Open-Source DevOps · hyperdxio

hyperdx

HyperDX is an open-source observability platform that unifies logs, metrics, traces, session replays, and errors in a single interface. It runs on top of ClickHouse and supports OpenTelemetry, designed to help teams quickly diagnose production issues without vendor lock-in or expensive SaaS costs.

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Source: GitHub — github.com/hyperdxio/hyperdx

9.7k

GitHub stars

423

Forks

TypeScript

Primary language

MIT

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	hyperdxio/hyperdx
Owner	hyperdxio
Primary language	TypeScript
License	MIT — OSI-approved
Stars	9.7k
Forks	423
Open issues	157
Latest release	cli-v0.5.1 (2026-06-30)
Last updated	2026-07-08
Source	https://github.com/hyperdxio/hyperdx

What hyperdx is

TypeScript-based observability stack with ClickHouse as the backend data store, OpenTelemetry collector integration (ports 4317/4318), and a React frontend. Provides schema-agnostic log/trace search, full-text and property-based query syntax, dashboards, alerting, and APM capabilities optimized for high-cardinality observability data.

Quickstart

Get the hyperdx source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/hyperdxio/hyperdx.git2cd hyperdx3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Self-hosted observability at scale

Teams operating on-premises or hybrid cloud who need to centralize logs, traces, and metrics without vendor SaaS fees. ClickHouse backend handles high-volume telemetry efficiently.

OpenTelemetry-native deployments

Organizations already standardized on OpenTelemetry (Kubernetes, Python, Node.js, Java, Go, etc.) can stream directly into HyperDX without middleware or proprietary agents.

Correlated troubleshooting across signals

Engineering teams needing to search and correlate logs, traces, session replays, and metrics in one place for faster mean-time-to-resolution (MTTR).

Implementation considerations

Requires instrumenting applications with OpenTelemetry SDKs or HyperDX-provided SDKs (Browser, Node.js, Python documented; others require review).
ClickHouse setup is mandatory—either self-hosted cluster or ClickHouse Cloud. Minimum recommended: 4GB RAM, 2 cores for testing; production sizing depends on ingestion volume.
Network requirements: ports 8080 (UI), 8000 (API), 4317/4318 (OTel collector) must be accessible. Firewall rules needed for production.
Schema is agnostic but requires understanding ClickHouse table design and retention policies for cost efficiency at scale.
Anonymous usage data is collected by default in open-source deployments; can be disabled via USAGE_STATS_ENABLED environment variable.

When to avoid it — and what to weigh

No existing ClickHouse infrastructure — Requires ClickHouse cluster setup and maintenance. If you lack database ops expertise or want a fully managed observability service, consider hosted alternatives first.
Minimal observability needs — Small teams with simple logging requirements may find deployment and operational overhead unjustified compared to lightweight log aggregators.
Proprietary agent ecosystem lock-in required — If your team relies heavily on vendor-specific instrumentation (Datadog agents, New Relic SDKs), migration effort to OpenTelemetry may be substantial.
Zero database administration capacity — Managing ClickHouse schema, backups, scaling, and performance tuning requires database literacy. Not suitable for teams without DBOps resources.

License & commercial use

MIT License—permissive OSI license allowing commercial use, modification, and distribution with minimal restrictions (include license and copyright notice).

MIT License permits commercial deployment and modification. However, ensure your use case aligns with operational requirements (ClickHouse, database admin expertise, etc.). No commercial support, SLA, or vendor liability implied by the license alone. Review support channels (Discord, GitHub issues, email) for your SLA needs.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Clear
Deployment complexity	High
DEV.co fit	Good
Assessment confidence	High

Security considerations

No security audit, penetration test results, or vulnerability disclosure policy mentioned in data. Production deployment should include: network isolation of ClickHouse cluster, TLS for OTel collector ingestion (ports 4317/4318), authentication/RBAC for UI (not detailed), data retention policies, and audit logging. Evaluate credential management for ClickHouse connectivity. Anonymous usage collection can be disabled but default-on posture should be reviewed by security teams.

Alternatives to consider

Grafana Loki + Grafana Tempo + Prometheus

Open-source stack; lower infrastructure overhead than ClickHouse; mature ecosystem. Trade-off: less query flexibility, separate tools to stitch together, lower cardinality optimization.

Datadog / New Relic / Elastic Cloud

Fully managed SaaS; strong UX; no ops overhead. Trade-off: vendor lock-in, higher costs at scale, proprietary data formats.

Splunk Enterprise (self-hosted)

Mature, proven observability platform with built-in correlation. Trade-off: expensive licensing, steep learning curve, Java-heavy, legacy tooling feel.

Software development agency

Build on hyperdx with DEV.co software developers

Start with the Docker all-in-one container for a low-risk proof-of-concept. Ensure your team has ClickHouse operational expertise and clarify support/SLA requirements before production deployment.

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hyperdx FAQ

Can I use HyperDX without OpenTelemetry?

Partially. HyperDX is schema-agnostic and works with existing ClickHouse data. However, OpenTelemetry is the recommended path for new instrumentation. Direct ClickHouse writes or custom integrations are possible but not formally documented in the provided data.

What's the minimum ClickHouse setup for production?

Unknown from provided data. README recommends 4GB RAM, 2 cores for testing. Production requirements (replication, sharding, storage) depend on ingestion volume and retention. Consult ClickHouse documentation and HyperDX ops guides.

Is there a managed/hosted version?

Not mentioned in the data. HyperDX describes ClickHouse Cloud integration option ('sign up for free'), but whether HyperDX itself is hosted by the vendor is unclear. Check hyperdx.io for current offerings.

What's the performance impact of session replay + traces + metrics simultaneously?

Unknown. Depends on ingestion rate, ClickHouse hardware, and query complexity. README highlights 'blazing fast searches optimized for ClickHouse' but no benchmarks provided. Test in your environment.

Software development & web development with DEV.co

DEV.co is a software development agency delivering custom software development services to companies building on open source. Our software developers and web developers design, integrate, and ship production systems — spanning web development, APIs, AI, data, and cloud. If hyperdx is part of your open-source devops roadmap, our team can implement, customize, migrate, and maintain it.

Ready to evaluate HyperDX for your observability stack?

Start with the Docker all-in-one container for a low-risk proof-of-concept. Ensure your team has ClickHouse operational expertise and clarify support/SLA requirements before production deployment.

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