deploy-agent

Overview

This agent ships code through a controlled pipeline with verification gates at every stage — build, test, and health checks before anything reaches production. Use it when a release must be reproducible and reversible. It refuses to call a deployment done until the live state is verified.

Deploy Agent

Quick Reference — see parent for full agent ecosystem.

The Deploy Agent ships artifacts to staging and production through a controlled pipeline with health checks, migration execution, automated rollbacks, and post-deploy monitoring. Its core design principle is reversibility: every deploy must have a tested rollback path before it begins.

When Not to Use

• Simple or one-off tasks — if the task is straightforward, direct execution is faster than structured methodology.
• Already established workflows — follow existing team conventions rather than introducing new frameworks.
• When automation overhead exceeds benefit — for very small scopes, the setup cost may not be justified.

Dependencies

• Python 3.8+ or Node.js 18+
• Access to relevant APIs/services for your specific use case
• Basic understanding of the domain concepts

Commands

# Refer to the skill's usage section for specific commands
# Adapt these to your workflow

Key Responsibilities

• Execute deployments with strategy: Support blue-green, rolling, canary, and hotfix strategies with zero-downtime guarantees
• Run database migrations: Apply schema changes in the correct order with dry-run validation and automated rollback scripts
• Verify post-deploy health: Run health checks, smoke tests, and monitor error rates for a configurable observation window

Code Example

"""Minimal deploy agent pattern — ship with verification."""

import json, subprocess, sys
from pathlib import Path

def deploy(target: str, tag: str, strategy: str = "rolling") -> dict:
    # 1. Pre-deploy checks
    assert subprocess.run(["git", "diff", "--quiet"], cwd=".").returncode == 0, "Dirty working tree"
    assert subprocess.run([sys.executable, "-m", "pytest", "-x", "-q"]).returncode == 0

    # 2. Build artifact
    build = subprocess.run(["docker", "build", "-t", f"app:{tag}", "."], capture_output=True, text=True)
    if build.returncode != 0:
        return {"status": "failed", "error": build.stderr}

    # 3. Run migrations (dry-run first)
    dry = subprocess.run([sys.executable, "-m", "alembic", "upgrade", "--sql", "head"], capture_output=True, text=True)
    print(f"Migration SQL:\n{dry.stdout}")

    # 4. Deploy
    push = subprocess.run(["docker", "push", f"app:{tag}"])
    if target == "production":
        subprocess.run(["kubectl", "set", "image", f"deployment/app=app:{tag}"])
        subprocess.run(["kubectl", "rollout", "status", "deployment/app"])

    return {
        "target": target, "tag": tag, "strategy": strategy,
        "migration_applied": True, "rollback": f"kubectl rollout undo deployment/app"
    }

if __name__ == "__main__":
    result = deploy(sys.argv[1], sys.argv[2], sys.argv[3] if len(sys.argv) > 3 else "rolling")
    print(json.dumps(result, indent=2))