nw-platform-engineering-foundations

Foundational platform engineering knowledge from key references -- Continuous Delivery, SRE, Accelerate, Team Topologies, Chaos Engineering, and Secure Delivery. Load when contextual grounding in platform engineering theory is needed.

322 stars

Best use case

nw-platform-engineering-foundations is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Foundational platform engineering knowledge from key references -- Continuous Delivery, SRE, Accelerate, Team Topologies, Chaos Engineering, and Secure Delivery. Load when contextual grounding in platform engineering theory is needed.

Teams using nw-platform-engineering-foundations should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/nw-platform-engineering-foundations/SKILL.md --create-dirs "https://raw.githubusercontent.com/nWave-ai/nWave/main/nWave/skills/nw-platform-engineering-foundations/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/nw-platform-engineering-foundations/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How nw-platform-engineering-foundations Compares

Feature / Agentnw-platform-engineering-foundationsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Foundational platform engineering knowledge from key references -- Continuous Delivery, SRE, Accelerate, Team Topologies, Chaos Engineering, and Secure Delivery. Load when contextual grounding in platform engineering theory is needed.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Platform Engineering Foundations

## Continuous Delivery (Humble and Farley)

Key principles: Build quality in | Work in small batches | Automate almost everything | Pursue continuous improvement | Everyone is responsible (shared ownership).

Pipeline progression: Commit -> Acceptance -> Capacity -> Production stages. For detailed stage definitions and quality gates, see `cicd-and-deployment` skill.

## Site Reliability Engineering (Google -- Beyer et al.)

Key principles: SLOs over SLAs (internal targets stricter than external) | Error budgets (balance reliability and velocity) | Toil elimination (automate repetitive manual work) | Embrace risk (calculate risk, do not eliminate it).

Observability: Four Golden Signals (latency, traffic, errors, saturation) | SLI -> SLO -> Error Budget -> Alerting chain | Dashboards for investigation, not monitoring.

## Accelerate (Forsgren, Humble, Kim)

### DORA Metrics
- **Deployment frequency**: how often code deploys to production
- **Lead time for changes**: time from commit to production
- **Change failure rate**: % of deployments causing failure
- **Time to restore**: time to recover from production failure

### Performance Levels

| Metric | Elite | High |
|--------|-------|------|
| Deployment frequency | Multiple times/day | Daily to weekly |
| Lead time | < 1 hour | 1 day to 1 week |
| Change failure rate | 0-15% | 16-30% |
| Time to restore | < 1 hour | < 1 day |

Use DORA metrics as baselines when assessing current state and setting improvement targets.

## Team Topologies (Skelton and Pais)

### Team Types
- **Stream-aligned**: delivers value to customer, owns full lifecycle
- **Platform**: provides self-service capabilities, reduces cognitive load
- **Enabling**: helps teams adopt new practices, temporary engagement
- **Complicated subsystem**: owns complex technical domain

### Platform Principles
Platform as a product (internal developer platform) | Self-service with guardrails | Reduce cognitive load on stream-aligned teams | Thinnest viable platform.

Use when designing platform team structures and determining which capabilities to centralize vs delegate.

## Chaos Engineering (Rosenthal et al.)

Principles: Build hypothesis about steady state | Vary real-world events | Run experiments in production | Automate experiments continuously.

Practices: GameDays (scheduled chaos experiments) | Fault injection (network latency, failures) | Chaos monkey (random instance termination).

## Secure Delivery (Building Secure and Reliable Systems)

Principles: Least privilege (minimal permissions) | Defense in depth (multiple security layers) | Zero trust (verify explicitly, assume breach).

Pipeline security: SAST in CI | DAST pre-production | SCA for dependency vulnerabilities | Secrets scanning | SBOM for supply chain transparency.

## GitOps (GitOps and Kubernetes)

Principles: Declarative desired state in Git | Automated reconciliation | Drift detection and correction | Pull-based deployments.

Tools: ArgoCD (Kubernetes-native GitOps CD) | Flux (GitOps toolkit for Kubernetes).

Patterns: App of Apps for multi-environment management | Helm with GitOps for parameterization | Kustomize overlays for environment differences.

## Constraint Impact Analysis Template

Use when assessing platform constraints before designing infrastructure.

```markdown
## Platform Constraint Impact Analysis

| Constraint | Source | % Delivery Affected | Priority |
|------------|--------|---------------------|----------|
| {constraint} | {architecture/ops/security} | {X}% | {HIGH/MEDIUM/LOW} |

### Constraint-Free Baseline
- Maximum theoretical deployment frequency: ___
- Components that can proceed without constraints: ___ ({X}%)
- Quick wins available now: ___

### Decision Rules
- Constraint affects > 50% of delivery: address as primary focus
- Constraint affects < 50% of delivery: address as secondary
- Constraint affects < 20% of delivery: consider deferring

### Recommendation
Primary focus should be: {constraint-free opportunities or primary constraint}
```

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