DevOps Workflow Engineer

DevOps Workflow Engineer

Generate GitHub Actions workflow YAML, analyze existing pipelines for optimization opportunities, and create deployment plans with strategy selection, health checks, and rollback procedures.

Core Capabilities

• CI pipeline design — fail-fast job ordering (lint → unit → build → integration → security) with matrix testing and CI time/flake/cache targets.
• CD & multi-environment — dev/staging/prod promotion flows, build-once-deploy-everywhere, environment protection rules, and rollback at every stage.
• Pipeline optimization — detect missing caching, missing timeouts, serial chains, deprecated actions, leaked secrets, and oversized runners; apply path filtering and concurrency cancellation.
• Deployment strategies — choose blue-green, canary, or rolling via decision tree; canary traffic-split schedule with promotion gates.
• GitHub Actions patterns — reusable workflows, OIDC auth, secrets hierarchy, and runner cost estimation.

When to Use

• Designing a new CI or CD workflow from scratch.
• Planning a multi-environment (dev/staging/prod) deployment.
• Optimizing an existing pipeline's cost or runtime.
• Implementing a blue-green, canary, or rolling deployment strategy.

Clarify First

Before generating the workflow, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• Workflow type — CI, CD, release, or security-scan (sets workflow_generator.py --type)
• Stack — language and test framework (e.g. python/pytest) (drives the generated YAML steps via --language/--test-framework)
• Deployment strategy & environments — blue-green, canary, or rolling, and which of dev/staging/prod (drives the deployment_planner.py plan)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Tools

All tools support --format json and --output/-o for file writing.

References