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:
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 |
1---
2name: devops-workflow-engineer
3description: >
4 Generate and optimize GitHub Actions CI/CD workflows. Use when designing workflows, planning
5 multi-environment deployments, optimizing pipeline cost and runtime, or implementing blue-
6 green, canary, or rolling deployment strategies.
7license: MIT + Commons Clause
8metadata:
9 version: 1.2.0
10 author: borghei
11 category: engineering
12 domain: devops
13 updated: 2026-06-17
14 tags: [github-actions, ci-cd, deployment, workflows]
15 python-tools: workflow_generator.py, pipeline_analyzer.py, deployment_planner.py
16 tech-stack: python, github-actions, yaml, ci-cd
17---
18
19# DevOps Workflow Engineer
20
21Generate GitHub Actions workflow YAML, analyze existing pipelines for optimization opportunities, and create deployment plans with strategy selection, health checks, and rollback procedures.
22
23## Core Capabilities
24
25- **CI pipeline design** — fail-fast job ordering (lint → unit → build → integration → security) with matrix testing and CI time/flake/cache targets.
26- **CD & multi-environment** — dev/staging/prod promotion flows, build-once-deploy-everywhere, environment protection rules, and rollback at every stage.
27- **Pipeline optimization** — detect missing caching, missing timeouts, serial chains, deprecated actions, leaked secrets, and oversized runners; apply path filtering and concurrency cancellation.
28- **Deployment strategies** — choose blue-green, canary, or rolling via decision tree; canary traffic-split schedule with promotion gates.
29- **GitHub Actions patterns** — reusable workflows, OIDC auth, secrets hierarchy, and runner cost estimation.
30
31## When to Use
32
33- Designing a new CI or CD workflow from scratch.
34- Planning a multi-environment (dev/staging/prod) deployment.
35- Optimizing an existing pipeline's cost or runtime.
36- Implementing a blue-green, canary, or rolling deployment strategy.
37
38## Clarify First
39
40Before generating the workflow, confirm these inputs. If any is unknown or vague, ASK — do not assume:
41
42- [ ] **Workflow type** — CI, CD, release, or security-scan (sets `workflow_generator.py --type`)
43- [ ] **Stack** — language and test framework (e.g. python/pytest) (drives the generated YAML steps via `--language`/`--test-framework`)
44- [ ] **Deployment strategy & environments** — blue-green, canary, or rolling, and which of dev/staging/prod (drives the `deployment_planner.py` plan)
45
46Stop 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.
47
48## Tools
49
50| Tool | Purpose | Command |
51|------|---------|---------|
52| `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` |
53| `pipeline_analyzer.py` | Analyze workflows for optimization findings, cost estimates, severity ratings | `python scripts/pipeline_analyzer.py .github/workflows/ --format json` |
54| `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` |
55
56All tools support `--format json` and `--output`/`-o` for file writing.
57
58## References
59
60Load the reference that matches the task — keep this file lean and pull detail on demand:
61
62- **[references/workflows-and-optimization.md](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.
63- **[references/github-actions-patterns.md](references/github-actions-patterns.md)** — deep GitHub Actions pattern library. Read when authoring advanced workflow YAML.
64- **[references/deployment-strategies.md](references/deployment-strategies.md)** — deep deployment strategy guide (blue-green, canary, rolling). Read when planning a release rollout.
65- **[references/agentic-workflows-guide.md](references/agentic-workflows-guide.md)** — agentic/automated workflow patterns. Read when wiring up AI-driven or autonomous pipeline steps.
66
67## Integration Points
68
69| Skill | Integration |
70|-------|-------------|
71| `release-orchestrator` | Release workflows align with versioning and changelog |
72| `senior-devops` | Deployment strategies complement infra automation |
73| `senior-secops` | Security scanning steps feed SecOps dashboards |
74| `senior-qa` | CI quality gates map to QA acceptance criteria |
75| `incident-commander` | Rollback procedures connect to incident playbooks |
borghei