# Serverless Workers - Python SDK > For the complete documentation index, see [llms.txt](https://docs.temporal.io/llms.txt). > Any documentation page is available as raw Markdown by appending `.md` to its URL. > Write Temporal Workers that run on serverless compute using the Python SDK. > **Public Preview** > AWS Lambda support is in Public Preview. GCP Cloud Run support is in Pre-release, and its APIs may change in > backwards-incompatible ways. To request Cloud Run access, create a [support ticket](/cloud/support#support-ticket) or > contact your account team, and [sign up for updates](https://temporal.io/pages/serverless-workers-updates) to hear > when Cloud Run reaches Public Preview. Serverless Workers run on ephemeral, on-demand compute rather than long-lived processes. Temporal invokes the Worker when Tasks arrive, and the Worker shuts down when the work is done. For a general overview of how Serverless Workers work, see [Serverless Workers](/serverless-workers). For the end-to-end deployment guide, see [Deploy a Serverless Worker](/production-deployment/worker-deployments/serverless-workers). ## Supported providers - [**AWS Lambda**](/develop/python/workers/serverless-workers/aws-lambda) - Use the `lambda_worker` contrib package to run a Worker as a Lambda function. Covers setup, configuration, Lambda-tuned defaults, and observability. - [**GCP Cloud Run**](/develop/python/workers/serverless-workers/cloud-run) - Run a standard Worker on a Cloud Run worker pool. Covers the versioned Worker setup, connection configuration, and handling scale-in.