This infrastructure documentation as code guide shows how a platform team moved runbooks, ownership maps, and architecture decisions into versioned workflows that people actually trusted.
Infrastructure documentation as code attracts search traffic because teams usually start caring about it only after a rough incident, an audit request, or a painful handoff. The documentation problem is rarely that people do not write enough. It is that the most important notes live outside the delivery workflow.
Once architecture decisions, change steps, and ownership details drift away from code, every new engineer and every auditor gets a different answer to the same question.
A platform team supported Terraform modules, Kubernetes clusters, shared CI runners, and a long list of internal services used by product teams.
During a customer security review, the team spent two days reconciling diagrams, stale wiki pages, and private notes to explain how data moved through one production environment.
The audit was passed, but the team realized that incident response and onboarding suffered from the same documentation drift.
They moved architecture decision records, runbooks, dependency maps, and service ownership files into the same repositories that drove infrastructure changes.
These issues are common because teams often optimize first for delivery speed and only later realize that reliability, cost visibility, or AI quality needs its own explicit control points. The faster a team is growing, the more likely it is to carry forward defaults that were reasonable at five services and painful at twenty-five.
The important theme is that the winning pattern is usually not more tooling by itself. It is better contracts, better sequencing, and clearer feedback when something drifts. That is what keeps the team out of reactive mode and makes the system easier to explain to new engineers, auditors, and on-call responders.
# ADR-012: Split shared runners by sensitivity
## Context
Security scans and customer-facing deploy jobs currently share the same runner pool.
## Decision
Create separate runner groups for production deploys and general CI workloads.
## Consequences
- Better isolation for privileged jobs
- Slightly higher runner management overhead
- Clearer audit trail for production access
This kind of implementation detail matters for search-driven readers because it turns abstract best practices into something a team can adapt immediately. The code or config is not the whole solution, but it shows where reliability and control actually live in the workflow.
For search readers, infrastructure documentation as code sounds like a process topic. In practice it is a reliability topic. Teams move faster when they can trust the map of what they operate.
The best documentation system is not the prettiest one. It is the one that changes with the infrastructure and survives audits, incidents, and turnover without drama.
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