CNCF Sandbox application for CAIPE
Application for CNCF Sandbox. This post tracks the text merged in cnoe-io/ai-platform-engineering#904; copy each section into the corresponding field of the GitHub issue form when submitting.
Basic project information
Project tagline
CAIPE is an integrated, open source distributed multi-agent system and reference implementation for automating platform engineering and cloud native operations, with standardized protocols, built-in knowledge bases, curated platform skills, enterprise security, a rich UX, and multiple client integrations.
Project description
Community AI Platform Engineering (CAIPE, pronounced "cape") is an open source distributed Multi-Agent System (MAS) developed under the CNOE (Cloud Native Operational Excellence) Agentic AI SIG. As platform engineering, SRE, and DevOps environments grow in complexity, traditional approaches often lead to operational delays, fragmented tooling, and developer friction. CAIPE addresses this by providing a secure and scalable persona-driven reference implementation that orchestrates specialized AI agents. Each agent integrates securely with platform tools such as ArgoCD, Backstage, GitHub, PagerDuty, Jira, Slack, and Kubernetes using standardized interoperability protocols.
Built on open source agentic SDKs and the latest open standards in inter-agent and tool communication such as A2A, MCP, and A2UI, CAIPE's architecture enables agents to be developed, deployed, and scaled independently while securely interacting with Kubernetes platforms, cloud native infrastructure, and operational tooling.
The platform includes a curated prompt and skills library evaluated for reliability in agentic workflows, a modern AI-native user interface for interacting with agents, the Agent Forge plugin contributed upstream to backstage/community-plugins for Internal Developer Portal integration, and a command line interface for automation and developer workflows. The system also includes enterprise-grade security with OAuth2 and JWT-based agent authentication and production-ready deployment patterns using Docker Compose and Helm charts.
CAIPE also provides extensible knowledge bases that support retrieval-augmented generation (RAG) and GraphRAG. These knowledge systems enable agents to reason over both unstructured documentation and structured relationships between systems, services, and operational data. In addition, CAIPE supports persistent agent memory, fact extraction, and recall. Agents can extract operational knowledge from workflows, incident investigations, and platform telemetry, store these facts in shared knowledge systems, and reuse them in future tasks.
This capability allows agents to maintain contextual awareness across workflows in Kubernetes and cloud native environments. For example, agents can recall prior incidents, service dependencies, deployment history, and troubleshooting outcomes when assisting with new operational tasks. This reduces repeated investigation and improves operational efficiency.
The platform also includes built-in tracing via OpenTelemetry-compatible tooling (Langfuse), evaluation pipelines, and workflow observability to ensure predictable and auditable automation. Curated platform engineering skills encode operational best practices for common tasks such as incident investigation, GitOps deployment workflows, and platform diagnostics.
CAIPE fills a gap in the cloud native ecosystem by providing a vendor-neutral and community-driven reference architecture for applying agentic AI to platform engineering and operations. It enables teams to automate complex workflows across multiple tools, reduce mean time to resolution (MTTR), and accelerate developer self-service while maintaining transparency, governance, and operational reliability within modern Kubernetes and cloud native platforms.
Project details
Org repo URL
Project repo URL in scope of application
https://github.com/cnoe-io/ai-platform-engineering
Additional repos in scope of the application
- https://github.com/cnoe-io/agent-chat-cli — CLI client for A2A agent interaction
- https://github.com/cnoe-io/openapi-mcp-codegen — OpenAPI-to-MCP server code generator
- https://github.com/cnoe-io/cnoe-agent-utils — Shared Python utilities for CAIPE agents
- https://github.com/cnoe-io/community-plugins/tree/agent-forge-upstream-docker/workspaces/agent-forge — Agent Forge Backstage plugin (upstream contribution to backstage/community-plugins, published as @caipe/plugin-agent-forge on npm)
Website URL
https://cnoe-io.github.io/ai-platform-engineering/
Roadmap
CAIPE's roadmap is developed openly through GitHub issues and community working groups and is tracked in the project roadmap board.
Project roadmap: https://github.com/orgs/cnoe-io/projects/9
Issues and feature discussions: https://github.com/cnoe-io/ai-platform-engineering/issues
Key roadmap themes include:
-
Agent ecosystem expansion Adding new agents for cloud native and platform engineering tools such as Crossplane, Backstage catalog, Prometheus/Grafana, and cloud provider services, along with a plugin registry for community-contributed agents.
-
Enterprise hardening Improving multi-tenancy, agent-level RBAC, audit logging, and policy-based guardrails using technologies such as OPA/Rego.
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Evaluation and observability Expanding automated evaluation pipelines and integrating with observability platforms such as Langfuse and OpenTelemetry to measure agent reliability and workflow execution.
-
Knowledge systems Enhancing RAG capabilities with GraphRAG, ontology-driven entity extraction, persistent memory, and multi-source ingestion of organizational knowledge.
-
Standards alignment Continued alignment with emerging agent interoperability standards such as A2A and MCP, and integration patterns across the cloud native ecosystem.
-
Community growth Expanding contributors through working groups, improved onboarding, and community workshops such as CAIPE Labs.
Project documentation: https://cnoe-io.github.io/ai-platform-engineering/
Contributing guide
https://github.com/cnoe-io/ai-platform-engineering/blob/main/CONTRIBUTING.md
Code of Conduct (CoC)
https://github.com/cnoe-io/governance/blob/main/CODE-OF-CONDUCT.md
Adopters
https://github.com/cnoe-io/ai-platform-engineering/blob/main/ADOPTERS.md
Maintainers file
https://github.com/cnoe-io/ai-platform-engineering/blob/main/MAINTAINERS.md
Security policy file
https://github.com/cnoe-io/ai-platform-engineering/blob/main/SECURITY.md
Standard or specification?
N/A. CAIPE is not a standard or specification. It is a reference implementation that builds on existing open protocols—specifically Google's Agent-to-Agent (A2A) protocol and Anthropic's Model Context Protocol (MCP)—to provide a practical, deployable multi-agent system for platform engineering.
Business product or service to project separation
CAIPE originated as an open source initiative within the CNOE (Cloud Native Operational Excellence) community, a CNCF-affiliated forum. While maintainers and contributors from multiple organizations including AWS, Cisco, Splunk, and Demandbase participate, CAIPE is not the upstream version of any commercial product. It operates under its own open governance within the CNOE Agentic AI SIG, with community-elected maintainers from multiple organizations. All development happens in the open on GitHub, and the project's roadmap is driven by community consensus. Contributing organizations may use CAIPE internally or build internal tooling on top of it, but the project itself is community-owned and vendor-neutral.
Cloud native context
Why CNCF?
CAIPE is built for and by the cloud native community. Joining the CNCF would:
- Accelerate adoption: CNCF's neutral governance and brand recognition would attract a broader contributor and adopter base across the platform engineering ecosystem.
- Strengthen interoperability: Being part of the CNCF landscape alongside projects like Argo, Backstage, Kubernetes, and Prometheus would formalize integration patterns and encourage co-development with these projects' communities.
- Solidify community-driven development: CNCF governance provides a stable, vendor-neutral home that formalizes multi-organization maintainership and encourages broader community ownership of the project's direction.
- Advance the ecosystem: Agentic AI applied to platform operations is an emerging area, and the current landscape lacks dedicated, production-quality projects focused on full platform operations—most existing efforts are scoped to individual tools with specific operational functions. CNCF hosting would signal to the industry that unified, AI-assisted platform operations is a serious discipline, and provide a focal point for best practices that span the entire cloud native stack.
The CNOE forum, which champions CAIPE, already operates within the CNCF ecosystem and many CAIPE contributors are active participants in other CNCF projects and TAGs.
Benefit to the landscape
CAIPE benefits the Cloud Native Landscape by:
- Bridging AI and cloud native operations: There is currently no CNCF project that provides a reference architecture for applying multi-agent AI systems to platform engineering workflows. CAIPE fills this gap.
- Unifying tool interaction: Platform teams use many CNCF and adjacent tools (Argo, Kubernetes, Prometheus, Backstage). CAIPE provides a unified conversational and agentic interface across all of its integrated CNCF and adjacent tools, reducing context-switching and operational friction.
- Pioneering protocol-based agent interoperability: By building on A2A and MCP protocols, CAIPE demonstrates how AI agents can be composed in a loosely coupled, cloud native manner—similar to how microservices communicate via gRPC/REST.
- Advance credibility of AI in production: CAIPE serves as a proof point for applying AI to real platform operations, with enterprise security, observability, and deployment patterns built in—demonstrating that agentic AI can be trusted in production cloud native environments.
Cloud native 'fit'
CAIPE is cloud native by design:
- Containerized: Every component (supervisor, sub-agents, UI, RAG services) runs as an independent container, deployable via Docker Compose or Kubernetes.
- Orchestrated: Helm charts provide production-grade Kubernetes deployment with configurable resource limits, HPA, health checks, and rolling updates.
- Microservices architecture: Sub-agents communicate via the A2A protocol over HTTP, enabling independent scaling, deployment, and lifecycle management.
- Stateless compute with external state: Agent state is managed via Redis (persistence) and Milvus (vector store), following cloud native patterns for state externalization.
- Observable: Integrated with OpenTelemetry-compatible tracing (Langfuse), structured logging, and health endpoints.
- Declarative configuration: Agent behavior, personas, prompts, and tool configurations are defined declaratively via common cloud native, GitOps-friendly practices.
- Infrastructure-agnostic: Runs on any Kubernetes cluster (EKS, GKE, AKS, on-prem) or locally via Docker Compose.
Cloud native 'integration'
CAIPE complements and integrates with the following CNCF projects:
| CNCF Project | Integration |
|---|---|
| Kubernetes | Reference deployment target; dedicated Kubernetes agent for cluster operations |
| Argo (ArgoCD) | Dedicated ArgoCD agent for GitOps deployment management |
| Backstage | Agent Forge plugin contributed upstream to backstage/community-plugins for Internal Developer Portal integration |
| Helm | Helm charts for Kubernetes deployment; Helm-based release lifecycle |
| OpenTelemetry | Tracing integration via Langfuse (OTel-compatible); structured telemetry |
| Prometheus/Grafana | Planned integration for metrics-driven agent workflows |
Cloud native overlap
CAIPE is an AI agent orchestration system that defines contextual intent and abstracted workflows, and orchestrates agents and resources to perform operations in service of those workflows. It operates at a layer above individual platform tools—using them through agents rather than replacing them. For example, while Backstage provides a developer portal UI and Argo provides GitOps capabilities, CAIPE complements both by providing an intelligent, conversational interface on top of them. CAIPE can also be integrated directly with Backstage via the Agent Forge plugin.
The closest CNCF project in the agentic AI space is kagent, a sandbox project focused on running AI agents in Kubernetes and providing MCP server tooling (kmcp). CAIPE and kagent are complementary rather than overlapping. kagent provides a Kubernetes-native framework for deploying and running individual agents, while CAIPE operates at a higher layer - defining platform engineering workflows, orchestrating multiple agents across tools, and maintaining contextual knowledge and memory across operations. CAIPE could leverage kagent's Kubernetes runtime and MCP infrastructure as part of its deployment and tool integration layer.
Similar projects
- kagent (CNCF Sandbox): A Kubernetes-native framework for running AI agents and MCP servers. kagent focuses on the runtime and deployment layer for individual agents, while CAIPE is an integrated system that provides multi-agent orchestration, abstracted platform engineering workflows, knowledge systems, and a full application layer (UI, CLI, Backstage plugin)—ready to deploy and use in platform engineering environments.
- LangGraph (LangChain ecosystem): A framework for building agent workflows. CAIPE uses LangGraph as its agent runtime but provides the full platform engineering application layer (agents, tools, deployment, UI) on top of it.
- Coding agents (Claude Code, Cursor etc.): Many coding agents can be configured to perform tasks similar to CAIPE, but they are personal, individual solutions rather than integrated systems designed for team-wide platform engineering operations.
No existing CNCF project provides an integrated multi-agent system that combines workflow orchestration, contextual knowledge, persistent memory, and a full application layer purpose-built for platform engineering operations.
Landscape
CAIPE is not yet listed on the Cloud Native Landscape. We would anticipate placement alongside kagent under the same primary categories (Provisioning and Automation & Configuration) and the additional category CNAI / Agentic AI, as shown on kagent's landscape entry.
CNCF policies
Trademark and accounts
- If the project is accepted, I agree to donate all project trademarks and accounts to the CNCF
IP policy
- If the project is accepted, I agree the project will follow the CNCF IP Policy
Will the project require a license exception?
N/A. CAIPE is licensed under Apache 2.0, which is the standard CNCF license. All dependencies are compatible with the CNCF Allowlist License Policy.
Project "Domain Technical Review"
[To be completed — the project has not yet engaged with a TAG for a formal presentation. We plan to engage with TAG App Delivery and/or TAG Runtime for a Domain Technical Review prior to the sandbox application review.]
Contact information
Application contact email(s)
cnoe-steering@googlegroups.com
Contributing or sponsoring entity signatory information
If an organization:
| Name | Address | Type (e.g., Delaware corporation) | Signatory name and title | Email address |
|---|---|---|---|---|
| Cisco Systems, Inc. | 170 W Tasman Dr, San Jose, CA 95134 | Delaware corporation | Cisco OSPO Legal | oss-legal@cisco.com |
Or, if an individual or individual(s):
| Name | Country | Email address |
|---|---|---|
Signatories for this application (individuals): Hasith Kalpage approves on the business side (Director). Natali Vlatko and Tim Swanson provide additional sign-off from Cisco OSPO. Legal approval: TBD.
| Name | Country | Email address | Title / role |
|---|---|---|---|
| Sri Aradhyula | United States | sraradhy@cisco.com | Project maintainer |
| Hasith Kalpage | United States | haskalpa@cisco.com | Project maintainer; Director (business approval) |
| Natali Vlatko | United States | nvlatko@cisco.com | Cisco OSPO Lead (additional signatory) |
| Tim Swanson | United States | tiswanso@cisco.com | Cisco OSPO Lead (additional signatory) |
Additional information
Maintainers (reference)
| Name | GitHub | Company |
|---|---|---|
| — | @adickinson72 | Demandbase |
| Arthur Drozdov | @artdroz | Cisco Outshift |
| Sri Aradhyula | @sriaradhyula | Cisco Outshift |
| Erik Lutz | @cisco-erilutz | Splunk |
| Carlos Santana | @csantanapr | AWS |
| Niall Thomson | @niallthomson | AWS |
| Hasith Kalpage | @haskalpa | Cisco Outshift |
| Kevin | @kevkantes | — |
| Shubham Bakshi | @subbaksh | Cisco Outshift |
| Sunny Whang | @suwhang-cisco | Cisco Outshift |
CNCF contacts
- The CAIPE project is championed by the CNOE (Cloud Native Operational Excellence) community, which has established relationships within the CNCF ecosystem.
- Several CAIPE contributors are active in CNCF TAGs and working groups.
- Natali Vlatko (Director of Open Source Software Engineering, Cisco OSPO)
- Tim Swanson (Cloud Native & Open Source Advocate, Cisco OSPO)
- Josh Halley (CNAI TOC)
- Ricardo Aravena (CNAI TOC)
- Lin Sun (CNCF TOC)
Additional information
Community engagement and traction:
- 316+ GitHub stars, 46+ forks, 3,055+ commits as of March 2026
- 32 releases with active development cadence (multiple releases per week)
- 77+ Architecture Decision Records documenting project evolution
- Weekly community meetings (CNOE Agentic AI SIG) with participants from multiple organizations
- Active Slack channel (#cnoe-sig-agentic-ai) on CNCF Slack
- Adopters include Outshift by Cisco, Splunk, and Demandbase
- Comprehensive documentation site with getting-started guides, architecture docs, and workshops (CAIPE Labs)
Technical maturity indicators:
- Extensive CI/CD pipeline with 30+ GitHub Actions workflows covering build, test, lint, security scanning, and release automation
- Conventional commits enforcement, automated dependency updates (Dependabot), and code ownership (CODEOWNERS)
- Helm chart with production-ready configuration for multi-node and single-node deployment modes
- Integration test suites for supervisor, multi-agent, and individual agent components
- Security policy with responsible disclosure process and GitHub Security Advisories
Governance:
- Governed by the CNOE Agentic AI SIG: https://github.com/cnoe-io/governance/tree/main/sigs/agentic-ai
- Open governance with community-driven roadmap and decision-making
- DCO (Developer Certificate of Origin) required for all contributions