WS_IMAGE_PULL_FAILED on Cloud Workstations, what causes it and how to fix

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

Running into WS_IMAGE_PULL_FAILED on Cloud Workstations, what causes it and how to fix on Google Cloud Workstations 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 ws_image_pull_failed on cloud workstations, what causes it and how to fix actually involves on Google Cloud Workstations

The WS_IMAGE_PULL_FAILED error from AWS typically surfaces with the message "Failed to pull workstation image requires Cloud NAT or Private Google Access". The error code itself is what you grep for in AWS re:Post or in AWS Support cases, not the human-readable line.

On Cloud Workstations, 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

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.

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

Most Google Cloud Workstations 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.

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 quotas are suspect, the Quotas page in Cloud Console (IAM & Admin > Quotas) console shows current usage and the active limit side by side. Request increases through Quotas page in Cloud Console (IAM & Admin > Quotas), not through Support tickets - quota dashboard requests usually approve faster (often within minutes for soft limits) and they are auditable in Cloud Audit Logs. Set up Quotas page in Cloud Console (IAM & Admin > Quotas) + Cloud Monitoring alert policys at 80 percent usage so you get notified before you hit the wall.

Automate this fix so you do not do it twice

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.

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 Google Cloud Workstations, the relevant metrics live under compute.googleapis.com/google 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.

Common pitfalls and what to watch for

The most common pitfall when fixing this on Google Cloud Workstations 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 Cloud Workstations resources support describe + export to JSON via CLI - capture that to source control before you start.
• Know your rollback path. Some Google Cloud Workstations 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:

• RUNNABLE_CONTAINER_PULL_FAILED on Cloud Batch, what causes it and how to fix
• IMAGE_PULL_DENIED on Cloud Run. what causes it and how to fix
• WS_IDE_NOT_REACHABLE on Cloud Workstations, what causes it and how to fix
• WS_TIMEOUT_VM_CREATE on Cloud Workstations. what causes it and how to fix
• WS_VPC_SC_BLOCKED on Cloud Workstations: what causes it and how to fix
• FAILED_PRECONDITION on Cloud Bigtable, what causes it and how to fix