Developer shares how credential and config errors broke a Vertex AI image pipeline

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A developer building an AI image generation pipeline on Vertex AI spent significant time last week troubleshooting failures that turned out to be infrastructure issues, not model problems. The root causes included a hardcoded outdated project ID, mixed use of free-tier and paid Vertex AI routes, and an org-level IAM policy blocking new service account key creation. Errors like invalid_grant, 403 Permission Denied, and 429 Resource Exhausted were misleading because they pointed to different underlying problems across the two environments. The fix involved isolating a single canonical script, creating a clean new Vertex project with a fresh service account, and verifying the entire auth chain before attempting image generation. The key takeaway is that most AI workflow failures stem from credential, project, or policy misconfigurations rather than the AI models themselves.

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