CanyonOS 0.2 Debuts as Open-Source Agent Observability Tool
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CanyonOS 0.2 is the first public release of an open-source, model-agnostic tool for finding, observing and scaling agents that slow down workflows. It runs on Docker or Kubernetes and works with any provider offering an OpenAI-compatible API, exporting OpenTelemetry-compatible traces and metrics to tools such as Datadog, Grafana, Prometheus, Langfuse and Arize Phoenix, with cost and queue time tracked per agent. The project is AGPL-3.0 licensed, so anyone who modifies it and offers it to others over a network must make those changes' source available. Adopting it requires rewriting agents into plain Python, one file per agent. Its FAQ states it has not yet run at large production scale, and the project describes itself as active with weekly releases.
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- Hacker News · AICanyonOS 0.2 launches as open-source tool to find, observe and scale agents
CanyonOS 0.2 is the first public release of an open-source, model-agnostic tool for finding, observing and scaling agents that slow down workflows. It runs on Docker or Kubernetes, works with any provider offering an OpenAI-compatible API, exports OpenTelemetry-compatible traces and metrics to tools such as Datadog, Grafana, Prometheus, Langfuse and Arize Phoenix, and adds cost and queue time per agent. The project is AGPL-3.0 licensed, requires agents to be rewritten into plain Python with one file per agent, and its FAQ states it has not yet run at large production scale.
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