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OpenChoreo Kubernetes developer platform, open source

OpenChoreo Kubernetes developer platform: the openchoreo/openchoreo repository describes itself as « a complete, open-source developer platform for Kubernetes ». It targets teams that build an internal developer platform (IDP) by gluing together a portal, CI, GitOps and observability. The project is released under the Apache 2.0 licence and, according to its README, belongs to the CNCF Sandbox.…

OpenChoreo is an open-source Kubernetes developer platform, described as a complete solution by its repository's README. Targeted at teams building internal developer platforms (IDPs), it integrates a portal, CI, GitOps, and observability components. Developed by WSO2, it's a complete rewrite, not a fork, based on OpenChoreo's experience with the Choreo SaaS platform. The platform surfaces logs, metrics, and traces using familiar abstractions like component, project, and environment.

The repository contains a complete Kubernetes developer platform, including the Backstage portal, CLI, GitOps, AI agents, control plane translating abstractions into Kubernetes resources, data plane for workloads, observability plane, and optionally, a CI plane. Abstractions include components, endpoints, and dependencies, with platform teams defining component types, traits, and workflows using Kubernetes resources.

The installation process involves checking prerequisites, running a one-command install script, and opening the Backstage portal. The observability plane is deployed with multiple Helm charts, including a logs module, tracing module, metrics module, and an OpenTelemetry collector. Alerts can be declared as code using a trait, with conditions based on log patterns or resource metrics.

Notifications are sent through email or webhook channels, with the first channel created becoming the default. Additionally, a root cause analysis agent is included, which investigates alerts using ReAct loops and produces structured reports.

Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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