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Google Vertex AI: Deployment Failed / Build Error
Current Status: Degraded
Last checked: 17m ago
What We're Seeing Right Now
No recent issues reported. If you're experiencing problems with Google Vertex AI, report below to help the community.
What is this error?
When Google Vertex AI fails to deploy your model or application, the build, packaging, or startup process encountered an error. This can block your production pipeline.
Error Signatures
Deployment failedBuild errorContainer failed to startHealth check failedModel failed to loadOut of memoryStartup timeoutBuild timed outCommon Causes
- Build dependencies failed to install
- Docker image or container configuration error
- Model file too large or corrupted
- Insufficient resources allocated for startup
- Google Vertex AI deployment infrastructure issue
✓ How to Fix It
- Check build logs for specific error messages
- Verify all dependencies and versions
- Test your deployment locally first
- Check resource allocation (RAM, GPU, disk)
- Try redeploying from scratch
- Check this page for Google Vertex AI infrastructure issues
Live Signals
Service Components
Vertex AI API
OperationalRecent Incidents
No incidents in the past 30 days
Frequently Asked Questions
Why did my Google Vertex AI deployment fail?
Check build logs for the specific error. Common causes are dependency issues, resource limits, and model loading errors.
Is Google Vertex AI deployment service down?
Check the live status and reports above.
How do I fix Google Vertex AI deployment errors?
Follow the troubleshooting steps above. Start with build logs and work through dependencies, resources, and configuration.