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https://openchoreo.devA modular, open-source developer platform for Kubernetes. OpenChoreo provides a Kubernetes-native system organized into Control, Data, Workflow, and Observability planes, enabling platform engineers to build Internal Developer Platforms (IDPs) using custom ResourceTypes and ProjectTypes.
OpenChoreo provides a set of specialized AI agents to extend platform capabilities:
Validation rules use Common Expression Language (CEL) expressions wrapped in ${} that must evaluate to true for validation to pass. They complement schema validation by enabling cross-field relationships, domain-specific invariants, rendering context validation, and custom error messages.
Validations occur in two stages:
preRenderValidations): Runs before rendering against static configuration (parameters, environmentConfigs, workload, etc.).postRenderValidations): Runs after all traits are applied against the final rendered Kubernetes resources.Critical Constraint: ComponentTypes and Traits are environment-agnostic. Validation rules must never hard-code environment names (e.g., "production"). Instead, use environmentConfigs to vary behavior per environment.
The Bulk Promote workflow allows developers to promote multiple Components to a target Environment (such as staging or production) in a single operation. Unlike build-and-release workflows, this process has no build phase; it operates purely on the GitOps repository to bind existing ComponentReleases to a target Environment.
Prerequisite: Components must be previously built using build-and-release workflows. The bulk promote workflow can only bind existing ComponentReleases.
Common Use Cases:
ResourceType is a platform-defined template in the openchoreo.dev/v1alpha1 API that governs how managed infrastructure (e.g., databases, queues, caches, object stores) is provisioned on the data plane and exposed to consumers. It defines the Kubernetes manifests to be emitted, the parameters developers can supply, environment-specific overrides, and the named outputs that workloads consume via environment or file bindings.Delivery Insights is an alpha feature that reports the four DORA metrics for components deployed by OpenChoreo. Metrics can be sliced by environment and viewed at the namespace, project, or component scope. Data is aggregated by the Observer every five minutes.
| Metric | Answers | Derived from |
|---|---|---|
| Deployment Frequency | How often do we ship? | Rollouts that reached a healthy state |
| Lead Time for Changes | How long from commit to running? | Commit authoring time to rollout ready time |
| Change Failure Rate | How often does shipping break something? | Failed rollouts, and incidents attributed to a rollout |
| Mean Time to Recovery | How long until we are healthy again? | Incidents, from trigger to resolution |
Each metric includes a value, a DORA classification (Elite, High, Medium, Low), a trend against the previous window of equal length, and a time-bucketed series (daily, weekly, or monthly).
OpenChoreo is a modular, open-source developer platform for Kubernetes designed to help platform teams build Internal Developer Platforms (IDPs). It integrates several core capabilities into a single cohesive platform, including:
Unlike platforms that hide Kubernetes, OpenChoreo uses Kubernetes-native APIs and controllers to augment Kubernetes, ensuring infrastructure teams maintain full control while providing application teams with simplified, intent-driven abstractions and 'golden paths'.
OpenChoreo provides two distinct MCP servers that allow AI assistants to interact with the platform. Each server is independently accessible and requires its own configuration:
Recommended Workflow: Use both servers together. Use the Control Plane MCP server to discover resource names (e.g., via list_namespaces or list_projects) and then pass those names as parameters to the Observability Plane MCP tools to fetch specific data.
A ResourceType is a platform-engineer-defined template that governs how managed-infrastructure resources (e.g., databases, queues, caches) are provisioned on the data plane and exposed to consumers. It defines the Kubernetes manifests to be emitted, the parameters developers can configure, environment-specific overrides, and the named outputs that workloads use to connect to the resource.
There are two scopes available:
OpenChoreo uses a split architecture between a Control Plane and a Workflow Plane to manage reusable pipelines:
ComponentType template which determines the workload type (e.g., Deployment, StatefulSet, CronJob) and default configuration. Components can be configured to build from source code using workflows or deploy pre-built container images.occ remote enables developers to run code on their local machine against real upstream dependencies in an environment. The architecture consists of a remote-agent-router (one per data plane) and a remote-agent (provisioned on demand per project and environment). occ connects to the router, which routes traffic to the appropriate agent based on the TLS ClientHello's SNI. TLS terminates at the agent, not the router. The agent authorizes streams via the openchoreo-api and dials the dependency.OpenChoreo provides automated workflows to handle the deployment of Components using a GitOps approach. The process is split into two phases:
occ CLI to generate the necessary GitOps resources, and opens a pull request.Once the PR is merged, a GitOps operator (like Flux CD) syncs the resources to the cluster.