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The leading GitOps continuous delivery tool for Kubernetes, automatically syncing your cluster state to match what's defined in git.

• DevOps

Progressive delivery operator that automates canary, blue-green, and A/B deployments for Kubernetes with automatic rollback on failure.

• DevOps

GitOps continuous delivery tool for Kubernetes that keeps a cluster's state synchronized with a git repository, a genuine alternative to Argo CD.

• DevOps

The standard package manager for Kubernetes, letting you define, install, and upgrade even complex applications as versioned, reusable charts.

• DevOps

Multi-cloud continuous delivery platform originally built at Netflix for deploying applications reliably across many cloud providers and regions.

• DevOps

Command-line tool that encrypts individual values inside YAML, JSON, and other config files, so secrets can be safely committed to git.

• DevOps

Radically simple IT automation platform for configuration management, deployment and orchestration.

• DevOps

Kubernetes-native platform for serving machine learning models at scale, standardizing model deployment across frameworks.

• AI & Machine Learning

Open source system for automating deployment, scaling and management of containerized applications.

• DevOps

High-performance, S3-compatible object storage system for self-hosted and hybrid cloud deployments.

• Storage

Open-source platform for managing the machine learning lifecycle: experiment tracking, model packaging, versioning, and deployment.

• AI & Machine Learning

Open-source tool for testing and evaluating LLM prompts, comparing outputs across models and catching quality regressions before deployment.

• AI & Machine Learning

Open source machine learning framework that accelerates the path from research prototyping to production deployment.

• AI & Machine Learning

Kubernetes operator that automates running Apache Kafka clusters, handling deployment, configuration, and lifecycle management.

• Backend

Extends Prometheus with long-term storage, global querying across clusters, and high availability for large-scale metrics deployments.

• Monitoring