Benchmarking an existing cluster


If you are just getting started with Rally and don’t understand how it works, please do NOT run it against any production or production-like cluster. Besides, benchmarks should be executed in a dedicated environment anyway where no additional traffic skews results.


We assume in this recipe, that Rally is already properly configured.

Consider the following configuration: You have an existing benchmarking cluster, that consists of three Elasticsearch nodes running on,, You’ve setup the cluster yourself and want to benchmark it with Rally. Rally is installed on

Sample Benchmarking Scenario

First of all, we need to decide on a track. So, we run esrally list tracks:

Name        Description                                                                   Documents  Compressed Size    Uncompressed Size    Default Challenge        All Challenges
----------  --------------------------------------------------------------------------  -----------  -----------------  -------------------  -----------------------  --------------------------
geonames    Standard track in Rally (11.4M POIs from Geonames)                             11396505  252.4 MB           3.3 GB               append-no-conflicts      append-no-conflicts,app...
geopoint    60.8M POIs from PlanetOSM                                                      60844404  481.9 MB           2.3 GB               append-no-conflicts      append-no-conflicts,app...
logging     Logging benchmark                                                             247249096  1.2 GB             31.1 GB              append-no-conflicts      append-no-conflicts,app...
nested      Nested query benchmark using up to 11,203,029 questions from StackOverflow     11203029  663.1 MB           3.4 GB               nested-search-challenge  nested-search-challenge...
nyc_taxis   Trip records completed in yellow and green taxis in New York in 2015          165346692  4.5 GB             74.3 GB              append-no-conflicts      append-no-conflicts,app...
percolator  Percolator benchmark based on 2M AOL queries                                    2000000  102.7 kB           104.9 MB             append-no-conflicts      append-no-conflicts,app...
pmc         Full text benchmark containing 574.199 papers from PMC                           574199  5.5 GB             21.7 GB              append-no-conflicts      append-no-conflicts,app...

We’re interested in a full text benchmark, so we’ll choose to run pmc. If you have your own data that you want to use for benchmarks, then please create your own track instead; the metrics you’ll gather which be representative and much more useful than some default track.

Next, we need to know which machines to target which is easy as we can see that from the diagram above.

Finally we need to check which pipeline to use. For this case, the benchmark-only pipeline is suitable as we don’t want Rally to provision the cluster for us.

Now we can invoke Rally:

esrally --track=pmc --target-hosts=,, --pipeline=benchmark-only

If you have X-Pack Security enabled, then you’ll also need to specify another parameter to use https and to pass credentials:

esrally --track=pmc --target-hosts=,, --pipeline=benchmark-only --client-options="basic_auth_user:'elastic',basic_auth_password:'changeme'"

Benchmarking a remote cluster

Contrary to the previous recipe, you want Rally to provision all cluster nodes.


At the moment, Rally can only provision a single remote node but support for provisioning of multi-node clusters is a high priority topic on our roadmap.

We will use the following configuration for the example:

  • You will start Rally on We will call this machine the “benchmark coordinator”.
  • Your Elasticsearch cluster will run on We will call this machine the “benchmark candidate”.
Sample Benchmarking Scenario

To run a benchmark for this scenario follow these steps:

  1. Install and configure Rally on all machines. Be sure that the same version is installed on all of them.
  2. Start the Rally daemon on each machine. The Rally daemon allows Rally to communicate with all remote machines. On the benchmark coordinator run esrallyd start --node-ip= --coordinator-ip= and on the benchmark candidate run esrallyd start --node-ip= --coordinator-ip= The --node-ip parameter tells Rally the IP of the machine on which it is running. As some machines have more than one network interface, Rally will not attempt to auto-detect the machine IP. The --coordinator-ip parameter tells Rally the IP of the benchmark coordinator node.
  3. Start the benchmark by invoking Rally as usual on the benchmark coordinator, for example: esrally --distribution-version=5.0.0 --target-hosts= Rally will derive from the --target-hosts parameter that it should provision the node
  4. After the benchmark has finished you can stop the Rally daemon again. On the benchmark coordinator and on the benchmark candidate run esrallyd stop.


Logs are managed per machine, so all relevant log files and also telemetry output is stored on the benchmark candidate but not on the benchmark coordinator.

Now you might ask yourself what the differences to benchmarks of existing clusters are. In general you should aim to give Rally as much control as possible as benchmark are easier reproducible and you get more metrics. The following table provides some guidance on when to choose which option:

Your requirement Recommendation
You want to use Rally’s telemetry devices Use Rally daemon, as it can provision the remote node for you
You want to benchmark a source build of Elasticsearch Use Rally daemon, as it can build Elasticsearch for you
You want to tweak the cluster configuration yourself Set up the cluster by yourself and use --pipeline=benchmark-only
You need to run a benchmark with plugins Set up the cluster by yourself and use --pipeline=benchmark-only
You need to run a benchmark against multiple nodes Set up the cluster by yourself and use --pipeline=benchmark-only

Rally daemon will be able to cover most of the cases described above in the future so there should be almost no case where you need to use the benchmark-only pipeline.

Changing the default track repository

Rally supports multiple track repositories. This allows you for example to have a separate company-internal repository for your own tracks that is separate from Rally’s default track repository. However, you always need to define --track-repository=my-custom-repository which can be cumbersome. If you want to avoid that and want Rally to use your own track repository by default you can just replace the default track repository definition in ~./rally/rally.ini. Consider this example:

default.url =
teamtrackrepo.url =

If teamtrackrepo should be the default track repository, just define it as default.url. E.g.:

default.url =

Also don’t forget to rename the folder of your local working copy as Rally will search for a track repository with the name default:

cd ~/.rally/benchmarks/tracks/
mv default old-rally-default
mv teamtrackrepo default

From now on, Rally will treat your repository as default and you need to run Rally with --track-repository=old-rally-default if you want to use the out-of-the-box Rally tracks.