{"data":{"slug":"ome-projects-ome","name":"ome","tagline":"Kubernetes operator for LLM serving and management","github_url":"https://github.com/ome-projects/ome","owner":"ome-projects","repo":"ome","owner_avatar_url":"https://avatars.githubusercontent.com/u/276942073?v=4","primary_language":"Go","stars":509,"forks":97,"topics":["deepseek","k8s","kimi-k2","llama","llm","llm-inference","model-as-a-service","model-serving","multi-node-kubernetes","oracle-cloud","pd-disaggregation","qwen","sglang","vllm"],"archived":false,"github_pushed_at":"2026-09-20T03:41:04+00:00","maintenance_label":"Very active","stars_delta_30d":27,"url":"https://www.graphcanon.com/tools/ome-projects-ome","markdown_url":"https://www.graphcanon.com/tools/ome-projects-ome.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/ome-projects-ome","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=ome-projects-ome","description":"Open Model Engine (OME) — Kubernetes operator for LLM serving, GPU scheduling, and model lifecycle management. Works with SGLang, vLLM, TensorRT-LLM, and Triton","homepage_url":"http://ome-projects.github.io/ome/","license":"Apache-2.0","open_issues":141,"watchers":13,"ai_summary":"OME is designed to handle LLM serving, GPU scheduling, and model lifecycle management through Kubernetes operations.","readme_excerpt":"## Installation\n\n**Requires Kubernetes 1.28 or newer**\n\n---\n\n# Install OME CRDs\nhelm upgrade --install ome-crd oci://ghcr.io/moirai-internal/charts/ome-crd --namespace ome --create-namespace\n\n---\n\n# Install OME resources\nhelm upgrade --install ome oci://ghcr.io/moirai-internal/charts/ome-resources --namespace ome\n```\n\n---\n\n### Option 2: Install from Source\n\nFor development or customization:\n\n```bash\n\n---\n\n# Install from local charts\nhelm install ome-crd charts/ome-crd --namespace ome --create-namespace\nhelm install ome charts/ome-resources --namespace ome\n```\n\n---\n\n## License\n\nOME is licensed under the [Apache License 2.0](LICENSE).","github_created_at":"2025-05-19T19:30:46+00:00","created_at":"2026-07-11T11:45:54.879029+00:00","updated_at":"2026-09-20T06:35:57.866822+00:00","categories":[{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"}],"tags":[{"slug":"gpu-scheduling","name":"gpu-scheduling"},{"slug":"kubernetes-operator","name":"kubernetes-operator"},{"slug":"llm-inference","name":"llm-inference"},{"slug":"model-serving","name":"model-serving"},{"slug":"multi-node-kubernetes","name":"multi-node-kubernetes"}],"trust":{"provenance":{"is_fork":false,"github_id":986553289,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T03:45:22.814Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":5,"days_since_push":0,"last_release_at":"2026-08-05T17:48:00Z","stars_delta_30d":27,"open_issues_delta_30d":20},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:45:56.131Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T03:45:23.863Z"},"languages":{"value":["go"],"source":"github.language","observed_at":"2026-09-20T03:45:23.863Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-09-20T03:45:23.863Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["If you need robust GPU scheduling alongside LLM serving","For enterprises that wish to streamline the deployment of models like Qwen on Kubernetes"],"when_not_to_use":["In environments where a language other than Go for the operator's implementation is preferred","When your infrastructure does not support or utilize Kubernetes for orchestration purposes"],"source":"enrich:decision_facts","observed_at":"2026-07-16T19:40:41.722Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"OME is a Kubernetes operator tailored for LLM serving and management, focusing on tasks such as GPU scheduling and model lifecycle control, compatible with SGLang, vLLM, TensorRT-LLM, and Triton."}]}}