Platform engineering gives product teams a self-service paved road for secure, observable, deployable services while preserving escape hatches. Architecture governance should record context and tradeoffs, automate high-value constraints, measure outcomes, and evolve. A template is successful only if teams can operate what it creates and the platform reduces cognitive load.
Use conformance tests and policy as code for critical rules, but avoid blocking teams on cosmetic uniformity. Track adoption friction and exceptions as product feedback.
Evidence-based capabilities: owner/on-call, SLO and alerts, dependency timeouts, authz tests, tenant isolation, secret rotation, migration compatibility, backup restore date, vulnerability posture, capacity test, AI evaluation freshness, tool approval policy, cost budget, and rollback drill.
Do not reduce security to a single green badge. Link each item to evidence and expiry.
An ADR contains title/status, date, context, decision drivers, considered options, decision, consequences, rollout, rollback, and revisit triggers. Example: “Use PostgreSQL vector search before a dedicated vector database.” Triggers may include index size, query latency, hybrid-search requirements, team capacity, and cost—not an arbitrary calendar date.
AI capability spreads quickly and can duplicate provider SDKs, prompts, tools, and sensitive traces. A platform centralizes hard controls and reusable evidence without forcing one orchestration framework. Teams still own feature semantics and evaluations.
Create a golden-path specification and ADR for SupportDesk AI, including the decision not to use Kubernetes or a dedicated vector database initially.
Acceptance criteria: a new team can create, deploy, observe, and roll back a safe service without privileged manual tickets; optional infrastructure stays optional; decisions have measurable future triggers.