vertex feature store error: entity type not found failed online serving

TL;DR

Look the object up by listing the current workspace rather than trusting the stored id or name, remap the reference to the current id, and fail loudly when a listing has no match. Start in the Vertex AI console feature store page and the ingestion job log, work on one affected item, and prove the fix there before running the full set. Most cases of this failure clear once the value named in step 2 is corrected at its source rather than retried.

vertex feature store error: entity type not found failed online serving

Use this when

• You see this exact message or symptom in Vertex AI Feature Store: vertex feature store error: entity type not found failed online serving
• One run, record, build, or object is affected and you can name it
• A retry without changing anything reproduces the same text

Not for this skill when

• Vertex AI Feature Store fails with a different message and none of the signals here appear
• Nothing has failed yet and you are doing first time setup or general planning
• Every service from this vendor is down for all users, which is a vendor outage to wait out first

Steps

1. Reproduce the failure once in the Vertex AI console feature store page and the ingestion job log and search the log or history for the exact text in the block above, recording the time, the workspace or project, and the one object it names. Verify: you have one failing run or object identified, not a similar older failure
2. Inspect the entity type, the feature value types, the ingest request rows, and the online serving node config, and check the current listing of the named objects, the old versus new id or name, and the remapped reference in the config. Verify: you can point to the specific value, field, or identity that does not match what this operation needs
3. Apply the fix at that source: look the object up by listing the current workspace rather than trusting the stored id or name, remap the reference to the current id, and fail loudly when a listing has no match. Verify: the corrected value or setting is visible in Vertex AI Feature Store itself, not only in a local config file
4. Re-run the original operation on the single affected item first: re-run the import or ingest job for one entity type with a small file, then test online serving for one entity. Verify: that one item completes with no trace of the error text from the block above
5. Check the downstream result a user or the next job would see: a ReadFeatureValues call for one entity id and the feature view sync status in the console. Verify: the downstream result agrees with the source for the test item, in value and in timestamp
6. Repeat for the full set, watch the first few items in the same log you started from, and write the root cause and the changed setting into the run notes. Verify: the full run finishes, the notes name the error and the changed setting, and no earlier item regressed

Variant phrasings

vertex feature store error: entity type not found failed online serving

The subject-first phrasing of the same failure. The fix is the same, start at step 1 and confirm the object the log names.

Vertex AI Feature Store version of this failure

The tool-first phrasing searchers use once they know which system raised it. It is the same underlying problem, not a separate bug.

Why does vertex feature store error: entity type not found failed online serving keep happening after a retry

The repeat-occurrence phrasing. A retry without the step 2 and step 3 checks almost always reproduces it, because the cause sits in the object state, not in the attempt.

Compatibility: Vertex AI Feature Store (Bigtable or optimized online store), gcloud and Python client, CSV or BigQuery ingest sources. The steps assume you can read the job or build log and change the named object in Vertex AI Feature Store.

Why it happens

In Vertex AI Feature Store, this failure usually means the reference the job uses points at an object that was renamed, merged, moved, or never created in this workspace, so the lookup returns nothing. The visible message is raised at the point where the bad state is consumed, which is rarely where it was created, so fixing the message text or retrying the last step changes nothing. Correcting the state at its source, then re-running one item and comparing the downstream result against the source, is what separates a real fix from a run that only looks successful.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_zrRxzWzP9oDZr8EIkONjtg