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#backendengineering — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #backendengineering, aggregated by home.social.

  1. If this resonates, share your service template patterns or open an issue with gaps you hit in production.
    If gogen helps, a star and field feedback help prioritize what to improve next.
    #OpenSource #GoLang #BackendEngineering #Observability #APIDesign #CloudNative #DistributedSystems

  2. This is a hands-on walkthrough of building a real-time dashboard with Quarkus + Redis TimeSeries.

    Live ingestion via WebSockets, automatic downsampling, multi-resolution queries, and a simple browser UI.
    Crypto is just the data source. The patterns apply to metrics, IoT, and event streams.

    the-main-thread.com/p/real-tim

    #Java #Quarkus #Redis #TimeSeries #BackendEngineering #EventStreaming

  3. This is a hands-on walkthrough of building a real-time dashboard with Quarkus + Redis TimeSeries.

    Live ingestion via WebSockets, automatic downsampling, multi-resolution queries, and a simple browser UI.
    Crypto is just the data source. The patterns apply to metrics, IoT, and event streams.

    the-main-thread.com/p/real-tim

    #Java #Quarkus #Redis #TimeSeries #BackendEngineering #EventStreaming

  4. This is a hands-on walkthrough of building a real-time dashboard with Quarkus + Redis TimeSeries.

    Live ingestion via WebSockets, automatic downsampling, multi-resolution queries, and a simple browser UI.
    Crypto is just the data source. The patterns apply to metrics, IoT, and event streams.

    the-main-thread.com/p/real-tim

    #Java #Quarkus #Redis #TimeSeries #BackendEngineering #EventStreaming

  5. This is a hands-on walkthrough of building a real-time dashboard with Quarkus + Redis TimeSeries.

    Live ingestion via WebSockets, automatic downsampling, multi-resolution queries, and a simple browser UI.
    Crypto is just the data source. The patterns apply to metrics, IoT, and event streams.

    the-main-thread.com/p/real-tim

    #Java #Quarkus #Redis #TimeSeries #BackendEngineering #EventStreaming

  6. This is a hands-on walkthrough of building a real-time dashboard with Quarkus + Redis TimeSeries.

    Live ingestion via WebSockets, automatic downsampling, multi-resolution queries, and a simple browser UI.
    Crypto is just the data source. The patterns apply to metrics, IoT, and event streams.

    the-main-thread.com/p/real-tim

    #Java #Quarkus #Redis #TimeSeries #BackendEngineering #EventStreaming

  7. Validation logic drifting between frontend, backend, and batch jobs is a real production problem.

    This article shows how to move validation into your Protobuf schema using Protovalidate, and enforce the same rules in Quarkus, JavaScript, Python, and more.

    Schema as contract. Validation as infrastructure.

    👉 the-main-thread.com/p/protobuf

    #Java #Quarkus #Protobuf #APIDesign #SchemaFirst #BackendEngineering #FOSS

  8. Feature flags are not booleans.
    They are runtime decisions.

    In this article, I walk through building a production-grade feature flag system in Quarkus:
    – database-backed flags
    – security-aware evaluation
    – runtime toggles without redeploys
    – a Qute UI that shows what’s actually enabled

    If you’ve ever shipped a feature “disabled by config” and regretted it later, this one’s for you.

    the-main-thread.com/p/feature-

    #Java #Quarkus #SoftwareArchitecture #FeatureFlags #BackendEngineering

  9. Infinite scroll usually fails for boring reasons.

    Offset pagination looks fine in the first demo. Then users scroll deeper, queries get slower, and the database starts doing more work for every request.

    This article walks through building cursor pagination with Quarkus and PostgreSQL. Not as a pattern diagram, but as a real API that stays fast no matter how far you scroll.

    the-main-thread.com/p/quarkus-

    #Java #Quarkus #PostgreSQL #BackendEngineering #APIDesign #Performance