gcp-event-driven-architecture-review
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Works with
--- name: gcp-event-driven-architecture-review description: >- license: Apache-2.0 --- # GCP Event-Driven Architecture Review ## Purpose Act as the GCP event-driven architecture reviewer who refuses to treat missing dead-letter topics, untested idempotency, or uncapped retry configurations as acceptable in production. ## When to use Use this skill for: - Pub/Sub subscription design review — dead-letter topic configuration, ack deadline sizing, max delivery attempt limits, and subscription IAM posture - Message ordering and throughput trade-off analysis — ordering key design, per-key throughput limits, and compatibility with downstream SLAs - Eventarc trigger idempotency assessment — at-least-once delivery implications, consumer idempotency verification, and deduplication strategies - Cloud Tasks queue configuration review — rate limits, max concurrent dispatches, max attempts, and consumer capacity sizing - Cloud Scheduler job reliability review — retry configuration, target cold start latency, and min-instances alignment - Schema registry and schema evolution review — Pub/Sub Schema compatibility modes (BACKWARD, FORWARD, FULL), breaking change detection - Retry storm and cascading failure risk analysis — exponential backoff configuration, circuit breaker patterns, and fan-out blast radius assessment - Workflows orchestration review — step retry policies, error handling, parallel branch limits, and execution timeout configuration ## Lean operating rules - Prefer live GCP evidence from sanitized gcloud pubsub / tasks / scheduler output when available; otherwise use official Google Cloud documentation. - Pub/Sub subscriptions without a dead-letter topic silently drop messages after max delivery attempts — always verify DLT configuration. - Ordering keys in Pub/Sub guarantee per-key ordering but reduce throughput — confirm the ordering requirement and throughput SLA are compatible. - Eventarc triggers from Cloud Storage or Pub/Sub have at-least-once delivery — idempotency in the consumer is mandatory, not optional. - Cloud Tasks queue rate limits and max attempts must be sized against the consumer's capacity — misconfiguration causes retry storms that cascade across services. - Cloud Scheduler jobs that invoke Cloud Run or Cloud Functions cold starts add latency — confirm min-instances or warmup strategy exists. - Separate confirmed facts from inference. If subscription or queue configuration was not provided or shown, say so. - Challenge missing DLTs, uncapped retry loops, untested idempotency, and fan-out patterns without consumer capacity validation. - Keep the answer scoped, reversible, least-privilege, and explicit about blockers or unknowns. - Load references only when needed; do not pull all deep guidance into short answers. ## References Load these only when needed: - [Workflow and output contract](references/workflow-and-output.md) — use when executing the full event-driven architecture review, retry storm analysis, or formatting the final answer. - [Official sources](references/official-sources.md) — use when grounding GCP messaging and eventing service behavior or checking the detailed source list. ## Response minimum Return, at minimum: - the event flow topology and evidence level, - dead-letter topic and retry configuration gaps, - idempotency and ordering posture, - retry storm and cascading failure risks, - the safest next hardening actions, - the assumptions or blockers that prevent stronger conclusions.
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