Platform-native observability
Logs, metrics, traces, alerts, and incidents are available where teams manage applications, mapped to platform concepts such as components and projects.
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Observability
Observability is expensive and fragmented when it is bolted on. OpenChoreo makes it part of the developer platform, mapped to the application model, so teams can troubleshoot faster without learning every underlying tool.
Self-service, access control and AI
Developers can investigate issues with AI for the projects and components they manage, while platform teams enforce RBAC and standardize observability backends.
Cost-effective with data sovereignty
OpenChoreo keeps observability within your infrastructure, reducing reliance on external tools, lowering costs, and giving you full ownership of your telemetry data.
01
Self-Service
Developer Self-Service Without Tool Sprawl
OpenChoreo gives developers direct access to runtime signals in the same place they build and deploy applications. Instead of switching between logging tools, metrics dashboards, tracing systems, and cluster views, application teams can investigate issues without switching context.
- Historical build workflow and runtime logs
- Historical CPU, memory and network usage metrics
- Distributed OpenTelemetry traces
- Alerts for log and metrics-based triggers
- Enhanced network observability with eBPF (with Cilium)
02
Integrated Data Model
Observability That Understands the Runtime Topology
OpenChoreo maps telemetry data to the platform model your teams already use. Logs, metrics, traces, alerts, and incidents are tied to domain-based components, projects, and environments rather than raw infrastructure data.
This alignment makes it easier to understand what is failing and why. Teams can correlate telemetry signals across services, navigate dependencies, and reason about system behavior using application-level concepts instead of figuring out tool-specific dashboards and queries.
03
AI, MCP and Skills
Natural Language for Observability
OpenChoreo structures observability data in a way that AI agents can efficiently query and reason about through the observability MCP and API. Because telemetry is tied to platform concepts and runtime topology, you can query telemetry data using natural language.
Claude Code, Codex, OpenCode, Gemini connected to OpenChoreo MCP Servers
$We have user reported failures in the ads-frontend component, find out what went wrong
$How many 500 error codes has the core-api service returned in the last 6 hours? Investigate the reason for each failure as well
$What caused the request with {uuid} to fail last Thursday at 3.00pm in the analytics project?
$What caused the memory spike and resulting OOM kill for the streaming service today?
$Add a log-based alert trait to the 'pdf-processor' component for any logs that matches the string '* failed to render *'
04
Open Standards
Best of Open Source, Built Into Your Platform
OpenChoreo integrates proven open source observability technologies into a unified platform experience. Teams get the flexibility and extensibility of open ecosystems without having to stitch together and operate multiple tools themselves.
Explore other observability modules in the OpenChoreo Ecosystem
Observability that doesn't slow you down.
OpenChoreo brings observability with AI into the developer platform, so teams can troubleshoot issues without switching tools or translating infrastructure signals. This reduces investigation time and MTTR, removes unnecessary friction on platform teams, and creates a more consistent operational model across your organization.