A standardized approach to running AI/ML workloads on Kubernetes
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If you're here to get certified, start at For Vendors. If you're here to help shape the program, jump to For Contributors.
The Kubernetes AI Conformance Program defines the capabilities a Kubernetes platform needs to reliably run AI and machine learning workloads. The goal is simple: if your AI application works on one conformant platform, it should work on others too—with fewer "it works on my cluster" surprises.
AI/ML workloads tend to stress clusters in unique ways (accelerators, bursty traffic, and strict isolation). Today, those capabilities vary across platforms. This program aims to:
- Make AI/ML workloads more portable across Kubernetes platforms
- Reduce platform-specific workarounds and "it works on my cluster" surprises
- Give the AI tooling ecosystem a clear baseline to build and test against
We're focusing on the most common AI/ML use cases:
- Training - Distributed or large training jobs that need accelerators and predictable scheduling
- Inference - Model/LLM serving where latency, routing, and scaling matter
- Agentic workloads - Multi-step workflows that combine tools, memory, and long-running tasks
If you provide a Kubernetes platform and want to get certified, here's what you need to know.
Most submissions are a completed checklist plus links to public evidence—think of it as a structured, reviewable self-assessment.
Before you start: Your platform must already be Kubernetes Conformant. AI conformance builds on top of base Kubernetes conformance.
- Prepare - Review the certification requirements and make sure your platform meets them
- Document - Fill out the conformance checklist and gather evidence (documentation, test results, etc.)
- Submit - Create a pull request with your submission to the https://github.com/cncf/k8s-ai-conformance repo.
- Review - CNCF reviews your submission (typically takes up to 10 business days)
- A completed conformance checklist (YAML file)
- Public documentation showing how your platform meets each requirement
- Your product logo in vector format (SVG, EPS, or AI)
- Proof of Kubernetes conformance
Note: Today, certification is based on self-assessment. Automated conformance tests are planned for 2026.
For detailed instructions on what to include, see instructions.md.
The program is a community-led effort to establish a vendor-neutral baseline for AI portability. We welcome participation from all stakeholders, including end users, to ensure the standard remains independent and effective.
| Area | What you can do |
|---|---|
| Documentation | Help improve guides, add examples, fix typos, clarify confusing parts |
| Research | Identify requirements for new AI workload types (especially agentic workloads) |
| Testing | Help develop automated conformance tests |
| Discussion | Participate in working group meetings and design discussions |
- Open an issue — have an idea, question, or suggestion? Start here
- Join the WG AI Conformance working group
- Check out the planning document to see what's in progress
flowchart TD
A[Platform must be Kubernetes Conformant] --> B[Complete self-assessment checklist]
B --> C[Gather evidence and documentation]
C --> D[Submit pull request]
D --> E[CNCF reviews submission]
E -->|Approved| F[Certified for 1 year]
E -->|Needs changes| B
Important notes:
- Certifications are valid for one year and must be renewed
- Certification is per-product and per-configuration (e.g., cloud vs air-gapped)
- The conformance requirements are aligned with Kubernetes release cycles
Platforms need to demonstrate capabilities across several areas: accelerators, networking, scheduling, observability, security, and operator support. The specifics evolve with each Kubernetes release.
For the full and up-to-date requirements, see the conformance versions in the WG repo.
- FAQ - Common questions about the program
- Instructions - How to prepare and submit your conformance results
- Terms & Conditions - Legal requirements for certification
Pick the one that matches your Kubernetes version:
- Kubernetes Conformance - Base Kubernetes certification (required first)
- Conformance Tests - Kubernetes test suite
- Verify Conformance Bot - Automation coming soon
The WG AI Conformance working group governs this program and defines the conformance requirements.
- Meetings: Check the community calendar in the working group repo
- Contact: wg-ai-conformance@kubernetes.io
See all certified platforms in the version directories:
- Read the FAQ first
- Ask questions in the working group
- Open an issue
- Email conformance@cncf.io
For private review of unreleased products, contact conformance@cncf.io directly.
Apache License 2.0 - see LICENSE for details.