🚀 Build a ☸️ Kubernetes ☸️ SRE Agent in Just Ten Minutes! ⏱️⚡

#agentup #kubernetes #ai #devops

Hey dev.to community! Have you ever wished you could automate more of your Kubernetes operational tasks, freeing up valuable SRE time? I made a video recently on "Building an AgentUp Kubernetes Agent in only Ten Minutes," demonstrates how to do just that with incredible speed and efficiency using AgentUp. This isn't just about scripting; it's about creating an autonomous, goal-driven agent that can understand, plan, and execute complex Kubernetes operations.

Let's dive into how the new and exciting AgentUp framework makes this possible and what makes this demonstration so compelling for developers.

Getting Started: A New Agent in a Flash

The video kicks off by showing just how easy it is to initialize a new agent using the agentup init command. The key choices made set the stage for a powerful automation tool:

Iterative Agent: This is the core of its intelligence – a goal-driven autonomous agent capable of planning, decomposing tasks, and iterating through them until a goal is achieved. The demo generously allocates 50 iterations, showing its capacity for complex problem-solving.
Essential Components: The initialization includes authentication, state management, an AI provider (OpenAI in this case), MCP (Model Context Protocol), and deployment options. For simplicity in the demo, a simple API key is used for authentication, with state persisted to a file.

The Brain of AgentUp: `agentup.yaml`

Once initialized, the agentup.yaml file becomes the central configuration point – effectively, the "brain of AgentUp". What's particularly appealing for developers here is its declarative runtime, allowing you to set everything in a single point of truth. This configuration is designed to be portable and easily shared or stored in a repository.

A critical part of the configuration involves the MCP (Model Context Protocol), where we use the Kubernetes MCP Server from the containers team. In AgentUp, MCP tools are exposed as A2A (Agent-to-Agent) skills, making them discoverable capabilities. This means one agent can query another to find out if it possesses the necessary skills, for example, to list pods or check cluster state.

Robust Security with Scopes

One of the most impressive aspects for a production environment is AgentUp's approach to security. Each tool available within the Kubernetes MCP server is mapped to a scope, which acts as a security permission.

The demo uses a wildcard scope for simplicity, granting admin access.
However, the system supports a top-down scope hierarchy, allowing for highly granular control over what the MCP server presents to the model.
Crucially, the model is not even aware of tools it has no scope for, and any attempt to use them would be denied. This ensures that your agent operates only within its designated permissions. While a fixed API key is used for the demo, in a real-world scenario, these scopes would typically be within a signed token for robust validation.

Putting the Agent to Work: Live Kubernetes Operations

After a quick virtual environment setup and running the agent, the demonstration shifts to a front-end client that communicates with the agent via A2A JSON RPC methods. This client immediately pulls and displays the available tools/skills from the agent.

The demo beautifully illustrates the iterative agent's capabilities with a series of chained commands:

Discovering Namespaces and Pods: The agent is asked, "How many namespaces do I have in my cluster and which namespaces contain the most pods?".
- The agent authenticates, identifies available tools, and selects namespaces list.
- It then proceeds to pods list in namespace.
- The agent successfully breaks this down into three tasks: listing namespaces, counting pods per namespace, and ranking namespaces by pod count. It correctly identifies the namespace with the most pods, showcasing its goal-driven task decomposition.
Checking Pod Running Times: A follow-up query, "How long have the pods been running within the agent up cluster?", demonstrates the agent's ability to extract specific information, again calling MCP pods listing namespace.
Performing a Deletion (and Verification!): In a bold move, the demonstration requests, "Please remove the completed completed pod".
- The agent processes this, calling pods delete, and successfully removes the specified pod. This highlights its write capabilities and the impact of its assigned scopes.
- To complete the loop, a verification step, "verify the pod has actually been removed," is performed, with the agent confirming the removal and providing a 100% confidence score.

What This Means for Developers

This AgentUp demo highlights several powerful takeaways:

Speed of Development: You can configure an agent incredibly quickly, essentially needing to "set a persona for the agent, give it some tools, and then send it to work".
Autonomous Operations: The iterative, goal-driven nature of these agents means they can handle complex tasks with minimal human intervention.
Secure & Discoverable Capabilities: The MCP system with granular scopes ensures secure operations, while A2A skills make agent capabilities discoverable, paving the way for advanced agent collaboration.

The video hints at exciting future developments like agent collaboration, which promises to unlock even more complex automation scenarios.

If you're looking to bring intelligent automation to your Kubernetes clusters and streamline SRE workflows, AgentUp looks like a game-changer. Check out the video and consider exploring AgentUp yourself – there's even an upcoming agent workshop mentioned where you can build your own agents! This is definitely one to watch for anyone interested in the future of autonomous operations.

The Agentup.yml is available here, to get you going in minutes!

What other Agents could you build, using your favorite MCP servers?

https://gist.github.com/lukehinds/1013cfe94a5417715a71ae4c5e9b6c8c