Platform Architecture & Integration Playbook

Welcome — why this playbook matters

This playbook helps teams reduce integration friction while keeping ownership clear and teams autonomous. It describes ownership models, common integration patterns, an integration decision guide, an API/version governance checklist you can apply immediately, a lightweight data-contract template, and recommended observability practices for detecting and containing cross-team failures.

Who should use this

• Platform teams designing reusable capabilities.
• Product teams integrating with platform services or other product APIs.
• Architects and engineering managers who need practical governance without blocking delivery.

Outcomes you can expect

• Clear ownership boundaries and decision rules so teams can integrate safely.
• Practical guardrails for versioning, contracts, and deprecation that reduce runtime breakage.
• Observability patterns that make integration failures visible and actionable.

Core principles

• Team-owned services: Each service or API has a single owning team responsible for compatibility, quality, and runbooks.
• Contracts over coupling: Exchange well-defined contracts (APIs or event schemas) rather than sharing internal implementation or direct DB access.
• Prefer asynchronous where possible: Event-driven integrations reduce coupling and increase resilience for many cross-team flows.
• Automate compatibility checks: CI-based contract tests are non-negotiable for safe evolution.
• Make failures visible: Instrument integrations with logs, metrics, tracing, and alerts focused on contract health.

Integration patterns (when to use them)

Integration decision guide

Use these quick rules to pick a pattern for a given integration.

1. If the caller needs an immediate, strongly consistent response and the call is user-facing, choose a sync service API (REST/gRPC) and design for timeouts and graceful degradation.
2. If many systems need the same state change and eventual consistency is acceptable, prefer events (pub/sub) to broadcast changes and decouple consumers.
3. If the integration is low-level utility logic shared across services, evaluate a shared SDK—but prefer service APIs or platform-hosted functions for evolving capabilities.
4. If you control both sides and latency is unimportant, but transformations are heavy, use batched ETL or data replication.
5. Always ask: who owns the data? The owning team should expose the contract and own compatibility guarantees.

API & version governance checklist

Use this checklist before accepting or publishing an integration.

• Ownership: Owning team named and contact info documented.
• Contract defined: Schema or API spec published (OpenAPI/Protobuf/JSON Schema) with examples.
• Versioning policy: Semantic versioning (major.minor.patch) and clear compatibility guarantees for each segment.
• Backward compatibility requirements: define what is additive vs breaking.
• Deprecation policy: minimum notice period, migration guidance, and sunset dates.
• Testing: Consumer-driven contract tests and CI gates that run on both producer and consumer changes.
• Environment parity: Staging environments replicating contract behavior and test data for consumers.
• Security: authentication/authorization method, rate limits, and data classification guidance.
• Observability: required metrics, tracing headers (e.g., correlation IDs), structured logs, and error codes documented.
• Runbooks & SLAs: incident runbook, expected recovery times, and SLOs/SLAs when applicable.
• Change communication: mailing list/announcement channel and version release notes template.

Data contract template (lightweight)

Use this as the minimum metadata for any shared schema or event contract. Store one document per contract in a registry.

• Contract Name — short identifier (e.g., order.created.v1)
• Version — semantic version (major.minor.patch)
• Producer — owning team/service
• Consumers — known consumers (optional but useful)
• Purpose — one-sentence description of the intent
• Schema location — link to OpenAPI/JSON Schema/Protobuf
• Compatibility rules — what constitutes a breaking change
• Example payload — minimal representative example
• Change log — list of versioned changes and migration notes

Example (compact): Contract Name: order.created; Version: 1.0.0; Producer: orders-service; Purpose: notify downstream systems of new orders; Schema: /contracts/order.created.json; Compatibility: adding optional fields allowed, removing fields is breaking.

Recommended observability patterns for integrations

• Standard telemetry fields: correlation_id, trace_id, producer, consumer (if known), contract_version, request_id, timestamp.
• Key metrics: request rate, error rate (4xx/5xx), latency percentiles, contract schema validation errors, consumer lag (for events), message retransmits.
• Distributed tracing: propagate trace IDs across sync calls and async handoffs to link cause and effect.
• Structured logs: include contract identifiers and version to make forensic analysis easier.
• Contract health checks: automated schema validation in CI and runtime schema checks with alerts on invalid messages.
• Synthetic tests: end-to-end smoke tests that exercise critical contracts on a schedule.
• Alerting & SLOs: set alert thresholds tied to business impact (e.g., percent of orders failing vs raw error counts).
• Dashboards: contract-centric dashboards showing consumers, producers, versions in use, and error trends.

Operational play — practical checklist to roll this out

1. Inventory: catalog existing integrations, contracts, owners, and versions.
2. Prioritize: pick high-risk/high-value integrations for immediate stabilization.
3. Pilot: implement contract tests, schema registry entries, and basic dashboards for one integration.
4. Automate: add contract tests to CI, enforce schema validation in pipelines, and require version metadata in messages.
5. Govern: create a lightweight approval flow for breaking changes and a communication template for deprecation notices.
6. Scale: package this playbook and the pilot artifacts into a reusable toolkit for other teams to adopt.

Recommended artifacts to publish alongside this playbook

• Integration decision guide (one-page).
• API/version governance checklist (template checkable by CI).
• Data contract template and example contracts.
• Contract/Schema registry or a simple index page listing contracts and owners.
• Observability dashboard templates and alerting thresholds.
• Consumer-driven contract test examples and CI snippets.

How to tailor this playbook

Start by copying the artifacts into an adaptive collection owned by your platform team. Keep the decision guide and checklist lightweight and living — the goal is to remove blockers, not add review bottlenecks. For regulated environments, expand contract metadata to include compliance and retention rules.

Next steps (90-day plan)

1. Week 1–2: Run an integration inventory workshop and publish owners.
2. Week 3–6: Pilot contract testing and schema registry for 2–3 critical contracts.
3. Week 7–12: Roll out governance checklist as CI gates and publish dashboards/alerts.
4. Ongoing: Maintain the registry, run quarterly contract-health reviews, and evolve policies based on incidents and team feedback.

This playbook is intended to be copied and adapted to your organization's needs. Use the artifacts as starting points and evolve them as you learn.