AI Cloud Infrastructure Management with Agent Skills

Five-Stage Workflow: Plan to Monitor

A complete AI-assisted cloud infrastructure workflow moves through five stages. Each stage maps to one or more of the skills above, and the agent maintains context across all stages in a single conversation thread.

Stage 1: Plan

The agent reviews your requirements — target workload, expected traffic, budget constraints, compliance requirements — and proposes a reference architecture. It outputs a list of resources to create, estimated monthly cost from the provider\u0027s pricing API, and the Terraform module structure it will generate. You review and approve before any cloud API calls are made.

Stage 2: Provision

The Terraform Skill generates \u002etf files matching the approved architecture, runsterraform plan to show the exact changes, and waits for your confirmation before applying. The AWS Skill handles any AWS-specific resources that fall outside the Terraform provider, such as Service Control Policies or Organization-level configurations.

Stage 3: Configure

With base infrastructure in place, the Docker Skill builds the application container image using your Dockerfile, tags it with the current Git SHA, and pushes it to your container registry. The agent then generates or updates Kubernetes manifests with the new image tag, resource requests and limits, and environment variable references.

Stage 4: Deploy

The Kubernetes Skill applies the updated manifests using a rolling update strategy and watches the rollout status in real time. If any pods enter a CrashLoopBackOff state, the agent immediately fetches logs, identifies the error, and proposes a corrective action — all before you would have noticed the problem in a dashboard.

Stage 5: Monitor

Post-deployment, the Cloudflare MCP checks edge health metrics, cache hit rates, and error response codes from Cloudflare\u0027s analytics API. The agent correlates anomalies with the deployment timeline and surfaces actionable insights: "Error rate increased 12% after deploy — the most common error is a 502 from the origin, which correlates with the new database connection pool setting."

Step-by-Step Setup

Step 1: Prerequisites

Ensure you have the following installed: Node.js 18+, AWS CLI (configured with a least-privilege IAM role), Terraform 1.5+, Docker, and kubectl pointed at your cluster. Each MCP server will use the credentials already configured for these tools rather than requiring separate authentication.

Step 2: Add Skills to Your MCP Config

Add the five cloud infrastructure skills to your AI assistant\u0027s MCP configuration file. For Claude Code, this is ~/.claude/settings.json:

{
  "mcpServers": {
    "cloudflare": {
      "command": "npx",
      "args": ["-y", "@cloudflare/mcp-server-cloudflare"],
      "env": { "CLOUDFLARE_API_TOKEN": "$CLOUDFLARE_API_TOKEN" }
    },
    "aws": {
      "command": "npx",
      "args": ["-y", "aws-mcp-server"]
    },
    "terraform": {
      "command": "npx",
      "args": ["-y", "terraform-mcp-server"]
    },
    "docker": {
      "command": "npx",
      "args": ["-y", "docker-mcp-server"]
    },
    "kubernetes": {
      "command": "npx",
      "args": ["-y", "kubernetes-mcp-server"]
    }
  }
}

Step 3: Verify Each Skill

Restart your AI assistant and confirm each skill is connected with a simple read-only command:

• "List my Cloudflare zones" — verifies Cloudflare MCP
• "List all S3 buckets in us-east-1" — verifies AWS Skill
• "Show terraform version" — verifies Terraform Skill
• "List running Docker containers" — verifies Docker Skill
• "Get all namespaces in the cluster" — verifies Kubernetes Skill

Use Cases

Zero-Downtime Deployment

Ask the agent to deploy a new version of your API service: "Build the Docker image from the current main branch, tag it with today\u0027s date, push to ECR, update the Kubernetes deployment to use the new tag, and watch the rollout. Roll back automatically if the error rate exceeds 1% within five minutes." The agent executes all five steps and monitors the outcome without further input from you.

Infrastructure Cost Audit

"Use the AWS Skill to list all EC2 instances that have been running for more than 30 days with CPU utilization below 5%, then generate a Terraform plan to rightsize them to t3.small." The agent produces a prioritized list of savings opportunities with estimated monthly cost reduction for each.

Disaster Recovery Testing

"Simulate a primary region failure by updating the Cloudflare DNS to point to the standby region, verify the application is healthy in the standby region using the Kubernetes Skill, and report the failover time." AI-assisted DR testing that previously required a dedicated runbook and an operations team can now be executed as a conversational workflow.

Comparison Table

Frequently Asked Questions