resume_deployment · Kubernetes MCP Server MCP: Risk & Policy

WHAT IT DOES

What resume_deployment does on Kubernetes MCP Server

AI agents invoke resume_deployment to trigger actions in Kubernetes MCP Server. 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 resume_deployment needs a policy

Resuming a paused deployment triggers execution of pending rollout changes in Kubernetes, which can cause pods to be replaced, scaled, or updated across a cluster. This is an operational trigger that initiates external system changes beyond simple data writes, making it an Execute category action. The blast radius is high since a resumed deployment could roll out breaking changes to production workloads at scale.

From the tool's definition Resume a paused deployment

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

resume_deployment Rate-limited

resume_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": {
    "resume_deployment": {
      "limits": [
        {
          "counter": "resume_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 Kubernetes MCP Server, so you can run agents against it safely.

FAQ

Questions about resume_deployment

What does the resume_deployment tool do? +

Resume a paused deployment. It is categorised as a Execute tool in the Kubernetes MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on resume_deployment? +

Register the Kubernetes MCP Server MCP server in PolicyLayer and add a rule for resume_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 Kubernetes MCP Server. Nothing to install.

What risk level is resume_deployment? +

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

Can I rate-limit resume_deployment? +

Yes. Add a rate_limit block to the resume_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 resume_deployment completely? +

Set action: deny in the PolicyLayer policy for resume_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 resume_deployment? +

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