About Honeycomb
Honeycomb is an observability platform for debugging production software by querying detailed event data. It is built around tracing and high-cardinality fields, so engineers can ask specific questions about live systems.
What it does
Honeycomb stores events from your services and lets you explore them in real time. You can slice the data by many fields at once, view patterns in heatmaps and use BubbleUp to see what differs about slow or failing requests. Teams can also define service level objectives and follow distributed traces across services. Honeycomb supports observability for AI systems, including LLM calls and multi-agent workflows.
Key features
- Real-time queries over high-cardinality production data
- Heatmaps and BubbleUp to spot outliers
- SLOs for tracking service reliability
- Distributed tracing across services
- LLM observability for AI workflows and agents
Who it's for
Honeycomb suits backend engineers, SRE and platform teams that run complex distributed systems. It is also useful for teams building AI features who need to see how their models and agents behave in production.
Pricing and good to know
The site offers a way to start for free, and there is a demo for teams that want a walkthrough. Paid plans are offered for larger use. Honeycomb also provides an MCP server, so AI tools can use your production data during investigations if your team wants that connection.
Highlights
- Real-time queries over high-cardinality production data
- Heatmaps and BubbleUp to spot outliers
- SLOs for tracking service reliability
- Distributed tracing across services
- LLM observability for AI workflows and agents
