{"data":{"slug":"kserve-kserve","name":"kserve","tagline":"Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes","github_url":"https://github.com/kserve/kserve","owner":"kserve","repo":"kserve","owner_avatar_url":"https://avatars.githubusercontent.com/u/83512434?v=4","primary_language":"Go","stars":5970,"forks":1689,"topics":["artificial-intelligence","cncf","genai","hacktoberfest","istio","k8s","knative","kserve","kubeflow","kubernetes","llm-inference","machine-learning","mlops","model-interpretability","model-serving","pytorch","service-mesh","tensorflow","vllm","xgboost"],"archived":false,"github_pushed_at":"2026-09-19T13:08:33+00:00","maintenance_label":"Very active","stars_delta_30d":239,"url":"https://www.graphcanon.com/tools/kserve-kserve","markdown_url":"https://www.graphcanon.com/tools/kserve-kserve.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/kserve-kserve","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=kserve-kserve","description":"Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes","homepage_url":"https://kserve.github.io/website/","license":"Apache-2.0","open_issues":204,"watchers":70,"ai_summary":"kserve/kserve provides a scalable inference platform for deploying generative and predictive models across multiple frameworks using Kubernetes.","readme_excerpt":"### :hammer_and_wrench: Installation\n\n#### Standalone Installation\n- **[Standard Kubernetes Installation](https://kserve.github.io/website/docs/admin-guide/overview#raw-kubernetes-deployment)**: Compared to Serverless Installation, this is a more **lightweight** installation. However, this option does not support canary deployment and request based autoscaling with scale-to-zero.\n- **[Knative Installation](https://kserve.github.io/website/docs/admin-guide/overview#serverless-deployment)**: KServe by default installs Knative for **serverless deployment** for InferenceService.\n- **[ModelMesh Installation](https://kserve.github.io/website/docs/admin-guide/overview#modelmesh-deployment)**: You can optionally install ModelMesh to enable **high-scale**, **high-density** and **frequently-changing model serving** use cases. \n- **[Quick Installation](https://kserve.github.io/website/docs/getting-started/quickstart-guide)**: Install KServe on your local machine.\n\n#### Kubeflow Installation\nKServe is an important addon component of Kubeflow, please learn more from the [Kubeflow KServe documentation](https://www.kubeflow.org/docs/external-add-ons/kserve/kserve). Check out the following guides for running [on AWS](https://awslabs.github.io/kubeflow-manifests/main/docs/component-guides/kserve) or [on OpenShift Container Platform](https://github.com/kserve/kserve/blob/master/docs/OPENSHIFT_GUIDE.md).","github_created_at":"2019-03-27T21:14:14+00:00","created_at":"2026-07-11T11:42:35.779076+00:00","updated_at":"2026-09-20T06:32:42.980076+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":"artificial-intelligence","name":"artificial-intelligence"},{"slug":"cncf","name":"cncf"},{"slug":"genai","name":"genai"},{"slug":"hacktoberfest","name":"hacktoberfest"},{"slug":"istio","name":"istio"},{"slug":"k8s","name":"k8s"},{"slug":"knative","name":"knative"},{"slug":"kserve","name":"kserve"}],"trust":{"provenance":{"is_fork":false,"github_id":178075572,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-19T18:29:35.749Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":5,"days_since_push":0,"last_release_at":"2026-09-10T17:44:50Z","stars_delta_30d":239,"open_issues_delta_30d":-101},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:42:36.926Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-19T18:29:36.789Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-09-19T18:29:36.789Z","managed_saas":false},"languages":{"value":["go"],"source":"github.language","observed_at":"2026-09-19T18:29:36.789Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-09-19T18:29:36.789Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-09-19T18:29:36.789Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["Requires a Kubernetes cluster to run."],"min_ram_gb":null,"requires_docker":true},"constraints":{"min_ram_gb":null,"requires_docker":true},"when_to_use":["When you need a standardized and scalable way to deploy generative and predictive models across multiple frameworks.","If your existing infrastructure is built around Kubernetes, as kserve/kserve is tightly integrated with it for efficient deployment.","For scenarios where you require support for machine learning model inference that spans various popular frameworks like TensorFlow, PyTorch, and XGBoost."],"when_not_to_use":["When your team or organization lacks expertise in Kubernetes, as effective use of kserve/kserve requires familiarity with Kubernetes operations.","If the deployment environment is not compatible with Kubernetes. KServe's architecture relies on the Kubernetes ecosystem for orchestrating model deployments.","In situations where support for specific specialized frameworks not covered by kserve (such as certain niche deep learning libraries) is needed."],"source":"enrich:decision_facts","observed_at":"2026-07-12T18:46:05.935Z"},"constraint_facets":{"min_ram_gb":null,"requires_docker":true},"decision_summary":[{"label":"Requirements","value":"Requires Docker; Requires a Kubernetes cluster to run."}]}}