GCP Outage

Original Article ↗ Hacker News Discussion ↗

Scope of the outage

  • Users reported widespread failures across many Google Cloud services: Console, GCS, Cloud Run, Cloud SQL, BigQuery, IAM, GKE, Cloud Build, Dataproc, Cloud Data Fusion, Firebase Auth/Firestore/Hosting/Data Connect, Cloud Shell, Cloud Workstations, Vertex AI Search, Gemini API, reCAPTCHA, and Google Meet/Chat/Maps/Street View/Nest/RCS messaging.
  • Impact spanned many regions (us‑west1, us‑central1, us‑east1, Europe including Frankfurt/Netherlands, Asia including South Korea and India).
  • Many third‑party platforms broke as collateral damage: Anthropic/Claude, Supabase, Sentry, npm/Yarn, Docker Hub (partially), Expo/FCM‑based systems, Discord uploads, Twitch, Spotify, Mapbox, xAI, various AI dev tools, and more.
  • Some workloads (e.g., App Engine, intra‑VPC traffic) kept working, indicating control-plane/auth failures more than pure compute loss.

Status pages and transparency

  • For a long initial window, GCP’s public status page showed “No major incidents” and all‑green checks while users saw pervasive errors.
  • Firebase’s status site explicitly cited a “Google Cloud global outage” before the GCP page acknowledged anything; that wording was later edited to remove “Google Cloud.”
  • Multiple comments assert major cloud status pages are manual, tightly controlled by PR/Legal/VP‑level approval because of SLA and compensation implications.
  • Many participants say they don’t trust first‑party status pages at all, preferring Downdetector, social media, or community chatter, despite acknowledging crowdsourced noise.

Root cause theories and dependencies

  • The official incident later attributed the GCP issues to an Identity and Access Management service problem; errors like “visibility check was unavailable” and token refresh failures matched this.
  • One contributor tied the symptoms to an internal Google service (“Chemist”) that enforces project/billing/abuse/quotas; this is speculative but fits the pattern of global auth/policy failure.
  • Cloudflare reported its Workers KV going offline due to a “3rd party service that is a key dependency,” strongly suspected in the thread to be a GCP service.
  • Some early speculation about BGP or backbone issues was later considered unlikely by several participants; the consensus leans toward a higher‑level auth/control‑plane failure, though anything beyond the published incident report is unclear.

Reliability, architecture, and cloud risk

  • Discussion highlights how a single global control‑plane/SaaS dependency (IAM, auth, KV, config services) can bypass region/zone redundancy: services are “up” but cannot authorize, so they effectively fail everywhere.
  • People note that large systems are always partially degraded; the debate is where to set the threshold for calling an incident and how to represent partial vs widespread impact.
  • Some argue status pages should at least say “degraded, some users seeing errors”; others emphasize the non‑binary nature of “up/down” and the difficulty of automating meaningful, low‑false‑positive health signals at this scale.
  • Several engineers discuss circuit breakers and backoff as key patterns: external SaaS outages can otherwise cascade into self‑inflicted failures even on unaffected clouds.

Centralization, SLAs, and business incentives

  • There is broad cynicism that uptime metrics and “five nines” claims are massaged via optimistic definitions and underreporting; SLAs are seen as mostly contractual escape hatches rather than guarantees of reliability.
  • Some argue big customers likely get accurate private incident info even when public dashboards lag or downplay issues.
  • The outage is cited as a lesson in “counterparty risk” and over‑reliance on a few giant cloud/edge providers; a few commenters say their mostly self‑hosted stacks rode out the event unnoticed.

Cultural and usage observations

  • The outage made many developers confront how dependent they’ve become on cloud‑hosted AI tools (Gemini, Claude, etc.) for everyday coding and ticket triage.
  • The RCS outage, contrasted with relatively robust SMS history, is used as an example of how centralization (e.g., Google’s hosted Jibe backend) can create new single points of failure.
  • Several note the irony that even monitoring, auth, status, and CDN/control‑plane systems (Cloudflare, Firebase, IAM, KV stores) themselves depended on the same clouds they’re supposed to make resilient.