Results for "kubernetes"

Infrastructure automation tools for building GPU clusters with Kubernetes and Slurm. Deploys multi-node GPU clusters with monitoring, logging, and storage for AI/HPC workloads. BSD-3-Clause licensed.

Kubernetes-native production stack for vLLM inference. Automated deployment, autoscaling, and monitoring for enterprise-grade LLM serving. Built by the vLLM team for seamless integration.

Kubernetes-native AutoML for hyperparameter tuning, early stopping, and neural architecture search. Framework-agnostic with support for TensorFlow, PyTorch, XGBoost, and custom training operators. Apache 2.0 licensed.

Machine Learning Pipelines for Kubeflow. Platform for building and deploying portable, scalable ML workflows using Kubernetes and Argo. Apache 2.0 licensed.

Kubernetes-native job queueing system for batch, HPC, AI/ML, and similar applications. Cloud-native job queueing with resource flavor fungibility, fair sharing, cohorts, and preemption policies. Integrates with Kubeflow, Ray, and JobSet. Apache 2.0 licensed.

Kubernetes resource scheduler for batch, data, and ML workloads. Provides hierarchical resource queues, multi-tenancy fairness, and gang scheduling for big data and machine learning applications. Apache 2.0 licensed.

Cloud-native batch scheduling system for compute-intensive workloads. CNCF incubating project with gang scheduling, job dependency management, and topology-aware scheduling for AI/ML and deep learning. Apache 2.0 licensed.

CNCF graduated container-native workflow engine for orchestrating parallel jobs on Kubernetes. Powers Kubeflow Pipelines and widely used for ML/data processing at scale. Apache 2.0 licensed.

Kubernetes-native ML/LLM platform.

Cost-efficient and pluggable infrastructure components for GenAI inference. Kubernetes-native control plane for vLLM with distributed KV cache, heterogeneous GPU serving, and intelligent routing. Apache 2.0 licensed.

Kubernetes-based model serving.

Kubernetes-native GPU scheduler for AI workloads at large scale. Originally developed by Run:ai, now open-sourced by NVIDIA. Optimizes GPU resource allocation with dynamic allocation and efficient queue management. Apache 2.0 licensed.

Heterogeneous GPU Sharing on Kubernetes. CNCF sandbox project providing GPU virtualization, slicing, and scheduling for efficient AI workload management across heterogeneous accelerators (GPUs, NPUs, MLUs). Apache 2.0 licensed.

Kubernetes-native execution runtime for high-density, stateful AI-agent sandboxes with actor lifecycle management, suspend/resume, and workload routing. Apache-2.0 licensed.

Manages unified access to generative AI services built on Envoy Gateway. Kubernetes-native AI gateway for routing, load balancing, and managing LLM traffic with enterprise-grade reliability. Apache 2.0 licensed.

AI-powered multi-cluster Kubernetes dashboard with GPU workload monitoring, AI pipeline observability, and CNCF ecosystem integrations. Apache 2.0 licensed.

MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle. Reproducible and scalable machine learning workflows on Kubernetes with experiment tracking, model management, and pipeline orchestration. Apache 2.0 licensed.

Run, manage, and scale AI workloads on any AI infrastructure. Unified interface to access and manage compute across Kubernetes, Slurm, and 20+ cloud providers. Used by Shopify and research institutions for training and inference. Apache 2.0 licensed.

Kubernetes operator for LLM serving with GPU scheduling and model lifecycle management across vLLM, SGLang, and TensorRT-LLM.

Next-generation proxy and routing layer for AI agents and MCP servers, with Kubernetes-native transport, protocol interoperability, and service-mesh-style isolation for reliable agent infrastructure. Apache 2.0 licensed.

Highly scalable distributed vector search engine. Cloud-native architecture with automatic indexing, horizontal scaling, and multiple ANN algorithm support. Apache 2.0 licensed.

Kubernetes-native distributed LLM inference framework. Donated to CNCF by RedHat, Google, and IBM. Intelligent scheduling, KV-cache optimization, and state-of-the-art performance across accelerators.

Declarative, high-throughput agent orchestration runtime for sandboxed agent workloads at cluster scale. Apache 2.0 licensed.

Vendor-agnostic orchestration for training, inference and agentic workloads across NVIDIA, AMD, TPU, and Tenstorrent on clouds, Kubernetes, and bare metal. MPL-2.0 licensed.