152. Exploring Lambda Durable Functions

AWS Lambda is fantastic for small, stateless code on demand. But when your “function” starts looking like a workflow (retries, backoff, long waits, human approvals, callbacks), classic Lambda patterns can feel like a fight: 15-minute max runtime, no built-in state, and orchestration glue everywhere (Step Functions, queues, schedules, and state you did not want to own). In this episode of AWS Bites, Eoin and Luciano explore AWS Lambda Durable Functions, announced at re:Invent 2025. It’s still Lambda (same runtimes and scaling), but with durable execution superpowers: named steps, automatic checkpointing, and the ability to suspend and resume from a safe point without redoing completed work. We unpack the replay/resume model under the hood, when this approach shines, and the gotchas (determinism, idempotency, replay-aware logging, debugging resumed runs). To make it real, we share how we rebuilt PodWhisperer v2 using Durable Functions to orchestrate a GPU-powered WhisperX pipeline, LLM refinement, speaker naming, and caption generation. In this episode, we mentioned the following resources: AWS announcement blog post: Durable Functions best practices: The replay model deep dive (Dev.to): Build workflows that last (Dev.to): Testing Durable Functions in TypeScript (Dev.to): Developing Durable Functions with AWS SAM (Dev.to): Hands-on notes: PodWhisperer (open source): WhisperX: Do you have any AWS questions you would like us to address? Leave a comment here or connect with us on X/Twitter, BlueSky or LinkedIn: - | | - | |

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152. Exploring Lambda Durable Functions is an episode from AWS Bites by AWS Bites.

This episode is 00:48:48 long.

This episode was published on Feb 6, 2026.

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