How to increase Cloud Build timeout above the default 10 minutes
| Service | Cloud Build and Artifact Registry |
|---|---|
| Cloud | Google Cloud (GCP) |
| Guide type | Procedure |
| Skill level | Intermediate to advanced |
| Time | 15 - 60 minutes depending on account size |
Running into How to increase Cloud Build timeout above the default 10 minutes on Cloud Build and Artifact Registry 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 how to increase cloud build timeout above the default 10 minutes actually involves on Cloud Build and Artifact Registry
This task on Cloud Build is one of the more searched operational topics on AWS in the last 12 months. The procedure below is the path that works in a current AWS account with default IAM and standard VPC config.
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
Diff against last known good. The last config change you made is the cause about three quarters of the time, even when the change should not have mattered. Use Asset Inventory snapshot history (or your Terraform / Deployment Manager or Terraform drift report) to see the actual delta between the resource state when it worked and when it broke. The change you remember is often not the only change that happened.
Look at the Cloud Audit Log event for the failed call, even if you are not enrolled in Cloud Logging Log Router. The basic 90-day event history works for most diagnostic purposes and lives in the console under Cloud Audit Logs > Event history. Filter by event name (the API action) and time range; the event JSON shows the exact user identity, source IP, request parameters, and error code.
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.
Solution-focused remediation path
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.
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.
When the fix involves a destructive operation (delete VPC endpoint, swap Cloud KMS key, rotate root credential), do it during a maintenance window with at least one teammate watching. Several Cloud Build and Artifact Registry operations have implicit dependencies that only show up when traffic starts flowing again. Document the rollback path before you start, not during the incident.
Automate this fix so you do not do it twice
Add a Cloud Monitoring alert policy so you know next time
The cheapest way to never see the same incident twice is a Cloud Monitoring alert policy on the metric that would have warned you. For Cloud Build and Artifact Registry, the relevant metrics live under compute.googleapis.com/cloud namespace or under custom metrics published by your Cloud Run service or GKE pod. Set thresholds based on observed normal range plus one or two standard deviations, not on round-number guesses. Cloud Monitoring anomaly-based alert policies remove the threshold-guessing problem entirely for metrics with regular seasonality.
Automate the fix with the gcloud CLI
The CLI one-liner pattern for Cloud Build and Artifact Registry operations is roughly: gcloud cloud describe RESOURCE --format=json --filter ... to read state, gcloud cloud update RESOURCE --quiet to apply the change, and gcloud cloud describe RESOURCE --format=json --filter ... again to verify. Wrap it in a shell script that sets a region variable at the top and exits on first error with set -euo pipefail so a partial run does not leave the account in a half-fixed state.
# Template - replace placeholders with your account specifics
export GOOGLE_CLOUD_REGION=us-central1
export GOOGLE_CLOUD_PROJECT=prod-project
gcloud cloud describe RESOURCE --format=json --filter 'Resources[?Status==`FAILED`].[Id,Reason]' --output table
gcloud cloud modify-... --resource-id RESOURCE_ID --no-dry-run
gcloud cloud describe RESOURCE_ID --query 'Status'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('cloud', 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"]}')
Common pitfalls and what to watch for
The most common pitfall when fixing this on Cloud Build and Artifact Registry 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 Cloud Build and Artifact Registry resources support describe + export to JSON via CLI - capture that to source control before you start.
- Know your rollback path. Some Cloud Build and Artifact Registry 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
gcloud cloud describe-... first, then commit it before you change anything. A few operations are one-way (Cloud KMS key deletion past the pending window, region migration, account closure). Check the Google Cloud doc for the specific API before you commit.aws CLI or SDK calls - those almost always still work.References
- docs.cloud.google.com - official documentation for Cloud Build and Artifact Registry
- Google Cloud Community - community Q&A with Google-staff-verified answers
- Cloud Service Health Dashboard at health.cloud.google.com
- Quotas page in Cloud Console (IAM & Admin > Quotas) and Architecture Framework checklists
Related fixes
Related guides worth a look while you sort this one out:
- BUILD_TIMEOUT on Cloud Build, what causes it and how to fix
- Docker push denied Permission denied Cloud Build SA roles
- AR_PERMISSION_DENIED on Cloud Build, what causes it and how to fix
- AR_REPO_NOT_FOUND on Cloud Build, what causes it and how to fix
- AR_VULNERABILITY_BLOCK on Cloud Build, what causes it and how to fix
- BUILD_PERMISSION_DENIED on Cloud Build: what causes it and how to fix