Tech Dev Sample Article: Platform Engineering

AI generated.

This article outlines a practical platform engineering roadmap for a 60-person product organization. The focus is standardizing pipelines, reducing toil, and improving release safety. Entity chips highlight the real tools used in each stage.

Tooling: GitHubGitHub, GitLabGitLab, azuredevops, DockerDocker, KubernetesKubernetes, helm, terraform.

Architecture

  • Monorepo governance and code ownership managed in GitHubGitHub
  • CI/CD pipelines in GitLabGitLab with release orchestration in azuredevops
  • Container builds in DockerDocker and deployments to KubernetesKubernetes with helm
  • Edge delivery with CloudflareCloudflare and preview environments on VercelVercel

Cloud services: AWSAWS, gcp, AzureAzure. Debug and quality: sentry, datadog, sonarqube.

Platform comparison

Platform SAML/SSO Built-in registry Hosted runners Policy controls
GitHubGitHub ✓ ✓ ✓ ✓
GitLabGitLab ✓ ✓ ✓ ✓
azuredevops ✓ ✗ ✓ ✓

Runtime & IaC stack

Component Primary Purpose Drift detection
Containers DockerDocker Build & package ✗
Orchestration KubernetesKubernetes Deploy & scale ✓
Packaging helm Release config ✗
IaC terraform Provision infra ✓

Expected outcomes

  • 40% shorter lead time driven by GitHubGitHub automation
  • Fewer production incidents via canary releases on KubernetesKubernetes
  • Full change traceability through azuredevops

Delivery checklist

  • Enforce branch policies in GitHubGitHub
  • Run dependency scans in GitLabGitLab
  • Spin ephemeral environments on KubernetesKubernetes
  • Publish SLO dashboards to datadog

Sample entity chips: GitHubGitHub, DockerDocker, KubernetesKubernetes.