path: root/docs/release/userguide/test-usage.rst

.. This work is licensed under a Creative Commons Attribution 4.0 International License.
.. http://creativecommons.org/licenses/by/4.0
.. (c) OPNFV, Dell EMC and others.

=============================
StorPerf Test Execution Guide
=============================

Prerequisites
=============

This guide requires StorPerf to be running and have its ReST API accessible.  If
the ReST API is not running on port 5000, adjust the commands provided here as
needed.

Interacting With StorPerf
=========================

Once the StorPerf container has been started and the ReST API exposed, you can
interact directly with it using the ReST API.  StorPerf comes with a Swagger
interface that is accessible through the exposed port at:

.. code-block:: console

   http://StorPerf:5000/swagger/index.html

The typical test execution follows this pattern:

#. Configure the environment
#. Initialize the cinder volumes
#. Execute one or more performance runs
#. Delete the environment

Configure The Environment
=========================

The following pieces of information are required to prepare the environment:

- The number of VMs/Cinder volumes to create
- The Glance image that holds the VM operating system to use.  StorPerf has
  only been tested with Ubuntu 16.04
- The name of the public network that agents will use
- The size, in gigabytes, of the Cinder volumes to create

The ReST API is a POST to http://StorPerf:5000/api/v1.0/configurations and
takes a JSON payload as follows.

.. code-block:: json

   {
     "agent_count": int,
     "agent_image": string,
     "public_network": string,
     "volume_size": int
   }

This call will block until the stack is created, at which point it will return
the OpenStack heat stack id.

Initialize the Cinder Volumes
=============================
Before executing a test run for the purpose of measuring performance, it is
necessary to fill the Cinder volume with random data.  Failure to execute this
step can result in meaningless numbers, especially for read performance.  Most
Cinder drivers are smart enough to know what blocks contain data, and which do
not.  Uninitialized blocks return "0" immediately without actually reading from
the volume.

Initiating the data fill looks the same as a regular performance test, but uses
the special workload called "_warm_up".  StorPerf will never push _warm_up
data to the OPNFV Test Results DB, nor will it terminate the run on steady state.
It is guaranteed to run to completion, which fills 100% of the volume with
random data.

The ReST API is a POST to http://StorPerf:5000/api/v1.0/jobs and
takes a JSON payload as follows.

.. code-block:: json

   {
      "workload": "_warm_up"
   }

This will return a job ID as follows.

.. code-block:: json

   {
     "job_id": "edafa97e-457e-4d3d-9db4-1d6c0fc03f98"
   }

This job ID can be used to query the state to determine when it has completed.
See the section on querying jobs for more information.

Execute a Performance Run
=========================
Performance runs can execute either a single workload, or iterate over a matrix
of workload types, block sizes and queue depths.

Workload Types
~~~~~~~~~~~~~~
rr
   Read, Random.  100% read of random blocks
rs
   Read, Sequential.  100% read of sequential blocks of data
rw
   Read / Write Mix, Random.  70% random read, 30% random write
wr
   Write, Random.  100% write of random blocks
ws
   Write, Sequential.  100% write of sequential blocks.

Block Sizes
~~~~~~~~~~~
A comma delimited list of the different block sizes to use when reading and
writing data.  Note: Some Cinder drivers (such as Ceph) cannot support block
sizes larger than 16k (16384).

Queue Depths
~~~~~~~~~~~~
A comma delimited list of the different queue depths to use when reading and
writing data.  The queue depth parameter causes FIO to keep this many I/O
requests outstanding at one time.  It is used to simulate traffic patterns
on the system.  For example, a queue depth of 4 would simulate 4 processes
constantly creating I/O requests.

Deadline
~~~~~~~~
The deadline is the maximum amount of time in minutes for a workload to run.  If
steady state has not been reached by the deadline, the workload will terminate
and that particular run will be marked as not having reached steady state.  Any
remaining workloads will continue to execute in order.

.. code-block:: json

   {
      "block_sizes": "2048,16384,
      "deadline": 20,
      "queue_depths": "2,4",
      "workload": "wr,rr,rw",
   }

Metadata
~~~~~~~~
A job can have metadata associated with it for tagging.  The following metadata
is required in order to push results to the OPNFV Test Results DB:

.. code-block:: json

      "metadata": {
          "disk_type": "HDD or SDD",
          "pod_name": "OPNFV Pod Name",
          "scenario_name": string,
          "storage_node_count": int,
          "version": string,
          "build_tag": string,
          "test_case": "snia_steady_state"
      }



Query Jobs Information
======================

By issuing a GET to the job API http://StorPerf:5000/api/v1.0/jobs?job_id=<ID>,
you can fetch information about the job as follows:

- &type=status: to report on the status of the job.
- &type=metrics: to report on the collected metrics.
- &type=metadata: to report back any metadata sent with the job ReST API

Status
~~~~~~
The Status field can be:
- Running to indicate the job is still in progress, or
- Completed to indicate the job is done.  This could be either normal completion
  or manually terminated via HTTP DELETE call.

Workloads can have a value of:
- Pending to indicate the workload has not yet started,
- Running to indicate this is the active workload, or
- Completed to indicate this workload has completed.

This is an example of a type=status call.

.. code-block:: json

   {
     "Status": "Running",
     "TestResultURL": null,
     "Workloads": {
       "eeb2e587-5274-4d2f-ad95-5c85102d055e.ws.queue-depth.1.block-size.16384": "Pending",
       "eeb2e587-5274-4d2f-ad95-5c85102d055e.ws.queue-depth.1.block-size.4096": "Pending",
       "eeb2e587-5274-4d2f-ad95-5c85102d055e.ws.queue-depth.1.block-size.512": "Pending",
       "eeb2e587-5274-4d2f-ad95-5c85102d055e.ws.queue-depth.4.block-size.16384": "Running",
       "eeb2e587-5274-4d2f-ad95-5c85102d055e.ws.queue-depth.4.block-size.4096": "Pending",
       "eeb2e587-5274-4d2f-ad95-5c85102d055e.ws.queue-depth.4.block-size.512": "Pending",
       "eeb2e587-5274-4d2f-ad95-5c85102d055e.ws.queue-depth.8.block-size.16384": "Completed",
       "eeb2e587-5274-4d2f-ad95-5c85102d055e.ws.queue-depth.8.block-size.4096": "Pending",
       "eeb2e587-5274-4d2f-ad95-5c85102d055e.ws.queue-depth.8.block-size.512": "Pending"
     }
   }

Metrics
~~~~~~~
Metrics can be queried at any time during or after the completion of a run.
Note that the metrics show up only after the first interval has passed, and
are subject to change until the job completes.

This is a sample of a type=metrics call.

.. code-block:: json

   {
     "rw.queue-depth.1.block-size.512.read.bw": 52.8,
     "rw.queue-depth.1.block-size.512.read.iops": 106.76199999999999,
     "rw.queue-depth.1.block-size.512.read.lat.mean": 93.176,
     "rw.queue-depth.1.block-size.512.write.bw": 22.5,
     "rw.queue-depth.1.block-size.512.write.iops": 45.760000000000005,
     "rw.queue-depth.1.block-size.512.write.lat.mean": 21764.184999999998
   }

Abort a Job
===========
Issuing an HTTP DELETE to the job api http://StorPerf:5000/api/v1.0/jobs will
force the termination of the whole job, regardless of how many workloads
remain to be executed.

.. code-block:: bash

  curl -X DELETE --header 'Accept: application/json' http://StorPerf:5000/api/v1.0/jobs

Delete the Environment
======================
After you are done testing, you can have StorPerf delete the Heat stack by
issuing an HTTP DELETE to the configurations API.

.. code-block:: bash

  curl -X DELETE --header 'Accept: application/json' http://StorPerf:5000/api/v1.0/configurations

You may also want to delete an environment, and then create a new one with a
different number of VMs/Cinder volumes to test the impact of the number of VMs
in your environment.