [{"count": 4, "duration_start": "2013-09-18T19:08:33", "min": 1.0,
      "max": 1.0, "duration_end": "2013-09-18T19:27:30", "period": 0,
      "sum": 4.0, "period_end": "2013-09-18T19:27:30", "duration": 1137.0,
      "period_start": "2013-09-18T19:08:33", "avg": 1.0,
      "groupby": {"project_id": "c2334f175d8b4cb8b1db49d83cecde78",
                  "resource_id": "551f495f-7f49-4624-a34c-c422f2c5f90b"},
      "unit": "image"},
     {"count": 4, "duration_start": "2013-09-18T19:08:36", "min": 1.0,
      "max": 1.0, "duration_end": "2013-09-18T19:27:30", "period": 0,
      "sum": 4.0, "period_end": "2013-09-18T19:27:30", "duration": 1134.0,
      "period_start": "2013-09-18T19:08:36", "avg": 1.0,
      "groupby": {"project_id": "c2334f175d8b4cb8b1db49d83cecde78",
                  "resource_id": "7c1157ed-cf30-48af-a868-6c7c3ad7b531"},
      "unit": "image"},
     {"count": 4, "duration_start": "2013-09-18T19:08:34", "min": 1.0,
      "max": 1.0, "duration_end": "2013-09-18T19:27:30", "period": 0,
      "sum": 4.0, "period_end": "2013-09-18T19:27:30", "duration": 1136.0,
      "period_start": "2013-09-18T19:08:34", "avg": 1.0,
      "groupby": {"project_id": "c2334f175d8b4cb8b1db49d83cecde78",
                  "resource_id": "eaed9cf4-fc99-4115-93ae-4a5c37a1a7d7"},
      "unit": "image"}]

You can request specific aggregate functions as well. For example, if you only
want the average CPU utilization, the GET request would look like this::

    GET /v2/meters/cpu_util/statistics?aggregate.func=avg

Use the same syntax to access the aggregate functions not in the standard set,
e.g. *stddev* and *cardinality*. A request for the standard deviation of CPU utilization would take the form::

    GET /v2/meters/cpu_util/statistics?aggregate.func=stddev

And would give a response such as the example::

    [{"aggregate": {"stddev":0.6858829535841072},
      "duration_start": "2014-01-30T11:13:23",
      "duration_end": "2014-01-31T16:07:13",
      "duration": 104030.0,
      "period": 0,
      "period_start": "2014-01-30T11:13:23",
      "period_end": "2014-01-31T16:07:13",
      "groupby": null,
      "unit" : "%"}]

The request syntax is similar for *cardinality* but with the aggregate.param
option provided. So, for example, if you want to know the number of distinct
tenants with images, you would do::

     GET /v2/meters/image/statistics?aggregate.func=cardinality
                                       &aggregate.param=project_id

For a more involved example, consider a requirement for determining, for some
tenant, the number of distinct instances (*cardinality*) as well as the total
number of instance samples (*count*). You might also want to see this
information with 15 minute long intervals. Then, using the *period* and
*groupby* options, a query would look like the following::

    GET /v2/meters/instance/statistics?aggregate.func=cardinality
                                      &aggregate.param=resource_id
                                      &aggregate.func=count
                                      &groupby=project_id&period=900

This would give an example response of the form::

    [{"count": 19,
      "aggregate": {"count": 19.0, "cardinality/resource_id": 3.0},
      "duration": 328.478029,
      "duration_start": "2014-01-31T10:00:41.823919",
      "duration_end": "2014-01-31T10:06:10.301948",
      "period": 900,
      "period_start": "2014-01-31T10:00:00",
      "period_end": "2014-01-31T10:15:00",
      "groupby": {"project_id": "061a5c91811e4044b7dc86c6136c4f99"},
      "unit": "instance"},
     {"count": 22,
      "aggregate": {"count": 22.0, "cardinality/resource_id": 4.0},
      "duration": 808.00384,
      "duration_start": "2014-01-31T10:15:15",
      "duration_end": "2014-01-31T10:28:43.003840",
      "period": 900,
      "period_start": "2014-01-31T10:15:00",
      "period_end": "2014-01-31T10:30:00",
      "groupby": {"project_id": "061a5c91811e4044b7dc86c6136c4f99"},
      "unit": "instance"},
     {"count": 2,
      "aggregate": {"count": 2.0, "cardinality/resource_id": 2.0},
      "duration": 0.0,
      "duration_start": "2014-01-31T10:35:15",
      "duration_end": "2014-01-31T10:35:15",
      "period": 900,
      "period_start": "2014-01-31T10:30:00",
      "period_end": "2014-01-31T10:45:00",
      "groupby": {"project_id": "061a5c91811e4044b7dc86c6136c4f99"},
      "unit": "instance"}]

If you want to retrieve all the instances (not the list of samples, but the
resource itself) that have been run during this month for a given project,
you should ask the resource endpoint for the list of resources (all types:
including storage, images, networking, ...)::

    GET /v2/resources
    q: [{"field": "timestamp",
         "op": "ge",
         "value": "2013-06-01T00:00:00"},
        {"field": "timestamp",
         "op": "lt",
         "value": "2013-07-01T00:00:00"},
        {"field": "project_id",
         "op": "eq",
         "value": "8d6057bc-5b90-4296-afe0-84acaa2ef909"}]

Then look for resources that have an *instance* meter linked to them. That
will indicate resources that have been measured as being instance. You can
then request their samples to have more detailed information, like their
state or their flavor::

    GET /v2/meter/instance
    q: [{"field": "timestamp",
         "op": "ge",
         "value": "2013-06-01T00:00:00"},
        {"field": "timestamp",
         "op": "lt",
         "value": "2013-07-01T00:00:00"},
        {"field": "resource_id",
         "op": "eq",
         "value": "64da755c-9120-4236-bee1-54acafe24980"},
        {"field": "project_id",
         "op": "eq",
         "value": "8d6057bc-5b90-4296-afe0-84acaa2ef909"}]

This will return a list of samples that have been recorded on this
particular resource. You can inspect them to retrieve information, such as
the instance state (check the *metadata.vm_state* field) or the instance
flavor (check the *metadata.flavor* field).
You can request nested metadata fields by using a dot to delimit the fields
(e.g. *metadata.weighted_host.host* for *instance.scheduled* meter)

To retrieve only the 3 last samples of a meters, you can pass the *limit*
parameter to the query::

    GET /v2/meter/instance
    q: [{"field": "timestamp",
         "op": "ge",
         "value": "2013-06-01T00:00:00"},
        {"field": "timestamp",
         "op": "lt",
         "value": "2013-07-01T00:00:00"},
        {"field": "resource_id",
         "op": "eq",
         "value": "64da755c-9120-4236-bee1-54acafe24980"},
        {"field": "project_id",
         "op": "eq",
         "value": "8d6057bc-5b90-4296-afe0-84acaa2ef909"}]
    limit: 3

This query would only return the last 3 samples.

Functional example for Complex Query
++++++++++++++++++++++++++++++++++++

This example demonstrates how complex query filter expressions can be generated and sent
to the /v2/query/samples endpoint of Ceilometer API using POST request.

To check for *cpu_util* samples reported between 18:00-18:15 or between 18:30 - 18:45
on a particular date (2013-12-01), where the utilization is between 23 and 26 percent,
but not exactly 25.12 percent, the following filter expression can be created::

    {"and":
     [{"and":
      [{"=": {"counter_name": "cpu_util"}},
       {">": {"counter_volume": 0.23}},
       {"<": {"counter_volume": 0.26}},
       {"not": {"=": {"counter_volume": 0.2512}}}]},
      {"or":
       [{"and":
        [{">": {"timestamp": "2013-12-01T18:00:00"}},
         {"<": {"timestamp": "2013-12-01T18:15:00"}}]},
        {"and":
         [{">": {"timestamp": "2013-12-01T18:30:00"}},
          {"<": {"timestamp": "2013-12-01T18:45:00"}}]}]}]}

Different sorting criteria can be defined for the query filter, for example the results
can be ordered in an ascending order by the *counter_volume* and descending order based on
the *timestamp*. The following order by expression has to be created for specifying this
criteria::

    [{"counter_volume": "ASC"}, {"timestamp": "DESC"}]

As the current implementation accepts only string values as query filter and order by
definitions, the above defined expressions have to be converted to string values.
By adding a limit criteria to the request, which maximizes the number of returned samples
to four, the query looks like the following::

    {
    "filter" : "{\"and\":[{\"and\": [{\"=\": {\"counter_name\": \"cpu_util\"}}, {\">\": {\"counter_volume\": 0.23}}, {\"<\": {\"counter_volume\": 0.26}}, {\"not\": {\"=\": {\"counter_volume\": 0.2512}}}]}, {\"or\": [{\"and\": [{\">\": {\"timestamp\": \"2013-12-01T18:00:00\"}}, {\"<\": {\"timestamp\": \"2013-12-01T18:15:00\"}}]}, {\"and\": [{\">\": {\"timestamp\": \"2013-12-01T18:30:00\"}}, {\"<\": {\"timestamp\": \"2013-12-01T18:45:00\"}}]}]}]}",
    "orderby" : "[{\"counter_volume\": \"ASC\"}, {\"timestamp\": \"DESC\"}]",
    "limit" : 4
    }

A query request looks like the following with curl::

    curl -X POST -H 'X-Auth-Token: <inserttokenhere>' -H 'Content-Type: application/json' \
      -d '<insertyourqueryexpressionhere>' \
       http://localhost:8777/v2/query/samples

.. _user-defined-data:

User-defined data
+++++++++++++++++

It is possible to add your own samples (created from data retrieved in any
way like monitoring agents on your instances) in Ceilometer to store
them and query on them. You can even get *Statistics* on your own inserted data.
By adding a *Sample* to a *Resource*, you create automatically the corresponding
*Meter* if it does not exist already. To achieve this, you have to POST a list
of one to many samples in JSON format::

    curl -X POST -H 'X-Auth-Token: <inserttokenhere>' -H 'Content-Type: application/json' \
      -d '<insertyoursampleslisthere>' \
      http://localhost:8777/v2/meters/<insertyourmeternamehere>

Fields *source*, *timestamp*, *project_id* and *user_id* are automatically
added if not present in the samples. Field *message_id* is not taken into
account if present and an internal value will be set.

By default, samples posted via API will be placed on the notification bus and
processed by the notification agent.

To avoid re-queuing the data, samples posted via API can be stored directly to
the storage backend verbatim by specifying a boolean flag 'direct' in the
request URL, like this::

    POST /v2/meters/ram_util?direct=True

Samples posted this way will bypass pipeline processing.

Here is an example showing how to add a sample for a *ram_util* meter (already
existing or not)::

    POST /v2/meters/ram_util
    body: [
            {
              "counter_name": "ram_util",
              "user_id": "4790fbafad2e44dab37b1d7bfc36299b",
              "resource_id": "87acaca4-ae45-43ae-ac91-846d8d96a89b",
              "resource_metadata": {
                "display_name": "my_instance",
                "my_custom_metadata_1": "value1",
                "my_custom_metadata_2": "value2"
               },
              "counter_unit": "%",
              "counter_volume": 8.57762938230384,
              "project_id": "97f9a6aaa9d842fcab73797d3abb2f53",
              "counter_type": "gauge"
            }
          ]

You get back the same list containing your example completed with the missing
fields : *source* and *timestamp* in this case.
