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AWS Bites

AWS Bites

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 AWS Bites is the show where we answer questions about AWS! This show is brought to you be Eoin Shanaghy and Luciano Mammino, certified AWS experts.AWS Bites
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  • 153. LLM Inference with Bedrock

    153. LLM Inference with Bedrock
    Mar 6 2026

    If you’re curious about building with LLMs, but you want to skip the hype and learn what it takes to ship something reliable in production, this episode is for you.We share our real-world experience building AI-powered apps and the gotchas you hit after the demo: tokens and cost, quotas and throttling, IAM and access friction, marketplace subscriptions, and structured outputs that do not break your JSON parser.We focus on Amazon Bedrock as AWS’s managed inference layer: how to get started with the current access model, how to choose models, how pricing works, and what to watch for in production.We also go deep on structured outputs: constrained decoding, schema design that improves output quality, and how to avoid “grammar compilation timed out”.


    In this episode, we mentioned the following resources:

    • fourTheorem: Bedrock structured outputs guide https://fourtheorem.com/amazon-bedrock-structured-outputs/
    • Amazon Bedrock https://aws.amazon.com/bedrock/
    • Bedrock docs https://docs.aws.amazon.com/bedrock/latest/userguide/
    • Bedrock pricing https://aws.amazon.com/bedrock/pricing/
    • Structured outputs https://docs.aws.amazon.com/bedrock/latest/userguide/structured-outputs.html
    • Cross-region inference https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.html
    • Quotas https://docs.aws.amazon.com/bedrock/latest/userguide/quotas.html
    • Throttling help https://repost.aws/knowledge-center/bedrock-throttling-error
    • Prompt caching https://docs.aws.amazon.com/bedrock/latest/userguide/prompt-caching.html
    • Troubleshooting error codes https://docs.aws.amazon.com/bedrock/latest/userguide/troubleshooting-api-error-codes.html


    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:


    - ⁠https://twitter.com/eoins⁠ | ⁠https://bsky.app/profile/eoin.sh⁠ | ⁠https://www.linkedin.com/in/eoins/⁠

    - ⁠https://twitter.com/loige⁠ | ⁠https://bsky.app/profile/loige.co⁠ | ⁠https://www.linkedin.com/in/lucianomammino/
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    43 Min.
  • 152. Exploring Lambda Durable Functions

    152. Exploring Lambda Durable Functions
    Feb 6 2026
    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: https://aws.amazon.com/blogs/aws/build-multi-step-applications-and-ai-workflows-with-aws-lambda-durable-functions/Durable Functions best practices: https://docs.aws.amazon.com/lambda/latest/dg/durable-best-practices.htmlThe replay model deep dive (Dev.to): https://dev.to/aws/the-replay-model-how-aws-lambda-durable-functions-actually-work-2a79Build workflows that last (Dev.to): https://dev.to/aws/aws-lambda-durable-functions-build-workflows-that-last-3ac7Testing Durable Functions in TypeScript (Dev.to): https://dev.to/aws/testing-aws-lambda-durable-functions-in-typescript-5bj2Developing Durable Functions with AWS SAM (Dev.to): https://dev.to/aws/developing-aws-lambda-durable-functions-with-aws-sam-ga9Hands-on notes: https://www.andmore.dev/blog/lambda_durable_functions/PodWhisperer (open source): https://github.com/fourTheorem/podwhisperer/WhisperX: https://github.com/m-bain/whisperXDo 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:- https://twitter.com/eoins | https://bsky.app/profile/eoin.sh | https://www.linkedin.com/in/eoins/- https://twitter.com/loige | https://bsky.app/profile/loige.co | https://www.linkedin.com/in/lucianomammino/
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    49 Min.
  • 151. EC2 ❤️ Lambda - Lambda Managed Instances

    151. EC2 ❤️ Lambda - Lambda Managed Instances
    Jan 16 2026

    AWS just made Lambda… less serverless. Lambda Managed Instances (Lambda MI) brings managed EC2 capacity into Lambda, and it changes the rules: environments stay warm, a single environment can handle multiple concurrent invocations, and scaling becomes proactive and asynchronous instead of “spin up on demand when traffic hits.”In this episode of AWS Bites, Eoin and Luciano break down what Lambda MI unlocks (and what it costs): fewer traditional cold starts, but a new world of capacity planning, headroom, and potential throttling during fast spikes. We compare it to Default Lambda, explain how the new scaling signals work, and what “ACTIVE” really means when publishing can take minutes on a new capacity provider.To make it real, we built a video-processing playground: an API, a CPU-heavy processor, and a Step Functions workflow that scales up before work and back down after. We share the practical lessons, the rough edges (regions, runtimes, mandatory VPC, minimum 2 GB + 1 vCPU, concurrency pitfalls), and the pricing reality: requests + EC2 cost + a 15% management fee.


    In this episode, we mentioned the following resources:

    • Lambda Managed Instances official docs: https://docs.aws.amazon.com/lambda/latest/dg/lambda-managed-instances.html
    • Our example repo (video processing playground): https://github.com/fourTheorem/lambda-mi
    • Concurrency mental model reference (Vercel Fluid Compute): https://vercel.com/fluid
    • Lambda MI Node.js runtime best practices (concurrency considerations): https://docs.aws.amazon.com/lambda/latest/dg/lambda-managed-instances-nodejs-runtime.html


      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:


      - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/eoins⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bsky.app/profile/eoin.sh⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/eoins/⁠⁠⁠⁠

      ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/loige⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bsky.app/profile/loige.co⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/lucianomammino/
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      36 Min.
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