153. LLM Inference with Bedrock

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.htmlCross-region inference https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.htmlQuotas https://docs.aws.amazon.com/bedrock/latest/userguide/quotas.htmlThrottling help https://repost.aws/knowledge-center/bedrock-throttling-errorPrompt caching https://docs.aws.amazon.com/bedrock/latest/userguide/prompt-caching.htmlTroubleshooting error codes https://docs.aws.amazon.com/bedrock/latest/userguide/troubleshooting-api-error-codes.htmlDo 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/

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.html The replay model deep dive (Dev.to): https://dev.to/aws/the-replay-model-how-aws-lambda-durable-functions-actually-work-2a79 Build workflows that last (Dev.to): https://dev.to/aws/aws-lambda-durable-functions-build-workflows-that-last-3ac7 Testing Durable Functions in TypeScript (Dev.to): https://dev.to/aws/testing-aws-lambda-durable-functions-in-typescript-5bj2 Developing Durable Functions with AWS SAM (Dev.to): https://dev.to/aws/developing-aws-lambda-durable-functions-with-aws-sam-ga9 Hands-on notes: https://www.andmore.dev/blog/lambda_durable_functions/ PodWhisperer (open source): https://github.com/fourTheorem/podwhisperer/ WhisperX: https://github.com/m-bain/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:- 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/

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.htmlOur example repo (video processing playground): https://github.com/fourTheorem/lambda-miConcurrency mental model reference (Vercel Fluid Compute): https://vercel.com/fluidLambda 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/

Love AWS Fargate, but occasionally hit the “I need more control” wall (GPUs, storage, network bandwidth, instance sizing)? In this episode of AWS Bites, Eoin and Luciano put the brand-new Amazon ECS Managed Instances (ECS MI) under the microscope as the “middle path” between Fargate simplicity and ECS on EC2 flexibility. We unpack what ECS MI actually is and where it fits in the ECS spectrum, especially how it changes the way you think about clusters and capacity providers. From there we get practical: we talk through the pricing model (EC2 pricing with an additional ECS MI fee that can be a bit counterintuitive if you rely heavily on Reserved Instances or Savings Plans), and we share what it feels like to finally get GPU support in an experience that’s much closer to Fargate than to “full EC2 fleet management”. To make it real, we walk through what we built: a GPU-enabled worker that transcribes podcast audio using OpenAI Whisper, including the end-to-end setup in CDK (roles, capacity provider wiring, task definitions, and service configuration). Along the way we call out the rough edges we ran into, like configuration options that look like they might enable Spot-style behavior, and the operational realities you should expect, such as tasks taking roughly 3–4 minutes to start when ECS needs to provision fresh capacity. We close by mapping out the workloads where ECS MI shines (queue-driven GPU jobs, HPC-ish compute, tighter storage/network control) and the scenarios where it’s probably the wrong choice, like when you need custom AMIs, SSH access, or stricter isolation guarantees.In this episode, we mentioned the following resources: Amazon ECS Managed Instances: ⁠https://aws.amazon.com/ecs/managed-instances/⁠ ECS Managed Instances documentation: ⁠https://docs.aws.amazon.com/AmazonECS/latest/developerguide/ManagedInstances.html⁠ Amazon Bottlerocket (what it is): ⁠https://aws.amazon.com/bottlerocket/⁠ Our CDK ECS MI template: ⁠https://github.com/fourTheorem/cdk-ecs-mi-template⁠ Ep 42. How do you containerise and run your API with Fargate?: ⁠https://awsbites.com/42-how-do-you-containerise-and-run-your-api-with-fargate/⁠ Ep 72. How do you save cost with ECS?: ⁠https://awsbites.com/72-how-do-you-save-cost-with-ecs/⁠ Ep 10. Lambda or Fargate for containers?: ⁠https://awsbites.com/10-lambda-or-fargate-for-containers/⁠ Ep 38. How do you choose the right compute service on AWS?: ⁠https://awsbites.com/38-how-do-you-choose-the-right-compute-service-on-aws/⁠ Ep 143. Is App Runner better than Fargate?: ⁠https://awsbites.com/143-is-app-runner-better-than-fargate/⁠ 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/

We dive deep into Strapi, an open-source headless CMS that's changing how we approach content management and CRUD applications. In this episode, we explore how Strapi separates content from presentation, allowing marketing teams to manage content independently while developers maintain full control over the frontend experience. We discuss the powerful features that caught our attention, including the visual content type builder, dynamic zones, components, and the innovative blocks editor that stores content as JSON rather than HTML. We also cover practical aspects like local development workflows, data synchronization between environments, and deployment strategies on AWS. While we highlight some rough edges around documentation and minor bugs, we share our overall positive experience and provide insights into when Strapi might be the right choice for your next project.In this episode, we mentioned the following resources:Strapi CMS: https://strapi.io/Strapi on GitHub: https://github.com/strapi/strapiStrapi Docs: https://docs.strapi.io/Strapi S3 Provider: https://www.npmjs.com/package/@strapi/provider-upload-aws-s3Strapi installation and pre-requisites: https://docs.strapi.io/cms/installation/cliThe React Block Content renderer: https://github.com/strapi/blocks-react-rendererContentful: https://www.contentful.com/Storyblok: https://www.storyblok.com/Sanity: https://www.sanity.io/HyGraph: https://hygraph.com/Byline CMS: https://bylinecms.app/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/

What if “Java is too old for serverless” is the myth holding your team back in 2025?We put it to the test with Mark Sailes (ex-AWS, Java-on-Lambda expert). In this AWS Bites episode we get specific: when Java is the right call for Lambda and when it isn’t, how to hit real latency targets, and the exact levers that matter in production—SnapStart, provisioned concurrency, smart JVM/GC settings, and whether GraalVM is worth it. We compare vanilla Java, Micronaut, Quarkus, and Spring Boot for startup and memory, share realistic p95/p99 expectations, and outline fast feedback loops with Testcontainers and LocalStack.If Java on Lambda sounds risky, this might change your mind. Stick around for Mark’s tuning checklist and our verdict on when to bet on Java vs pick another runtime.Big shoutout to fourTheorem for powering yet another episode of AWS Bites. At fourTheorem, we believe the cloud should be simple, scalable, and cost-effective, and we help teams do just that. Whether you’re diving into containers, stepping into event-driven architecture, or scaling a global SaaS platform on AWS, or trying to keep cloud spend under control our team has your back. Visit ⁠⁠⁠⁠https://fourTheorem.com⁠⁠⁠⁠ to see how we can help you build faster, better, and with more confidence using AWS cloud!In this episode, we mentioned the following resources:Mark Sailes's website and books: https://www.sailes.co.uk/booksMark's YouTube channel: https://youtube.com/@javainthecloudRunning Java effectively on serverless (ServerlessLand): https://serverlessland.com/content/service/lambda/guides/effectively-running-java-on-serverless/1-introductionLambda execution visualizer: https://lambda-sim.sailes.co.uk/Lambda SnapStart for Java simulator: https://www.sailes.co.uk/learn/lambda-snapstartPenna logging library for Java: https://github.com/hkupty/pennaTestcontainers for Java: https://java.testcontainers.org/Localstack: https://docs.localstack.cloud/aws/Micronaut: https://micronaut.io/Quarkus: https://quarkus.io/GraalVM: https://www.graalvm.org/AWS response to the Log4j issue: https://aws.amazon.com/security/security-bulletins/AWS-2021-005/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/

What if AWS built an IDE to rival your favorite editor? Turns out they did!In this episode of AWS Bites, we dive into Kiro, an AI centric fork of VS Code that tries to turn an empty repo and a loose idea into working software. Kiro imports your VS Code world, then guides you through requirements, design, and a clear task plan before an agent gets to work. We share what clicked, what tripped us up, and how Kiro’s spec driven approach compares to Cursor or Claude Code. We also cover status, limits, pricing, and what this could become if AWS leans in with deep cloud integration. Stick around for our take on whether you should switch or wait.Big shoutout to fourTheorem for powering yet another episode of AWS Bites. At fourTheorem, we believe the cloud should be simple, scalable, and cost-effective, and we help teams do just that. Whether you’re diving into containers, stepping into event-driven architecture, or scaling a global SaaS platform on AWS, or trying to keep cloud spend under control our team has your back. Visit ⁠⁠⁠https://fourTheorem.com⁠⁠⁠ to see how we can help you build faster, better, and with more confidence using AWS cloud!In this episode, we mentioned the following resources: Kiro website: https://kiro.dev/ Kiro docs on Agent Hooks: https://kiro.dev/docs/hooks/ Kiro docs on Steering: https://kiro.dev/docs/steering/ Kiro pricing plans blog: https://kiro.dev/blog/pricing-plans-are-live/ Cargo Lambda: https://www.cargo-lambda.info/ Episode 64: how do you write Lambda functions in Rust?: https://awsbites.com/64-how-do-you-write-lambda-functions-in-rust/ Kiro GitHub issue: https://github.com/kirodotdev/Kiro/issues/2004 Amazon Q developer CLI: https://github.com/aws/amazon-q-developer-cli 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/

What if AWS had its own version of Killed by Google? Well… turns out it kind of does.In this episode of AWS Bites, we explore the AWS Product Lifecycle page, the official place where AWS quietly lists products and services that are being deprecated, shut down, or closed to new customers. If you rely on AWS in production, this is a page you’ll want to bookmark.We walk through what’s on the list today, from Amazon Pinpoint to IoT Analytics and beyond, and we even throw in some predictions of what might be next to hit the chopping block. App Runner vs Beanstalk? API Gateway REST vs HTTP? Let the speculation begin!Big shoutout to fourTheorem for powering yet another episode of AWS Bites. At fourTheorem, we believe the cloud should be simple, scalable, and cost-effective, and we help teams do just that. Whether you’re diving into containers, stepping into event-driven architecture, or scaling a global SaaS platform on AWS, or trying to keep cloud spend under control our team has your back. Visit ⁠⁠https://fourTheorem.com⁠⁠ to see how we can help you build faster, better, and with more confidence using AWS cloud!In this episode, we mentioned the following resources:AWS Product Lifecycle Page: ⁠⁠https://aws.amazon.com/products/lifecycle/⁠⁠AWS Blog – Introducing the AWS Product Lifecycle Page: ⁠⁠https://aws.amazon.com/blogs/aws/introducing-the-aws-product-lifecycle-page-and-aws-service-availability-updates/⁠⁠AWS Bites Episode 98 – Amazon Pinpoint Quota Changes: ⁠⁠https://awsbites.com/98⁠⁠AWS Bites Episode 74 – API Gateway REST vs HTTP: ⁠⁠https://awsbites.com/74⁠⁠AWS Bites Episode 76 – AWS Copilot: ⁠⁠https://awsbites.com/76⁠⁠AWS Bites Episode 143 – Is App Runner Better than Fargate?: ⁠⁠https://awsbites.com/143⁠⁠API Gateway Routing Rules: ⁠⁠https://aws.amazon.com/blogs/compute/dynamically-routing-requests-with-amazon-api-gateway-routing-rules/⁠⁠Alexa+ and the future of generative AI at Amazon: ⁠⁠https://www.aboutamazon.com/news/devices/new-alexa-generative-artificial-intelligence⁠⁠Do 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/

Amazon Aurora DSQL promises to bring a truly serverless experience to SQL databases. But does it actually deliver? In this episode of AWS Bites, we put Aurora DSQL to the test. We explore what makes it exciting, how it compares to traditional Aurora Serverless, and where it falls short. You’ll hear what changed since our last Aurora deep dive, and why DSQL might be the PostgreSQL-compatible serverless database you’ve been waiting for.Big shoutout to fourTheorem for powering yet another episode of AWS Bites. At fourTheorem, we believe the cloud should be simple, scalable, and cost-effective, and we help teams do just that. Whether you’re diving into containers, stepping into event-driven architecture, or scaling a global SaaS platform on AWS, or trying to keep cloud spend under control our team has your back. Visit ⁠https://fourTheorem.com⁠ to see how we can help you build faster, better, and with more confidence using AWS cloud!In this episode, we mentioned the following resources:AWS Blog – Amazon Aurora DSQL is Now Generally Available: ⁠https://aws.amazon.com/blogs/aws/amazon-aurora-dsql-is-now-generally-available/⁠AWS Blog – Introducing Amazon Aurora DSQL: ⁠https://aws.amazon.com/blogs/database/introducing-amazon-aurora-dsql/⁠Aurora DSQL Deep Dive by Amazon: ⁠https://www.youtube.com/watch?v=GCdAngjKZY4⁠DSQL Example Application by fourTheorem: ⁠https://github.com/fourTheorem/dsql-example/⁠PlanetScale Docs – Why Does PlanetScale Not Recommend Constraints: ⁠https://planetscale.com/docs/vitess/operating-without-foreign-key-constraints#why-does-planetscale-not-recommend-constraints-⁠Marc Bowes – How to Spend a Dollar with DSQL: ⁠https://marc-bowes.com/dsql-how-to-spend-a-dollar.html⁠Alessandro Volpicella – Amazon DSQL Pricing Guide: ⁠https://awsfundamentals.com/blog/amazon-dsql-pricing-guide⁠BinaryHeap Blog – First Look at DSQL (The Naughty List): ⁠https://binaryheap.com/first-look-dsql/⁠AWS Bites – Aurora Deep Dive (Episode 122): ⁠https://awsbites.com/122⁠Do 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/

Cost is always top of mind when building in the cloud, and recently AWS has introduced some changes worth paying attention to. In this episode of AWS Bites, we explore a shift that caught many by surprise: the “free” INIT phase for Lambda’s managed runtimes is going away. That cold start time that used to fly under the billing radar? It's now part of the cost. We dig into what this means for your workloads, who might feel the impact, and whether this gives languages like Rust and Go an extra edge. But it’s not all bad news. AWS has also rolled out new pricing tiers for CloudWatch Logs, making it cheaper for high-volume accounts. On top of that, there are new options to send logs directly to S3 or Firehose, helping simplify pipelines and reduce costs. We close with a few tips to help you keep your Lambda and logging spend under control. If you're building on AWS and care about efficiency, this is one you won't want to miss.Big shoutout to fourTheorem for powering yet another episode of AWS Bites. At fourTheorem, we believe the cloud should be simple, scalable, and cost-effective, and we help teams do just that. Whether you’re diving into containers, stepping into event-driven architecture, or scaling a global SaaS platform on AWS, or trying to keep cloud spend under control our team has your back. Visit https://fourTheorem.com to see how we can help you build faster, better, and with more confidence using AWS cloud!In this episode, we mentioned the following resources:AWS Blog – Tiered Pricing for AWS Lambda: https://aws.amazon.com/blogs/compute/introducing-tiered-pricing-for-aws-lambda/Luc van Donkersgoed – When is the Lambda INIT phase free and when is it billed?: https://lucvandonkersgoed.com/2022/04/09/when-is-the-lambda-init-phase-free-and-when-is-it-billed/AWS Bites – Explaining Lambda Runtimes (Episode 104): https://awsbites.com/104-explaining-lambda-runtimes/AWS Blog – Standardized Billing for Lambda INIT Phase: https://aws.amazon.com/blogs/compute/aws-lambda-standardizes-billing-for-init-phase/Lambda Cold Start Benchmarks by Maxim David: https://maxday.github.io/lambda-perf/Duckbill Group Blog – Lambda Logs Just Got Cheaper: https://www.duckbillgroup.com/blog/lambda-logs-just-got-cheaper/AWS Bites – Becoming a Logs Ninja with CloudWatch (Episode 35): https://awsbites.com/35-how-can-you-become-a-logs-ninja-with-cloudwatchDo 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/