⚠️ This project is 100% experimental. Please do not attempt to install the controller in any production and/or shared environment.
The goal of the Temporal Worker Controller is to make it easy to run workers on Kubernetes while leveraging Worker Versioning.
Temporal's deterministic constraints can cause headaches when rolling out or rolling back workflow code changes.
The traditional approach to workflow determinism is to gate new behavior behind versioning checks. Over time these checks can become a source of technical debt, as safely removing them from a codebase is a careful process that often involves querying all running workflows.
Worker Versioning is an alternative approach which enables workflow executions to be sticky to workers running a specific code revision. This allows a workflow author to omit version checks in code and instead run multiple versions of their worker in parallel, relying on Temporal to keep workflow executions pinned to workers running compatible code.
This project aims to provide automation which simplifies the bookkeeping around tracking which worker versions still have active workflows, managing the lifecycle of versioned worker deployments, and calling Temporal APIs to update the default version after a deployment.
- Registration of new worker versions
- Creation of versioned worker deployment resources
- Deletion of unreachable worker deployments
- Manual, Blue/Green, and Progressive rollouts of new worker versions
- Autoscaling of worker deployments
- Automated rollover to compatible worker versions
- Canary analysis of new worker versions
- Optional cancellation after timeout for workflows on old versions
- Passing
ContinueAsNew
signal to workflows on old versions
In order to be compatible with this controller, workers need to be configured using these standard environment variables:
WORKER_BUILD_ID
TEMPORAL_HOST_PORT
TEMPORAL_TASK_QUEUE
TEMPORAL_NAMESPACE
Each of these will be automatically set in the pod template's env, and do not need to be manually specified outside the
TemporalWorker
spec.
Every TemporalWorker
resource manages one or more standard Deployment
resources. Each deployment manages pods
which in turn poll Temporal for tasks pinned to their respective versions.
flowchart TD
wd[TemporalWorker]
subgraph "Latest/default worker version"
d5["Deployment v5"]
rs5["ReplicaSet v5"]
p5a["Pod v5-a"]
p5b["Pod v5-b"]
p5c["Pod v5-c"]
d5 --> rs5
rs5 --> p5a
rs5 --> p5b
rs5 --> p5c
end
subgraph "Deprecated worker versions"
d1["Deployment v1"]
rs1["ReplicaSet v1"]
p1a["Pod v1-a"]
p1b["Pod v1-b"]
d1 --> rs1
rs1 --> p1a
rs1 --> p1b
dN["Deployment ..."]
end
wd --> d1
wd --> dN
wd --> d5
p1a -. "poll version v1" .-> server
p1b -. "poll version v1" .-> server
p5a -. "poll version v5" .-> server
p5b -. "poll version v5" .-> server
p5c -. "poll version v5" .-> server
server["Temporal Server"]
When a new worker version is deployed, the worker controller automates the registration of a new default worker version in Temporal.
As older workflows finish executing and deprecated worker versions are no longer needed, the worker controller also frees up resources by deleting old deployments.
sequenceDiagram
autonumber
participant Dev as Developer
participant K8s as Kubernetes
participant Ctl as WorkerController
participant T as Temporal
Dev->>K8s: Create TemporalWorker "foo" (v1)
K8s-->>Ctl: Notify TemporalWorker "foo" created
Ctl->>K8s: Create Deployment "foo-v1"
Ctl->>T: Register v1 as new default
Dev->>K8s: Update TemporalWorker "foo" (v2)
K8s-->>Ctl: Notify TemporalWorker "foo" updated
Ctl->>K8s: Create Deployment "foo-v2"
Ctl->>T: Register v2 as new default
Ctl->>Ctl: Run breaking change detection between v1 and v2
Ctl->>T: If versions compatible, merge v1 and v2.
loop Poll Temporal API
Ctl-->>T: Wait for v1 workflow executions to close
end
Ctl->>K8s: Delete Deployment "foo-v1"
This project is in very early stages; as such external code contributions are not yet being solicited.
Bug reports and feature requests are welcome! Please file an issue.
You may also reach out to @jlegrone
on the Temporal Slack if you have questions, suggestions, or are
interested in making other contributions.