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AWS Bites

AWS Bites

By: AWS Bites
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Summary
 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
Episodes
  • 155. How We Made AWS Containers Start Up to 10× Faster!

    155. How We Made AWS Containers Start Up to 10× Faster!
    22 Oct 2026
    What if you could make your AWS containers start up to 10× faster, without changing your application code?In this episode of AWS Bites, we explore practical ways to speed up container startup on AWS, from smaller Docker images and multi-stage builds to smarter compression with gzip and zstd. We discuss the trade-offs between download size and decompression speed, and why optimizing container images is still the best place to start.Then we dive into SOCI (Seekable OCI), an AWS-developed open-source technology that enables lazy loading of container images. Instead of waiting for every image layer to download and unpack, SOCI lets containers start sooner and fetch the files they need on demand. We explain how this works under the hood, including containerd snapshotters, FUSE, zTOCs, compressed spans, and HTTP Range requests. We also explore SOCI support across ECS Fargate, SageMaker, EKS, and ECS on EC2.We share the results of our own open-source benchmark covering 44 configurations and 1,320 ECS task executions. We compare small and large container images, gzip versus zstd, SOCI versus traditional image pulling, ARM64 versus x86-64, and Fargate versus EC2 running Amazon Linux 2023 or Bottlerocket. In some cases, SOCI delivered up to 10× faster container startup for large images on Fargate!Finally, we explain how to create and publish SOCI indexes, explore the tools involved, and discuss when these optimizations are worth adopting. Most importantly, we explain why time to useful work matters more than container startup time alone.Resources mentionedContainer startup benchmark: source code and interactive resultsThe hidden design compromises of Docker layersBuilding x86 Rust containers from Apple SiliconAWS deep dive: Lazy loading container images with SOCISOCI Snapshotter on GitHubAWS SageMaker SOCI documentationECS roadmap: SOCI snapshotter supportECS roadmap: containerd supportSponsorThanks to fourTheorem for powering AWS Bites. We help teams build cloud systems that are simple, scalable, and cost effective. Visit fourtheorem.com.Chapters00:00 Introduction: How to make containers start faster on AWS01:20 Why container startup speed matters: scaling, deployments, and latency03:17 Docker image optimization: smaller images, multi-stage builds, and caching05:33 gzip vs zstd: Compression trade-offs and faster image pulls08:31 Introducing SOCI (Seekable OCI) and lazy loading09:17 Traditional container startup: Why downloading every layer is slow10:40 How SOCI works: Snapshotters, FUSE, and on-demand file loading15:25 SOCI support on AWS: Fargate, SageMaker, EKS, and ECS on EC216:55 SOCI internals: Container layers, zTOCs, gzip spans, and HTTP Range requests21:54 Our benchmark methodology: 44 configurations and 1,320 ECS tasks24:48 Benchmark results: gzip vs zstd and up to 10× faster startup with SOCI26:56 Fargate vs EC2, Bottlerocket vs Amazon Linux, and ARM64 vs x8628:30 Getting started with SOCI: Index generation, ECR, and OCI tools31:38 Key takeaways: When to use zstd, when to use SOCI, and what to measure33:39 Listener questions, fourTheorem sponsor, and closingSend us your AWS questionsDo 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:Eóin: Bluesky | LinkedInLuciano: X/Twitter | Bluesky | LinkedIn
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    35 min
  • 154. S3 Files

    154. S3 Files
    22 May 2026

    We take a deep dive into Amazon S3 Files, AWS's exciting new managed file system backed by S3!

    We kick things off by exploring why S3 isn't a traditional file system, covering everything from the lack of true directories and atomic renames to immutable objects and POSIX access control differences. We then walk through the existing solutions people have used to bridge that gap, like S3FS FUSE, MountPoint for S3, FSx for Lustre, and Storage Gateway.

    From there, we get into the heart of the episode: how S3 Files works, how to set it up, and how it uses EFS under the hood as a caching layer. We share our own real-world benchmarking results comparing S3 Files against various EFS configurations across Lambda and Fargate, and we discuss a real customer project where we put S3 Files to the test.

    We also cover the important caveats like eventual consistency, the 60-second write-back delay, the lack of cross-account bucket support, and the cost model so you can make an informed decision.

    Resources mentioned

    • Episode 124: S3 Performance
    • Episode 95: Mounting S3 as a Filesystem
    • Amazon S3 FAQs: S3 Files
    • fourTheorem S3 Files demo code on GitHub
    • Amazon documentation: Understanding how synchronization works

    Sponsor

    Thanks to fourTheorem for powering AWS Bites. We help teams build cloud systems that are simple, scalable, and cost effective. Visit fourtheorem.com.

    Chapters

    • 00:00 Introduction: Why S3 is amazing but not a file system, and what S3 Files promises to solve
    • 01:47 Why S3 is not a file system: no true directories, immutable objects, no atomic renames, expensive listings, and POSIX differences
    • 05:23 Existing solutions for mounting S3 as a file system: S3FS FUSE, Python fsspec, Hadoop S3A, MountPoint, FSx for Lustre, File Cache, and Storage Gateway
    • 07:16 How S3 Files works: NFS-based access, EFS caching layer, streaming from S3, and supported compute services like EC2, ECS, EKS, and Lambda
    • 09:49 Setting up S3 Files: buckets, file system resources, import and expiration rules, mount targets, access points, VPC requirements, and NFS port configuration
    • 13:42 S3 Files performance numbers from AWS documentation: throughput, IOPS, latency figures, and why real-world benchmarking is recommended
    • 15:39 Benchmarking S3 Files vs EFS configurations on Lambda and Fargate: small and large file reads and writes, memory/CPU impact, and key findings
    • 19:48 Downsides and limitations: NFS only, no hard links, no atomic renames, eventual consistency, the 60-second write-back delay, and large-scale rename performance warnings
    • 23:05 Real-world project experience: a SaaS multi-tenant architecture, cross-account bucket limitation discovered, and how the team worked around it
    • 27:52 Cost breakdown: EFS-equivalent cache pricing, S3 storage costs, reads from cache vs. S3 directly, and how S3 access tiers still apply
    • 29:50 Final recap and take: when S3 Files shines, when to be cautious, mixed access pattern warnings, and an invitation to share your own experiences
    • 33:42 Closing

    Send us your AWS questions

    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:

    • Eóin: Bluesky | LinkedIn
    • Luciano: X/Twitter | Bluesky | LinkedIn
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    34 min
  • 153. LLM Inference with Bedrock

    153. LLM Inference with Bedrock
    6 Mar 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
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