🧭 Engineering Best Practices Playbook

🧱 1. Planning

Written Planning Process
Use RFCs, Design Docs, or ADRs before implementation to clarify goals and gather feedback.
Standardized Architectural Diagrams
Use tools like Lucidchart, Excalidraw, or PlantUML with a shared legend and consistent style.
Milestone Definition
Break projects into phases with measurable deliverables and deadlines.
Stakeholder Communication
Establish review cadences with product, engineering, and leadership.

Environment Setup Automation
Use Docker, DevContainers, Gitpod, or bootstrap scripts for quick onboarding.
Prototyping
Build throwaway prototypes to test ideas before formal implementation.
Code Reviews
All non-trivial code must be peer-reviewed for clarity, performance, and maintainability.
Automated Code Formatting
Enforce styles using Prettier, Black, gofmt, etc.
Linting
Use ESLint, Pylint, RuboCop to catch style and logic issues early.
Static Code Analysis
Tools like SonarQube, Snyk, or CodeQL to catch security and quality issues.
Project & Component Templates
Use starter kits or clones with standard structure, lint/test config, and CI.
Code Generation
Automate boilerplate with tools like Hygen, Plop, or custom generators.
Post-Commit Code Reviews
Used in small or high-velocity teams. Allows faster iteration at risk of regressions.
Cross-Platform Development
Use frameworks like React Native, Flutter, or Capacitor to maximize code reuse.
CI/CD
Use GitHub Actions, GitLab CI, or CircleCI to automate testing, building, and deployment.

Automated Testing
Use a pyramid of:
- Unit tests
- Integration tests
- End-to-end (E2E) tests
- Performance & load tests
Test-Driven Development (TDD)
Write tests before the implementation to drive design and correctness.
Preview Environments
Use ephemeral PR environments via Vercel, Netlify, or custom infrastructure.
Staging/QA Environments
Isolate testing environments before production rollout.
Testing in Production
Use safe methods: feature flags, shadow traffic, or canary releases.
Test Data Generation
Use factories, scripts, or production forks (with redaction) for realism.
Load Testing
Use tools like k6, JMeter, or Locust to simulate heavy traffic.
Performance Benchmarking
Benchmark CPU, memory, I/O and automate performance regressions checks.

Feature Flags & A/B Testing
Roll out features gradually and experiment safely with LaunchDarkly, Unleash, etc.
Progressive Delivery
Staged rollouts, blue-green deployments, and canary releases.
Monitoring & Alerting
Tools like Prometheus, Grafana, Datadog, New Relic for live monitoring.
Structured Logging
Use JSON-based logs with correlation IDs and log aggregation (e.g., ELK stack).
Observability
Add OpenTelemetry for tracing, metrics, and logs visibility.

Production Debugging
Tools like Sentry, Datadog, Honeycomb, or in-house observability platforms.
Documentation
Auto-generated or hand-written using tools like Docusaurus, MkDocs, etc.
Runbooks
Include alert resolution steps, escalation contacts, and common fixes.
Migration Runbooks
Plan and automate data/code migrations with safety and rollback procedures.