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

Tool	Purpose	Command
workflow_generator.py	Generate GitHub Actions YAML (ci, cd, release, security-scan, docs-check)	python scripts/workflow_generator.py --type ci --language python --test-framework pytest
pipeline_analyzer.py	Analyze workflows for optimization findings, cost estimates, severity ratings	python scripts/pipeline_analyzer.py .github/workflows/ --format json
deployment_planner.py	Generate a deployment plan with strategy, health checks, rollback	python scripts/deployment_planner.py --type webapp --environments dev,staging,prod --strategy canary

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

References

Load the reference that matches the task — keep this file lean and pull detail on demand:

• references/workflows-and-optimization.md — the CI / CD / optimization workflows with full YAML, deployment-strategy decision tree and canary schedule, GitHub Actions patterns, runner cost table, anti-patterns, and troubleshooting. Read when building or tuning a pipeline.
• references/github-actions-patterns.md — deep GitHub Actions pattern library. Read when authoring advanced workflow YAML.
• references/deployment-strategies.md — deep deployment strategy guide (blue-green, canary, rolling). Read when planning a release rollout.
• references/agentic-workflows-guide.md — agentic/automated workflow patterns. Read when wiring up AI-driven or autonomous pipeline steps.

Integration Points

Skill	Integration
release-orchestrator	Release workflows align with versioning and changelog
senior-devops	Deployment strategies complement infra automation
senior-secops	Security scanning steps feed SecOps dashboards
senior-qa	CI quality gates map to QA acceptance criteria
incident-commander	Rollback procedures connect to incident playbooks