SERVICE_NOT_ENABLED_AE on App Engine: what causes it and how to fix
| Service | App Engine |
|---|---|
| Cloud | Google Cloud (GCP) |
| Guide type | Procedure |
| Skill level | Intermediate to advanced |
| Time | 15 - 60 minutes depending on account size |
Running into SERVICE_NOT_ENABLED_AE on App Engine, what causes it and how to fix on App Engine 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 service_not_enabled_ae on app engine, what causes it and how to fix actually involves on App Engine
The SERVICE_NOT_ENABLED_AE error from AWS typically surfaces with the message "App Engine Admin API has not been used in project before". The error code itself is what you grep for in AWS re:Post or in AWS Support cases, not the human-readable line.
On App Engine, 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
Reproduce the failure with the gcloud CLI in --debug mode. The full SigV4 request payload it emits, plus the exact endpoint URL it resolved to, is what Google Cloud Support uses to verify policy, region, or parameter issues without you having to share IAM credentials. Save the debug output to a file with gcloud ... --debug 2> debug.log and you can search it for the failed aws.request entry.
Check Cloud Monitoring Logs for the calling service. Lambda, ECS, EKS, Step Functions, API Gateway, and most managed services write detailed traces to Cloud Monitoring Logs under predictable log group names. Use Cloud Monitoring Logs Insights with fields @timestamp, @message | filter @message like /ERROR/ | sort @timestamp desc | limit 50 to surface the most recent failures.
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.
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.
If the issue points at IAM, do not start by adding * to a policy. Use IAM Policy Troubleshooter and IAM Recommender against the failed action to see the minimum scope. Adding * is the fastest way to fail your next Google Cloud Architecture Framework security review, and it usually does not even fix the issue because the explicit deny is often coming from a higher level (Org Policy, RCP, or permission boundary), not a missing allow.
If networking is suspect, use Network Intelligence Connectivity Tests. It is the only tool that simulates the full ENI-to-ENI path including firewall rules, hierarchical firewall policies, routes, and VPC Service Controls perimeters in one call. Manual trace is slower and misses transitive issues. The analyzer charges $0.10 per analysis - cheaper than a 30-minute call with your network team.
Automate this fix so you do not do it twice
Automate the fix with the gcloud CLI
The CLI one-liner pattern for App Engine operations is roughly: gcloud app describe RESOURCE --format=json --filter ... to read state, gcloud app update RESOURCE --quiet to apply the change, and gcloud app 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 app describe RESOURCE --format=json --filter 'Resources[?Status==`FAILED`].[Id,Reason]' --output table
gcloud app modify-... --resource-id RESOURCE_ID --no-dry-run
gcloud app 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('app', 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.app"], "detail-type": ["Google Cloud API Call via Cloud Audit Logs"], "detail": { "errorCode": ["AccessDenied", "ThrottlingException"] }
}
Common pitfalls and what to watch for
A subtle pitfall on App Engine is that the Cloud Console and the SDK can disagree about resource state during a configuration change. Console UI is cached for performance and may show the old config for up to 10 minutes after you change it via API or Deployment Manager or Terraform. Always confirm with describe-* CLI calls during a change window, not with screenshots from the Console.
The other pitfall: assuming that an automated remediation is correct because it succeeded. A Lambda that fires on a Cloud Monitoring alert policy and runs a remediation step should also publish a metric for every remediation; sudden surges in auto-fix invocations are themselves an outage signal. Otherwise you can hide a slow-burn regression behind a quiet remediation loop for weeks.
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 App Engine resources support describe + export to JSON via CLI - capture that to source control before you start.
- Know your rollback path. Some App Engine 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 app 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 App Engine
- 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:
- MEMORY_LIMIT_EXCEEDED_AE on App Engine, what causes it and how to fix
- CONFIG_INVALID_APP_YAML on App Engine: what causes it and how to fix
- CRON_FAILED on App Engine, what causes it and how to fix
- DEADLINE_EXCEEDED_DEPLOY on App Engine, what causes it and how to fix
- DeadlineExceededError on App Engine, what causes it and how to fix
- DISPATCH_RULES_INVALID on App Engine: what causes it and how to fix