RESOURCE_IN_USE_BY_ANOTHER_RESOURCE on Persistent Disk: what causes it and how to fix

By Sai Kiran Pandrala · Last verified: 2026-05-31 · Source: Google Cloud Community, community Q&A, Google Cloud docs

Running into RESOURCE_IN_USE_BY_ANOTHER_RESOURCE on Persistent Disk, what causes it and how to fix on Google Persistent Disk is one of the more searched issues on Google Cloud Community and StackOverflow in the last 12 months. Here is what actually moves the needle when the Google Cloud docs are too generic.

What resource_in_use_by_another_resource on persistent disk, what causes it and how to fix actually involves on Google Persistent Disk

The RESOURCE_IN_USE_BY_ANOTHER_RESOURCE error from AWS typically surfaces with the message "RESOURCE_IN_USE_BY_ANOTHER_RESOURCE". The error code itself is what you grep for in AWS re:Post or in AWS Support cases, not the human-readable line.

On Persistent Disk, this most often comes from one of three causes: a missing or restrictive IAM permission, a service-level limit you have hit, or a transient AWS-side capacity issue. The fix path differs by which.

The rest of this page is the structured fix path. Start with diagnose, then remediation, then the automation options so you do not have to do this by hand the next time it surfaces. Verify and safety sections at the end are the discipline that keeps the fix from regressing in production.

Diagnose first, fix second

Run gcloud auth list and gcloud config list first. About one in five 'why does this not work' tickets are actually 'I am in the wrong account' or 'my session expired and the SDK is using stale credentials or ADC pointed at the wrong project'. The 5-second sanity check costs nothing and saves real time when the answer is that simple.

Check the Google Cloud Service Health at status.cloud.google.com and the per-product status board for ongoing service events in your region. About one in ten user-reported outages turn out to be region-scoped Google Cloud service degradation already being tracked. Cloud Service Health also exposes an API and Eventarc events, so you can wire a Lambda hook that pages on-call only when the failure correlates with an active Cloud Service Health event in the same region and service.

Start by capturing the exact Google Cloud error string. The Cloud Console truncates messages in popups, but Cloud Logging keeps the full record in protoPayload.status and protoPayload.methodName. The camelCase error code (e.g. AccessDenied, InsufficientInstanceCapacity, ConditionalCheckFailedException) is the thing you grep for in Google Cloud Community and StackOverflow, not the human-readable sentence next to it. Paste the code into the re:Post search bar in quotes and you will usually land on at least one Google-staff-verified answer within the first three results.

Solution-focused remediation path

When the failure happens in production but not in dev, do not just compare the IAM policy. Compare the Org Policy / RCP at the OU level, the permission boundary on the role, and the resource-based policy on the target. One of those is almost always different between accounts. Policy Intelligence recommendations bundles make this comparison routine.

Most Google Persistent Disk failures fall into one of three buckets: IAM permission gap, networking path break (security group, NACL, or VPC endpoint policy), or service-limit / quota hit. Run that mental triage first - it covers around 80 percent of real-world cases. If the failure does not fit any of the three, it is likely a service-side regression worth opening a re:Post or support ticket for.

For IAM and STS issues, the timing matters. STS sessions can take up to 60 seconds to propagate after creation. The first call right after assume-role can fail with a permission error even when the policy is correct. Add a small retry with backoff before treating the first failure as definitive.

Automate this fix so you do not do it twice

Automate the fix with Python and boto3

For anything you do more than twice, write a small Python script. The boto3 pattern below uses paginators (so it does not blow up on accounts with thousands of resources), explicit region binding, and a dry-run flag that defaults to True. Keep the script under 100 lines; if it grows beyond that, you are building a tool and should put it behind a Lambda with proper logging.

import boto3, sys
DRY_RUN = '--apply' not in sys.argv
client = boto3.client('google', region_name='us-east-1')
paginator = client.get_paginator('describe_...')
for page in paginator.paginate(): for item in page.get('Items', []): if item.get('Status') == 'FAILED': if DRY_RUN: print(f'[dry-run] would fix {item["Id"]}') else: client.modify_...(ResourceId=item['Id']) print(f'fixed {item["Id"]}')

Wire the fix into Eventarc for self-healing

If the failure mode is recurring, automate the remediation instead of the diagnosis. Eventarc Scheduler or rules that watch Cloud Logging events for the specific error code can invoke a Lambda that runs the same fix you would run by hand. The Lambda must be idempotent (re-running it on already-healthy resources must be a no-op) and must emit a Cloud Monitoring metric so you can track how often the auto-fix fires. A spike in auto-fix invocations is itself a signal worth alerting on.

# Eventarc rule pattern (JSON)
{ "source": ["aws.google"], "detail-type": ["Google Cloud API Call via Cloud Audit Logs"], "detail": { "errorCode": ["AccessDenied", "ThrottlingException"] }
}

Codify the fix in Terraform or Deployment Manager

When you reach for the console to fix the same issue twice, the third occurrence should be solved in IaC, not in the console. Terraform's terraform import and Deployment Manager or Terraform's resource importer let you adopt the existing resource into state without recreating it. Lock the corrected attribute behind a variable so the next operator does not have to rediscover the value. Add a moved {} block or Deployment Manager or Terraform resource refactor to keep the diff clean.

Common pitfalls and what to watch for

The most common pitfall when fixing this on Google Persistent Disk is treating it as a one-off rather than as a recurring class of incident. The same misconfiguration tends to happen again after a deployment, a role rotation, or a region migration unless the fix is codified. Add a Org Policy or VPC Service Controls constraint, Organization Policy condition, or Org Policy or VPC Service Controls rule that prevents the same misconfig from being introduced again. Documentation alone does not survive turnover.

Another common trap: confirming the fix on a single resource and assuming the fleet is healthy. Loop your check across every account, region, and IAM principal that could exhibit the same symptom. If you cannot enumerate the affected scope without a script, you do not yet understand the scope.

Verify the fix worked

• Reproduce the original symptom path. If it still surfaces in any account or region or IAM role or service account, you have not fixed it.
• Watch for 24 to 48 hours. Cloud Monitoring metrics and Cloud Asset Inventory can mask issues with cached health for 6 to 12 hours, especially Cloud CDN and Cloud DNS.
• Run a smoke test under realistic load. Happy-path tests miss race conditions and IAM session-cache issues.
• Capture the new state in a runbook so the next person on call does not have to rediscover this. Push it to Confluence or your team wiki, not into Slack.
• If the fix involved a permission change, run IAM Access Analyzer one more time to confirm you did not open a separate hole while closing this one.

Safety, rollback, blast radius

• Test in a non-production account if your environment has Resource Manager and Organization Policy or Cloud Resource Manager (organizations, folders, projects). The cost of one sandbox account is cheaper than one rollback meeting.
• Export the existing config before changing it. Most Google Persistent Disk resources support describe + export to JSON via CLI - capture that to source control before you start.
• Know your rollback path. Some Google Persistent Disk operations are one-way (region migration, account-level feature opt-in, Cloud KMS key deletion past pending window). Confirm reversibility on the Google Cloud doc before you commit.
• Be aware of cross-service impact. IAM role or service account changes ripple to every service trusting that role. Cloud KMS key changes break every workload depending on that key. VPC endpoint changes affect every VPC consumer of that endpoint.
• Maintenance window discipline: if the change touches DNS, certificate rotation, or anything that emits TLS handshakes, line up a window with stakeholder notification, not a heroic mid-day swap.

FAQ

Related fixes

Related guides worth a look while you sort this one out:

• RESOURCE_IN_USE_BY_ANOTHER_RESOURCE on Compute Engine, what causes it and how to fix
• RESOURCE_IN_USE_BY_ANOTHER_RESOURCE on VPC. what causes it and how to fix
• RESOURCE_OPERATION_RATE_EXCEEDED on Persistent Disk: what causes it and how to fix
• ZONE_RESOURCE_POOL_EXHAUSTED on Persistent Disk, what causes it and how to fix
• Cannot on Persistent Disk. what causes it and how to fix
• Disk on Persistent Disk. what causes it and how to fix