HyperDX helps engineers figure out why production is
broken faster by centralizing and correlating logs, metrics, traces, exceptions
and session replays in one place. An open source and developer-friendly
alternative to Datadog and New Relic.
Documentation • Chat on Discord • Live Demo • Bug Reports • Contributing
- 🕵️ Correlate end to end, go from browser session replay to logs and traces in
just a few clicks - 🔥 Blazing fast performance powered by Clickhouse
- 🔍 Intuitive full-text search and property search syntax (ex.
level:err) - 🤖 Automatically cluster event patterns from billions of events
- 📈 Dashboard high cardinality events without a complex query language
- 🔔 Set up alerts in just a few clicks
{Automatic JSON/structured log parsing- 🔭 OpenTelemetry native
Additional Screenshots
📈 Dashboards
🤖 Automatic Event Pattern Clustering
🖥️ Session Replay & RUM
Spinning Up HyperDX
The HyperDX stack ingests, stores, and searches/graphs your telemetry data.
After standing up the Docker Compose stack, you’ll want to instrument your app
to send data over to HyperDX.
You can get started by deploying a complete stack via Docker Compose. After
cloning this repository, simply start the stack with:
Afterwards, you can visit http://localhost:8080 to access the HyperDX UI.
If your server is behind a firewall, you’ll need to open/forward port 8080,
8000 and 4318 on your firewall for the UI, API and OTel collector
respectively.
We recommend at least 4GB of RAM and 2 cores for testing.
Enabling Self-instrumentation/Demo Logs
To get a quick preview of HyperDX, you can enable self-instrumentation and demo
logs by setting the HYPERDX_API_KEY to your ingestion key (go to
http://localhost:8080/team after creating your
account) and then restart the stack.
This will redirect internal telemetry from the frontend app, API, host metrics
and demo logs to your new HyperDX instance.
ex.
sudo for docker, make sure to forward the environmentvariable with the
-E flag:HYPERDX_API_KEY= sudo -E docker compose up -d
Hosted Cloud
HyperDX is also available as a hosted cloud service at
hyperdx.io. You can sign up for a free account and start
sending data in minutes.
Instrumenting Your App
To get logs, metrics, traces, session replay, etc into HyperDX, you’ll need to
instrument your app to collect and send telemetry data over to your HyperDX
instance.
We provide a set of SDKs and integration options to make it easier to get
started with HyperDX, such as
Browser,
Node.js, and
Python
You can find the full list in our docs.
OpenTelemetry
Additionally, HyperDX is compatible with
OpenTelemetry, a vendor-neutral standard for
instrumenting your application backed by CNCF. Supported languages/platforms
include:
- Kubernetes
- Javascript
- Python
- Java
- Go
- Ruby
- PHP
- .NET
- Elixir
- Rust
(Full list here)
Once HyperDX is running, you can point your OpenTelemetry SDK to the
OpenTelemetry collector spun up at http://localhost:4318.
Contributing
We welcome all contributions! There’s many ways to contribute to the project,
including but not limited to:
- Opening a PR (Contribution Guide)
- Submitting feature requests or bugs
- Improving our product or contribution documentation
- Voting on open issues or contributing use cases to a feature request
Motivation
Our mission is to help engineers ship reliable software. To enable that, we
believe every engineer needs to be able to easily leverage production telemetry
to quickly solve burning production issues.
However, in our experience, the existing tools we’ve used tend to fall short in
a few ways:
- They’re expensive, and the pricing has failed to scale with TBs of telemetry
becoming the norm, leading to teams aggressively cutting the amount of data
they can collect. - They’re hard to use, requiring full-time SREs to set up, and domain experts
to use confidently. - They requiring hopping from tool to tool (logs, session replay, APM,
exceptions, etc.) to stitch together the clues yourself.
We’re still early on in our journey, but are building in the open to solv
