restart_deployment · K8s MCP: Risk & Policy

WHAT IT DOES

What restart_deployment does on K8s

AI agents invoke restart_deployment to trigger actions in K8s. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

WHY IT NEEDS A POLICY

Why restart_deployment needs a policy

restart_deployment executes a concrete action against a Kubernetes cluster—initiating a rolling update of a deployment. While not destructive (the deployment itself is not deleted), it actively modifies the state of infrastructure by terminating and recreating pods. This falls squarely under Execute: it runs an operation whose effects depend on which deployment is targeted.

From the tool's definition Tool performs a 'rolling update' restart operation on Kubernetes deployments, which triggers external cluster operations. This is equivalent to 'kubectl rollout restart', an imperative command that initiates deployment modifications with side effects.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

restart_deployment Rate-limited

restart_deployment stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "restart_deployment": {
      "limits": [
        {
          "counter": "restart_deployment_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches K8s, so you can run agents against it safely.

FAQ

Questions about restart_deployment

What does the restart_deployment tool do? +

Restart a deployment via rolling update (equivalent to kubectl rollout restart). It is categorised as a Execute tool in the K8s MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on restart_deployment? +

Register the K8s MCP server in PolicyLayer and add a rule for restart_deployment: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches K8s. Nothing to install.

What risk level is restart_deployment? +

restart_deployment is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit restart_deployment? +

Yes. Add a rate_limit block to the restart_deployment rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block restart_deployment completely? +

Set action: deny in the PolicyLayer policy for restart_deployment. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides restart_deployment? +

restart_deployment is provided by the K8s MCP server (jingyanjiang/k8s-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.