RESOURCE_EXHAUSTED
GCP RESOURCE_EXHAUSTED means a quota, rate limit, or finite backend capacity was exhausted for the request.
Last reviewed: February 11, 2026|Editorial standard: source-backed technical guidance
What Does Resource Exhausted Mean?
Requests are rejected due to exhausted limits, so throughput drops until demand is reduced, retries are controlled, or quota headroom is restored.
Common Causes
- -Per-project, per-user, or per-method quota limits were exceeded.
- -Burst traffic combined with aggressive retries triggered short-window throttling.
- -Workload demand exceeded available backend capacity or configured throughput.
- -Multiple workers or tenants are contending for the same constrained quota bucket.
How to Fix Resource Exhausted
- 1Inspect error details and quota metrics to identify the exact exhausted dimension and scope.
- 2Apply exponential backoff with full jitter and strict retry budgets for idempotent calls.
- 3Reduce burst concurrency using queueing, token buckets, or workload smoothing.
- 4Request quota increase or redistribute traffic across projects/regions where architecture allows.
Step-by-Step Diagnosis for Resource Exhausted
- 1Capture request rate, concurrency, and retry amplification during the failure interval.
- 2Map the failure to a concrete quota metric, method, and principal/project scope.
- 3Verify whether errors are sustained hard-quota exhaustion or transient throttling windows.
- 4Replay traffic with controlled ramps and corrected retry policy to validate recovery behavior.
Quota Dimension and Scope Analysis
- -Identify exact quota key and scope from diagnostics (example: per-minute method quota exhausted for one service account).
- -Confirm billing or quota project mapping in user-credential flows (example: requests charge an unintended quota project and exhaust its limits).
Retry Budget and Traffic Shaping
- -Inspect retry fan-out to prevent self-amplifying load (example: three nested retries across client, worker, and gateway layers).
- -Introduce smoothing controls for burst producers (example: token-bucket limiter at ingress keeps request rate below short-window thresholds).
How to Verify the Fix
- -Run controlled load tests and confirm RESOURCE_EXHAUSTED remains below error-budget thresholds.
- -Verify retry paths follow jittered exponential policy and do not create secondary bursts.
- -Monitor quota headroom and sustained throughput after production rollout.
How to Prevent Recurrence
- -Define service-level retry standards with centralized backoff and retry-budget enforcement.
- -Set proactive alerts on quota-utilization slopes, not only hard-limit breaches.
- -Use adaptive throttling and queue backpressure to flatten producer bursts automatically.
Pro Tip
- -reserve operational quota headroom for incident traffic by capping non-critical batch jobs during peak windows.
Decision Support
Compare Guide
AWS ThrottlingException vs GCP RESOURCE_EXHAUSTED
Compare AWS ThrottlingException and GCP RESOURCE_EXHAUSTED to separate rate limiting from quota/resource exhaustion and choose the remediation path.
Compare Guide
429 Too Many Requests vs 503 Service Unavailable
Use 429 for caller-specific throttling and 503 for service-wide outages, so retry behavior, escalation paths, and incident ownership stay correct.
Playbook
Rate Limit Recovery Playbook (429 / ThrottlingException / RESOURCE_EXHAUSTED)
Use this playbook to separate transient throttling from hard quota exhaustion and apply retry, traffic-shaping, and quota-capacity fixes safely.
Official References
Provider Context
This guidance is specific to GCP services. Always validate implementation details against official provider documentation before deploying to production.