StorageAccountQuotaExceeded
Azure returns `StorageAccountQuotaExceeded` when storage account capacity, ingress/egress, or request-rate limits are exceeded for the workload.
Last reviewed: February 28, 2026|Editorial standard: source-backed technical guidance
What Does Storage Account Quota Exceeded Mean?
Write/read throughput and capacity operations are blocked or throttled until account-level limits and partition pressure are brought back within bounds.
Common Causes
- -Account approaches maximum capacity and can no longer absorb additional data growth.
- -Request volume per partition/account exceeds scalable target thresholds, triggering 503/timeout behavior.
- -Ingress or egress throughput bursts exceed configured regional account limits.
- -Workload is concentrated on hot partitions instead of distributed access patterns.
How to Fix Storage Account Quota Exceeded
- 1Identify the exact exhausted dimension (capacity, request rate, ingress, or egress) using storage metrics.
- 2Reduce hotspot pressure with partition-aware key design and controlled retry backoff.
- 3Apply lifecycle policies to tier or delete stale data and reclaim capacity headroom.
- 4Scale out data/workload across additional storage accounts or request supported limit increases.
Step-by-Step Diagnosis for Storage Account Quota Exceeded
- 1Capture error codes, request IDs, and metric spikes for capacity, ingress, egress, and TPS.
- 2Differentiate hard capacity exhaustion from transient
ServerBusypartition throttling. - 3Trace workload key distribution to detect hot partitions causing localized limit breaches.
- 4Retest after applying load shaping, lifecycle cleanup, or account scale-out changes.
Limit Dimension Attribution
- -Map failure to concrete storage target dimension (example: requests per second exceeded while total capacity is still below account maximum).
- -Inspect region-specific limits and recent quota increase state (example: expected increased ingress limit not yet effective in target region).
Partition Hotspot and Load Pattern Analysis
- -Audit object key design for skew (example: timestamp-prefix keys route heavy traffic to a narrow partition range).
- -Evaluate retry storm amplification (example: aggressive parallel retries convert transient 503 into sustained quota pressure).
How to Verify the Fix
- -Run controlled load tests and verify no quota/throttling errors at target throughput.
- -Confirm storage metrics show stable headroom for capacity and bandwidth dimensions.
- -Validate retry behavior no longer amplifies spikes during temporary backend pressure.
How to Prevent Recurrence
- -Set proactive alerts on capacity and throughput thresholds before saturation points.
- -Design partition-friendly key space and controlled client retry budgets by default.
- -Continuously review lifecycle policies against actual data growth curves.
Pro Tip
- -model expected partition distribution in pre-production and reject key patterns that create predictable hot partitions.
Decision Support
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.
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.
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 Azure services. Always validate implementation details against official provider documentation before deploying to production.