Serverless Workers on AWS Lambda
This page covers how Serverless Workers work on AWS Lambda, including the invocation lifecycle, autoscaling behavior, and how Worker Versioning maps to Lambda function versions.
For a step-by-step deployment guide, see Deploy a Serverless Worker on AWS Lambda.
Autoscaling
The Lambda autoscaling algorithm is event-driven and reactive. Sync match failure is the primary control signal, and backlog aids sizing.
When the WCI needs more capacity, it calls the Lambda InvokeFunction API to start new Workers.
Each call is a discrete action ("invoke N more functions"), not a target state.
The WCI does not manage a fleet of instances.
Scale-out
On sync match failure, the WCI invokes new Lambda functions. Because Lambda cold start is sub-second to low single-digit seconds, reactive-only control does not create meaningful backlog overshoot. The WCI can scale from zero with low latency.
Scale-in
Scale-in is automatic. Each Lambda invocation runs until the Worker has finished processing available Tasks or approaches the 15-minute execution time limit, then shuts down. There is no drain logic or stabilization window. The WCI does not need to actively remove capacity.
Instance model
Each invocation is independent. The Worker starts, creates a fresh client connection, processes multiple Tasks until near the execution time limit, and then shuts down gracefully. There is no shared state across invocations.
Worker Versioning
Serverless Workers require Worker Versioning, and the compute provider must invoke a stable, immutable build for each Worker Deployment Version. With AWS Lambda, this means aligning two versioning systems:
- Temporal Worker Deployment Versions — identified by deployment name and Build ID. Each Workflow runs against a specific Worker Deployment Version (Pinned) or moves between them on routing changes (Auto-Upgrade).
- AWS Lambda function versions — immutable numbered snapshots of your Lambda function code (
1,2,3, ...).
A Worker Deployment Version is an immutable build identifier. For production workloads, keep the Lambda function code it
invokes immutable as well: map each Worker Deployment Version to exactly one Lambda function version, and configure the
compute provider with the qualified
versioned ARN for that Lambda version (for
example, arn:aws:lambda:us-east-1:123:function:my-worker:5).
For development or non-critical workloads, you can use an unqualified ARN to iterate without publishing a new Lambda function version each time.
An unqualified ARN (no version suffix) points at $LATEST, which changes on every redeploy. Without a versioned ARN,
deploying replay-unsafe code causes non-determinism errors for in-flight Workflows, even for Workflows annotated as
Pinned.
How the Versioning Behavior changes rollout
The choice of Pinned or Auto-Upgrade controls how Workflows move between Worker Deployment Versions in Temporal. It does not change how a Worker Deployment Version targets Lambda. Both behaviors expect a versioned ARN that points at one immutable Lambda function version. The following table shows what happens to existing Workflows when you set a new Current Version, with and without versioned Lambda ARNs.
| Versioning Behavior | With versioned Lambda ARN | Without versioned Lambda ARN |
|---|---|---|
| Pinned | Existing Workflows stay on their original Lambda function version until they complete. | Existing Workflows stay on their original Worker Deployment Version, but the underlying Lambda code has already changed since $LATEST updated at redeploy. The new code must be replay-compatible. |
| Auto-Upgrade | Existing Workflows move to the new Worker Deployment Version and its new Lambda function version at the next Workflow Task after you move the Current Version. | The Lambda redeploy already changed the code for all versions. Setting the Current Version only changes routing, not which code runs. |
For step-by-step instructions on publishing Lambda versions and configuring the compute provider with a versioned ARN, see Publish a Lambda function version.