Durable execution in Pydantic AI agents with AWS Lambda Durability

AWS Lambda durable functions can prevent long-running AI agents from repeating completed model requests and external tool calls after timeouts or retries by checkpointing each operation and replaying stored results when execution resumes. Pydantic AI Harness adds this capability through AWSLambdaDurability and durable handler decorators, allowing agents to retain their existing APIs while durable executions can run for up to a year, pause for external events, and avoid compute charges while waiting. Deployment requires durable Lambda configuration, published function versions, and IAM permissions for checkpoint access, while Logfire can connect checkpointed steps to traces across separate invocations. Developers can configure retry behavior, checkpoint semantics, and serialization per tool, but must design side-effecting operations to be idempotent because interruptions before checkpointing may still cause re-execution. Durable handlers run tool calls sequentially to preserve checkpoint order, cannot stream output directly to callers, and require careful versioning because changes to agent, model, toolset, or execution order can invalidate in-flight runs. Lambda durability is one of five durable-execution options supported by Pydantic AI and is intended for teams seeking workflow resilience without adding a separate orchestration service.

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