Pre-written workflows and activities useful for benchmarking Temporal.
This worker can be used alongside Maru or other benchmarking tools to mimic different workloads.
Also included is a simple workflow runner which will keep a configurable number of workflow executions running concurrently to provide load for testing, starting a new execution each time one completes.
The worker is available as docker image for use in Docker or Kubernetes setups.
You can pull the latest image from: ghcr.io/temporalio/benchmark-workers:main.
In future we will provide releases with appropriate image tags to make benchmarks more easily repeatable.
The worker can be configured via environment variables. Currently only a small number of options are available, please let us know if there is a particular option you would like to be exposed by filing an issue.
The table below lists the environment variables available and the relevant Temporal Go SDK options they relate to (the worker is currently written using the Temporal Go SDK).
| Environment Variable | Relevant Client or Worker option | Description |
|---|---|---|
| TEMPORAL_GRPC_ENDPOINT | ClientOptions.HostPort | The Temporal Frontend GRPC endpoint |
| TEMPORAL_TLS_KEY | ClientOptions.ConnectionOptions.TLS | Path to TLS Key file |
| TEMPORAL_TLS_CERT | ClientOptions.ConnectionOptions.TLS | Path to TLS Cert file |
| TEMPORAL_TLS_CA | ClientOptions.ConnectionOptions.TLS | Path to TLS CA Cert file |
| TEMPORAL_NAMESPACE | ClientOptions.Namespace | The Temporal Namespace |
| TEMPORAL_TASK_QUEUE | TaskQueue | The Temporal Task Queue |
| TEMPORAL_WORKFLOW_TASK_POLLERS | WorkerOptions.MaxConcurrentWorkflowTaskPollers | Number of workflow task pollers |
| TEMPORAL_ACTIVITY_TASK_POLLERS | WorkerOptions.MaxConcurrentActivityTaskPollers | Number of activity task pollers |
| PROMETHEUS_ENDPOINT | n/a | The address to serve prometheus metrics on |
To run the worker in a Kubernetes cluster you could use:
kubectl run benchmark-worker --image ghcr.io/temporalio/benchmark-workers:main \
--image-pull-policy Always \
--env "TEMPORAL_GRPC_ENDPOINT=temporal-frontend.temporal:7233" \
--env "TEMPORAL_NAMESPACE=default" \
--env "TEMPORAL_TASK_QUEUE=benchmark" \
--env "TEMPORAL_WORKFLOW_TASK_POLLERS=16" \
--env "TEMPORAL_ACTIVITY_TASK_POLLERS=8"
However, we suggest you use a deployment for workers rather than kubectl run so that you can collect metrics via prometheus. We provide an example deployment spec for you to customize to your requirements. Once you have edited the environment variables in the deployment.yaml you can create the deployment with kubectl apply -f ./deployment.yaml.
You can then use the benchmark workflows with your benchmark tool. To test with tctl you could run:
tctl workflow start --taskqueue benchmark --workflow_type ExecuteActivity --execution_timeout 60 -i '{"Count":1,"Activity":"Sleep","Input":{"SleepTimeInSeconds":3}}'
This will run the ExecuteActivity workflow, described below.
The runner is available as docker image for use in Docker or Kubernetes setups.
You can pull the latest image from: ghcr.io/temporalio/benchmark-workers:main.
The runner can be configured via environment variables and command line arguments. Currently only a small number of options are available, please let us know if there is a particular option you would like to be exposed by filing an issue.
The table below lists the environment variables available and the relevant Temporal Go SDK options they relate to (the runner is currently written using the Temporal Go SDK).
| Environment Variable | Relevant Client or Worker option | Description |
|---|---|---|
| TEMPORAL_GRPC_ENDPOINT | ClientOptions.HostPort | The Temporal Frontend GRPC endpoint |
| TEMPORAL_TLS_KEY | ClientOptions.ConnectionOptions.TLS.Certificates | Path to TLS Key file |
| TEMPORAL_TLS_CERT | ClientOptions.ConnectionOptions.TLS.Certificates | Path to TLS Cert file |
| TEMPORAL_TLS_CA | ClientOptions.ConnectionOptions.TLS | Path to TLS CA Cert file |
| PROMETHEUS_ENDPOINT | n/a | The address to serve prometheus metrics on |
The runner is also configured via command line options:
Usage: runner [flags] [workflow input] ...
-c int
concurrent workflows (default 10)
-n string
namespace (default "default")
-t string
workflow type
-tq string
task queue (default "benchmark")
-w wait for workflows to complete (default true)
To use the runner in a Kubernetes cluster you could use:
kubectl run benchmark-runner --image ghcr.io/temporalio/benchmark-workers:main \
--image-pull-policy Always \
--env "TEMPORAL_GRPC_ENDPOINT=temporal-frontend.temporal:7233" \
--command -- runner -t ExecuteActivity '{ "Count": 3, "Activity": "Echo", "Input": { "Message": "test" } }'
The worker provides the following workflows for you to use during benchmarking:
ExecuteActivity({ Count: int, Activity: string, Input: interface{} })
This workflow takes a count, an activity name and an activity input. The activity Activity will be run Count times with the given input. If the activity returns an error the workflow will fail with that error.
The worker provides the following activities for you to use during benchmarking:
Sleep({ SleepTimeInSeconds: int })
This activity sleeps for the given number of seconds. It never returns an error. This can be used to simulate activities which take a while to complete.
Echo({ Message: string }) result
This activity simply returns the message as it's result. This can be used for stress testing polling with activities that return instantly.