Letter A Journey
Exploring essential CNCF projects for letter A. Check out the current letter (U).
Ai Agent Agent Framework
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
Key Features
- • Provides building blocks for AI agents
- • Scalable management of agent lifecycles
Build, run, manage agentic software at scale
Key Features
- • Production API with over 50 endpoints, SSE, and websockets.
- • Built-in storage for sessions, memory, knowledge, and traces.
Ai Agent Evaluation
A generative AI-powered framework for testing virtual agents
Key Features
- • Built-in support for popular AWS services like Amazon Bedrock, Amazon Q Business, and Amazon SageMaker
- • Orchestrate concurrent, multi-turn conversations with your agent while evaluating its responses
Ai Agent Knowledge Graph
Graph database optimized for fast analysis and real-time data processing. It is provided as an extension to PostgreSQL.
Key Features
- • Provides graph database functionality as a PostgreSQL extension.
- • Read and write graph data in nodes and edges within an existing relational database.
Ai Agent Protocol
Agent2Agent (A2A) is an open protocol enabling communication and interoperability between opaque agentic applications.
Key Features
- • Standardized Communication: Defines standard message formats and protocols for AI agents to communicate and coordinate tasks.
- • Interoperability: Enables agents built on different frameworks or by different organizations to interact seamlessly.
Ai Agent Workflow Orchestration
Enterprise-grade, commercial-friendly agentic workflow platform for building next-generation SuperAgents with multi-agent orchestration capabilities.
Key Features
- • AI workflow orchestration and model management
- • AI and MCP tool integration
Ai Native Infra Gateway
Next Generation Agentic Proxy for AI Agents and MCP servers
Key Features
- • LLM Gateway: Route traffic to major LLM providers through a unified OpenAI-compatible API with budget controls, load balancing, and failover.
- • MCP Gateway: Connect LLMs to tools and external data sources via MCP with tool federation, OpenAPI integration, and OAuth authentication.
App Definition and Development Application Definition Image Build
Artifact Hub is a web-based application that enables finding, installing, and publishing packages and configurations for CNCF projects
Key Features
- • Discover, install, and publish packages and configurations
- • Explore content like Helm chart schemas and templates interactively
App Definition and Development Continuous Integration Delivery
Kubernetes-native tools to run workflows, manage clusters, and do GitOps right.
Key Features
- • Argo CD: Declarative GitOps continuous delivery keeping cluster state in sync with Git.
- • Argo Workflows: Kubernetes-native workflow engine for parallel compute and ML DAGs.
Open Source CI/CD platform with advanced features and architecture. Powerful, reproducible and containerized workflows (called Runs), git based workflow (integrates with all the primary git repositories like GitHub, GitLab, Gitea), restart Runs from failed tasks, user direct runs (test your local changes to a remote Agola server with just one command), distributed and high available by design and runs everywhere (Kubernetes, docker, IaaS, bare metal).
Key Features
- • Container-native workflow execution in Kubernetes pods.
- • User-driven pipelines configured via YAML manifests.
App Definition and Development Database
An indexed columnar data format for fast analytics on big data platforms, optimized for multi-dimensional point lookups and aggregations.
Key Features
- • Multi-level indexing (min/max, inverted index, B-tree) for rapid point queries.
- • Columnar storage with advanced encoding and compression.
A foundational open-source framework that allows for the distributed processing and storage of large data sets across clusters of computers.
Key Features
- • HDFS (Hadoop Distributed File System) for fault-tolerant distributed storage.
- • YARN for cluster resource negotiation and workload scheduling.
A distributed in-memory database, caching layer, and computation platform designed to accelerate transactional and analytical workloads.
Key Features
- • In-memory data grid and distributed cache with ANSI-99 SQL support.
- • ACID-compliant distributed transactions across memory and disk tiers.
A native multi-model database system supporting graph, document, and key-value data models with a unified declarative query language (AQL).
Key Features
- • Unified multi-model engine allowing graph traversals, document queries, and search.
- • ArangoDB Query Language (AQL) providing declarative syntax for joins and graph traversals.
App Definition and Development Streaming Messaging
An easy-to-use, powerful, and reliable system to process, transform, and distribute data across distributed enterprise systems.
Key Features
- • Web-based visual canvas for designing and monitoring real-time dataflows.
- • Complete data provenance tracking every transformation of every FlowFile.
A distributed messaging and streaming data platform offering low latency, high throughput, high reliability, and ultra-large capacity.
Key Features
- • Strict message ordering and transactional message guarantees.
- • Massive topic scalability supporting tens of thousands of topics per cluster.
A unified multi-language engine for executing large-scale data engineering, data science, and machine learning on single-node machines or clusters.
Key Features
- • In-memory distributed computing delivering up to 100x speed over MapReduce.
- • Unified APIs in Python (PySpark), SQL, Scala, Java, and R.
A distributed, real-time computation system for processing unbounded streams of data reliably with high speed and low latency.
Key Features
- • Real-time stream abstraction with Spouts and Bolts in Topologies.
- • Guaranteed message processing semantics (at-least-once or Trident exactly-once).
A self-service Industrial IoT (IIoT) and streaming analytics platform designed to enable non-technical users to connect, analyze, and explore IoT data streams.
Key Features
- • Drag-and-drop web pipeline editor for building stream workflows without coding.
- • Pre-built library of pipeline elements (adapters, processors, sinks).
Apicurio Registry is an open-source registry for API and schema artifacts (OpenAPI, AsyncAPI, Avro, Protobuf, JSON Schema, GraphQL and more) and AI agent artifacts (A2A Agent Cards, MCP tool definitions, prompt templates, model schemas), with immutable versioning, validity and compatibility rules, role-based access control, and standards-based discovery through AI Catalog and ARD well-known endpoints.
Key Features
- • Comprehensive format support: OpenAPI, AsyncAPI, Avro, Protobuf, JSON Schema, GraphQL.
- • Schema validation and compatibility rules preventing breaking changes in event streams.
High-performance Rust stream processing engine, providing powerful data stream processing capabilities, supporting multiple input/output sources and processors.
Key Features
- • Blazing fast stream processing built with Rust and Tokio for memory safety and low latency.
- • Declarative stream pipeline definitions and modular event filters.
AutoMQ is a cloud-native fork of Kafka by separating storage to S3. 10x cost-effective. Autoscale in seconds. Single-digit ms latency.
Key Features
- • Stateless broker architecture leveraging object storage (S3) instead of local disk storage.
- • 100% Apache Kafka® compatible (retention of Kafka API, protocol, and ecosystem).
Cnai Automl
Cnai Ci Cd Delivery
Cnai Data Architecture
Data orchestration for analytics and machine learning in the cloud.
Key Features
- • Memory-speed distributed caching across storage tiers (RAM, NVMe, SSD).
- • Unified namespace aggregating AWS S3, HDFS, GCS, and Ceph.
A high performance real-time analytics database.
Key Features
- • Sub-second query response times for multi-dimensional filtering and grouping.
- • Native real-time streaming ingestion from Kafka and Kinesis.
Open source stream processing framework with powerful stream- and batch-processing capabilities.
Key Features
- • Event-driven stream processing with exactly-once state consistency guarantees.
- • Sub-millisecond latency with RocksDB state backend.
Open source, distributed, versioned, column-oriented store modeled after Google' Bigtable.
Key Features
- • Linear horizontal scalability across commodity servers.
- • Strictly consistent read and write operations at scale.
A realtime distributed OLAP datastore.
Key Features
- • Ultra-low latency SQL queries (sub-50ms) over billions of rows.
- • Pluggable indexing (inverted, star-tree, range, text, JSON, geospatial).
A unified analytics engine for large-scale data processing.
Key Features
- • In-memory distributed computing delivering up to 100x speed over MapReduce.
- • Unified APIs in Python (PySpark), SQL, Scala, Java, and R.
Cnai Data Science
Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.
Key Features
- • Multi-language backend interpreter supporting Spark, SQL, Python, Scala, Shell, JDBC.
- • Built-in data visualizations and pivot charts without front-end code.
Cnai Distributed Training
Cnai General Orchestration
Cnai Governance Policy Security
Cnai Ml Serving
Cost-efficient and pluggable Infrastructure components for GenAI inference.
Key Features
- • High-Density LoRA Management: Streamlined support for lightweight, low-rank adaptations of models.
- • LLM Gateway and Routing: Efficiently manage and direct traffic across multiple models and replicas.
Arks is an end-to-end framework for managing LLM-based applications within Kubernetes cluster. It provides a robust and extensible infrastructure tailored for deploying, orchestrating, and scaling LLM inference workloads in cloud-native environments.
Key Features
- • Kubernetes-native orchestration for large language models and multi-agent workflows.
- • Optimized inference scheduling, batching, and GPU resource management.
Cnai Model Llm Observability
Cnai Open Enterprise Ai Blueprints
Cnai Vector Databases
Cnai Workload Observability
Cncf Members Academic
Cncf Members End User Supporter and Contributor
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Data Data Architecture
A high performance real-time analytics database.
Key Features
- • Sub-second query response times for multi-dimensional filtering and grouping.
- • Native real-time streaming ingestion from Kafka and Kinesis.
Open source stream processing framework with powerful stream- and batch-processing capabilities.
Key Features
- • Event-driven stream processing with exactly-once state consistency guarantees.
- • Sub-millisecond latency with RocksDB state backend.
Open source, distributed, versioned, column-oriented store modeled after Google's Bigtable.
Key Features
- • Linear horizontal scalability across commodity servers.
- • Strictly consistent read and write operations at scale.
A realtime distributed OLAP datastore.
Key Features
- • Ultra-low latency SQL queries (sub-50ms) over billions of rows.
- • Pluggable indexing (inverted, star-tree, range, text, JSON, geospatial).
Data Data Science
Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.
Key Features
- • Multi-language backend interpreter supporting Spark, SQL, Python, Scala, Shell, JDBC.
- • Built-in data visualizations and pivot charts without front-end code.
Inference Framework
Cost-efficient and pluggable Infrastructure components for GenAI inference.
Key Features
- • High-Density LoRA Management: Streamlined support for lightweight, low-rank adaptations of models.
- • LLM Gateway and Routing: Efficiently manage and direct traffic across multiple models and replicas.
Arks is an end-to-end framework for managing LLM-based applications within Kubernetes cluster. It provides a robust and extensible infrastructure tailored for deploying, orchestrating, and scaling LLM inference workloads in cloud-native environments.
Key Features
- • Kubernetes-native orchestration for large language models and multi-agent workflows.
- • Optimized inference scheduling, batching, and GPU resource management.
Observability and Analysis Chaos Engineering
Observability and Analysis Continuous Optimization
Observability and Analysis Feature Flagging
Observability and Analysis Observability
Anteon is a platform that combines effortless Kubernetes Monitoring and Performance Testing to provide seamless observability of your K8S infrastructure using eBPF.
Key Features
- • eBPF-powered non-intrusive network and application monitoring for Kubernetes.
- • Distributed load testing engine simulating realistic user traffic.
Orchestration Management Api Gateway
APIOAK is a distributed API gateway based on OpenResty. It provides full lifecycle management of APIs including dynamic routing, load balancing, authentication, rate limiting, and analytics.
Key Features
- • Distributed architecture based on OpenResty
- • Full API lifecycle management
Apache APISIX is a dynamic, real-time, high-performance API Gateway. It provides rich traffic management features such as load balancing, dynamic upstream, canary release, circuit breaking, authentication, observability, and more.
Key Features
- • Dynamic and real-time configuration without restarts
- • Support for HTTP, TCP, UDP, gRPC, and MQTT proxy
Azure API Management is a hybrid, multi-cloud API, full lifecycle management platform for APIs across all environments. It allows customers to self-host API gateways as containers on Kubernetes.
Key Features
- • Provides full lifecycle management platform for APIs.
- • Allows customers to self-host API gateways as containers on Kubernetes.
Orchestration Management Coordination Service Discovery
A centralized service for maintaining configuration information, naming, providing distributed synchronization, and group services across distributed systems.
Key Features
- • Hierarchical key-value namespace structured like a filesystem (znodes).
- • Zab (ZooKeeper Atomic Broadcast) consensus ensuring sequential consistency.
Orchestration Management Remote Procedure Call
A lightweight, cross-language remote procedure call (RPC) framework with a powerful code generation engine for building scalable distributed services.
Key Features
- • Interface Definition Language (IDL) defining types and services in `.thrift` files.
- • Code generation across dozens of languages (C++, Java, Python, Go, Rust, Ruby, C#).
An industrial-grade, high-performance RPC framework built in C++ and used extensively in mission-critical, latency-sensitive distributed services.
Key Features
- • Ultra-high performance with lock-free concurrency (bthread M:N user-space threading).
- • Multi-protocol support: Baidu-std, gRPC, HTTP/HTTPS, Redis, Memcached, Thrift.
Orchestration Management Scheduling Orchestration
A secure-by-default agent execution runtime for running millions of sandboxes.
Agones is a library for hosting, running, and scaling dedicated game servers on Kubernetes.
Key Features
- • Define a single GameServer, and/or large game server Fleets within Kubernetes - either through yaml or via the API
- • Manage GameServer lifecycles - including health checking and connection information
A distributed systems kernel that abstracts compute resources across clusters to enable efficient resource sharing among diverse frameworks.
Key Features
- • Two-level resource offer mechanism allowing frameworks to negotiate resources.
- • Scalability to tens of thousands of nodes and hundreds of thousands of tasks.
Armada is a multi-Kubernetes cluster batch job scheduler
Key Features
- • Multi-cluster orchestration to schedule jobs across many Kubernetes clusters seamlessly
- • High-throughput queueing capable of handling millions of queued jobs
A distributed systems platform that makes it easy to package, deploy, and manage scalable and reliable microservices and containers.
Key Features
- • Microservices and container orchestration
- • State management
Orchestration Management Service Mesh
Aeraki Mesh allows you to manage any layer-7 traffic in a service mesh
Key Features
- • Extends Istio to support various layer-7 protocols like Dubbo, Thrift, Kafka, Redis.
- • Uses MetaProtocol Proxy for unified traffic management.
Orchestration Management Service Proxy
Platform Certified Kubernetes Ai Platform
Platform Certified Kubernetes Distribution
Amazon Elastic Kubernetes Service Distro (Amazon EKS-D) is a Kubernetes distribution based on and used by Amazon Elastic Kubernetes Service (EKS) to create reliable and secure Kubernetes clusters.
Platform Certified Kubernetes Hosted
Platform Certified Kubernetes Installer
Amazon EKS Anywhere is a new deployment option for Amazon EKS that allows customers to create and operate Kubernetes clusters on customer-managed infrastructure, supported by AWS.
Platform Paas Container Service
A toolkit and runtime for building concurrent, distributed, resilient, and message-driven applications using the Actor model on the JVM.
Key Features
- • Actor-based concurrency eliminating explicit locking.
- • Akka Cluster for decentralized node discovery and state management.
Application Platform for Linode Kubernetes Engine (LKE)
Key Features
- • Turnkey developer platform layer sitting on top of Linode Kubernetes Engine.
- • Integrated CI/CD workflows and automated container deployment pipelines.
Provisioning Automation Configuration
A collection of loosely coupled, declarative open-source tools for automating cloud provisioning and lifecycle management using Kubernetes and YAML.
Key Features
- • Declarative infrastructure management driven by Kubernetes CRDs.
- • Unified lifecycle automation for bare metal, VMs, and control planes.
A Kubernetes Resource Interface for the Edge
Key Features
- • Automated discovery of IoT edge devices (ONVIF, udev, OPC UA, etc.)
- • Exposes devices as Kubernetes Custom Resources (CRDs)
An agentless open-source automation engine for configuration management, cloud provisioning, application deployment, and infrastructure orchestration.
Key Features
- • Agentless architecture communicating over standard SSH or WinRM.
- • Human-readable YAML playbooks defining declarative desired state.
Apollo is a reliable open-source configuration management system
Key Features
- • Real-time configuration synchronization pushing updates to clients within 1 second.
- • Multi-environment (DEV, FAT, UAT, PROD) and multi-cluster management UI.
Provisioning Container Registry
Provisioning Key Management
Open source platform for X.509 certificate based service authentication and fine grained access control in dynamic infrastructures
Key Features
- • X.509 Certificate Based Authentication
- • Fine-grained Authorization (RBAC with JWT)
Provisioning Security Compliance
APIClarity is a cloud API observability open-source project that provides functionality to discover and monitor any API traffic that interacts with modern applications and report suspected security weaknesses or possible abuses. Once an OpenAPI spec is either uploaded or reconstructed by APIClarity, it monitors for shadow and zombie APIs, Broken Functional-Level Authorization (BFLA), Broken Object-Level Authorization (BOLA), weak authentication, sensitive data leaks and data injection risks.
Key Features
- • OpenAPI automatic reconstruction based on observed API traffic
- • Spec Diffs module to identify Shadow APIs, Zombie APIs, and specification deviations
Runtime Cloud Native Network
Runtime Cloud Native Storage
An open-source data orchestration layer that bridges analytical and AI compute frameworks with distributed and cloud storage systems.
Key Features
- • Memory-speed distributed caching across storage tiers (RAM, NVMe, SSD).
- • Unified namespace aggregating AWS S3, HDFS, GCS, and Ceph.
Runtime Container Runtime
Serverless Framework
A simple, declarative open-source framework for building serverless applications on AWS with fast local development and plain text architecture manifests.
Key Features
- • Concise `app.arc` manifest defining HTTP routes, scheduled jobs, queues, and tables in plain text.
- • Fast local development sandbox simulating API Gateway, Lambda, and DynamoDB without Docker.
Serverless Hosted Platform
Develop more efficiently with Functions, an event-driven serverless compute platform that can also solve complex orchestration problems. Build and debug locally without additional setup, deploy and operate at scale in the cloud, and integrate services using triggers and bindings.
Key Features
- • Serverless architecture
- • Event-driven programming model
Serverless Installable Platform
A lightweight, serverless cloud-native integration framework built on Apache Camel, designed to run integrations directly on Kubernetes and OpenShift.
Key Features
- • Sub-second deployment of Enterprise Integration Patterns (EIPs) on Kubernetes.
- • Serverless integration powered by Knative scaling down to zero.
An open-source serverless platform built on Kubernetes and Apache OpenWhisk designed to simplify serverless computing across multi-cloud environments.
Key Features
- • Turnkey deployment of serverless execution on any Kubernetes cluster.
- • Integrated API gateway, cron scheduling, and web asset hosting.
An open-source, distributed serverless cloud platform that executes code in response to events at any scale.
Key Features
- • Event-driven architecture with Triggers, Rules, and Actions model.
- • Polyglot containerized function execution across major languages.
An open-source cloud computing platform that automatically executes and scales Google App Engine (GAE) applications on any public, private, or hybrid cloud.
Key Features
- • Full API emulation of Google App Engine services (Datastore, Memcache, Task Queue, Blobstore).
- • Polyglot application support for Python, Java, Go, and PHP.
Serverless Security
Serverless Tools
Special Certified Cnfs
Special Kubernetes and Cloud Native Training Partner
Special Kubernetes Certified Service Provider
Training Post Training
Go ahead and axolotl questions
Key Features
- • Multiple Model Support: Train various models like GPT-OSS, LLaMA, Mistral, Mixtral, Pythia, and many more models available on the Hugging Face Hub.
- • Multimodal Training: Fine-tune vision-language models (VLMs) and audio models.
Wasm Ai Machine Learning
An open-source machine learning compiler framework for CPUs, GPUs, and specialized hardware accelerators.
Key Features
- • Automated compilation from PyTorch, TensorFlow, ONNX, and Keras.
- • End-to-end compilation lowering computation graphs to hardware machine code.
Wasm Application Frameworks
An open-source, multiplayer game and simulation runtime built in Rust, leveraging WebGPU and WebAssembly for native multi-platform execution.
Key Features
- • First-class multiplayer networking with client/server synchronization.
- • WebAssembly (WASM) guest module system in Rust.
Wasm Debugging Observability
Wasm Decentralized Platforms
Wasm Edge Bare Metal
Wasm Embedded Functions
Wasm Hosted Platforms
Wasm Languages
Wasm Orchestration Management
Wasm Packaging Registries Application Delivery
Wasm Runtimes
Wasm Tooling
A JavaScript wrapper intended to be used with the Asyncify feature of Binaryen. Together, they allow the use of asynchronous APIs (such as most Web APIs) from within WebAssembly written and compiled from any source language.
Key Features
- • JavaScript wrapper for Binaryen's Asyncify feature.
- • Enables using asynchronous APIs (like most Web APIs) within WebAssembly.