HyperDX Local – Open-source Datadog alternative for local debugging/dev
Hi HN, Mike and Warren here! We’ve been building an open source local-dev-friendly mode for HyperDX (hyperdx.io). It's a single Docker container that lets you view logs, metrics, and traces for local development in a similar way you can use them for production (live tail, filter/correlate logs & spans, build charts, flamegraph, etc.) Basically, imagine you can run Datadog in a single container for local development. We does this by spinning up an OpenTelemetry collector, Clickhouse DB and HyperDX UI all in a single container - it only takes a few seconds to start and lets you start live…
In plain words
HyperDX Local is an open-source Docker container that provides local development debugging capabilities similar to Datadog. It bundles an OpenTelemetry collector, ClickHouse database, and HyperDX UI to let developers view logs, metrics, and traces for their local applications. The tool supports live log tailing, filtering and correlating logs with spans, charting metrics, and viewing flamegraphs. It starts in seconds and is designed for developers who want production-like observability during local development without external services.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hi HN, Mike and Warren here! We’ve been building an open source local-dev-friendly mode for HyperDX (hyperdx.io). It's a single Docker container that lets you view logs, metrics, and traces for local development in a similar way you can use them for production (live tail, filter/correlate logs & spans, build charts, flamegraph, etc.) Basically, imagine you can run Datadog in a single container for local development. We does this by spinning up an OpenTelemetry collector, Clickhouse DB and HyperDX UI all in a single container - it only takes a few seconds to start and lets you start live tailing your local logs and traces immediately (and graph metrics of course). README (w/ demo gif): https://github.com/hyperdxio/hyperdx/blob/main/LOCAL.md We started building local mode as it became one of our most loved [1] community issue after sharing HyperDX. It made sense - as we constantly use HyperDX to debug our own issues locally, and have found it to be a huge productivity boost for things like… 1. Tailing multiple container logs (and grepping/isolating them) without a ton of different terminal splits open at the same time. 2. Be able to sensibly view structured logs and correlated traces to debug local issues (because you’re using structured logging and tracing right?) instead of adding ad-hoc console statements that print out exactly what I could’ve gotten from tracing. 3. Testing telemetry are actually emitting/correlating as expected, before shipping it all the way out to prod and realizing I accidentally created a very expensive high-cardinality metric or a span that has the wrong properties. We spent some time packaging & tuning our existing OSS stack to run in a single container with less memory/space requirements by staring at `dive` to slim down the image and applied incantations from documentation until memory usage improved. Additionally we removed a few non-local-friendly things like authentication requirements and extraneous services. It still has all the goodness you’d want - so you can full text search your logs/traces, live tail all your events, view spans correlated with logs (and vice versa), create dashboards based on logs, metrics, traces, and is fully OpenTelemetry compatible - just point your Otel SDK/collector to http://localhost:4318 (or 4317 for the grpc folks) and you’re already good to go. I’m excited to share what we’ve been working on and would love to hear your feedback and opinions! Spin up the container yourself to try it out: docker run -p 8000:8000 -p 4318:4318 -p 4317:4317 -p 8080:8080 -p 8002:8002 hyperdx/hyperdx-local Main Open Source Repo: https://github.com/hyperdxio/hyperdx Hosted Demo (in case you want to play around in a cloud sandbox instead): https://api.hyperdx.io/login/demo HyperDX Landing Page: https://hyperdx.io [1]: https://github.com/hyperdxio/hyperdx/issues/7
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