ark-documentation

Provider-agnostic operations for agentic resources. ARK codifies patterns and practices developed across dozens of agentic application projects.

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최근 업데이트: 4/21/2026

⚒️ ark

Agentic Runtime for Kubernetes

A declarative, Kubernetes-native framework for building portable, scalable, and provider-agnostic agentic applications.


FeaturesQuickstartDocumentation

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What is Ark?

Ark is a declarative toolkit for building and hosting distributed AI agents. By defining what agents should do rather than how they do it, Ark eliminates vendor lock-in and ensures your applications stay adaptable as AI evolves.

Built on Kubernetes, Ark lets you deploy a dev-friendly cluster in minutes or scale agentic workloads across existing infrastructure. Leverage proven patterns for security, monitoring, and RBAC—avoiding bespoke overhead while maintaining a portable, production-ready foundation for your AI projects.

Why Ark?

Ark is designed for rapid, democratic development of agentic systems. The entire stack is built on open-source Kubernetes technology designed for running distributed systems. It can run comfortably on a single developer's machine or be deployed into a Kubernetes cluster across multi-cloud and on-prem environments. Developers and operations teams have full visibility into the entire stack, from the highest to the lowest levels.

Because each workload is a declarative specification of agent behavior rather than proprietary code, teams can re-platform individual use cases onto specialized or proprietary stacks when needed, typically with minimal migration overhead.

Features

  • Declarative Agents — Define agents as Kubernetes custom resources with prompts, tools, and model references
  • Provider Agnostic — Swap between OpenAI, Anthropic, Google, Azure, or local Ollama without code changes
  • Multi-Agent Teams — Orchestrate agents with sequential, graph, selector, or round-robin strategies
  • Tool Integration — Connect agents to HTTP APIs, MCP servers, or other agents as tools
  • Persistent Memory — Maintain conversation context across sessions with pluggable memory backends
  • A2A Protocol — Interoperate with external agent systems via Agent-to-Agent protocol
  • CLI & SDKs — Manage agents from the command line or integrate via Python and TypeScript SDKs

Quickstart

You will need a Kubernetes cluster to install Ark into. You can use Minikube, Kind, Docker Desktop or similar to run a local cluster.

Ensure you have Node.js and Helm installed. Then run the following commands to install Ark:

# Install the 'ark' CLI:
npm install -g @agents-at-scale/ark

# Install Ark:
ark install

# Optionally configure a 'default' model to use for agents:
ark models create default

# Run the dashboard:
ark dashboard

In most cases the default installation options will be sufficient. This will install the Ark dependencies, the controller, the APIs and the dashboard. You can optionally setup a default model that will be the default used by agents. The install command will warn if any required dependencies are missing.

User guides, developer guides, operations guides and API reference documentation is all available at:

https://mckinsey.github.io/agents-at-scale-ark/

To troubleshoot an installation, run ark status.

Credits

The initial design and implementation of Ark was led by Roman Galeev, Dave Kerr, and Chris Madden.