Honeycomb
Observability platform for distributed systems and AI workflows
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About Honeycomb
Distributed microservices and non-deterministic AI workflows make modern production environments difficult to debug. Engineering teams often struggle to isolate root causes and understand user-facing failures across complex architectures.
Honeycomb is an observability platform built for debugging distributed software systems and AI applications. It uses an event-based, high-cardinality data model that allows engineering teams to query production telemetry in real time without preaggregation or sampling.
The platform supports distributed tracing, metrics, and logs, alongside dedicated tools for tracking LLM latency, token costs, and multi-agent workflows. It also integrates with AI investigation agents to help developers and site reliability engineers perform root-cause analysis.
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