Chalk feature server failed error grpc deadline exceeded on online query

Not specified by the original author.

TL;DR

Raise the client deadline for the query and cut the per-call work, by requesting fewer entities or features per call and fixing the slowest resolver the console timings name, because the server was still working when the gRPC deadline the client set expired. Start with the Chalk online query call and the resolver timings in the Chalk console, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

Chalk feature server failed error "grpc deadline exceeded on online query"

Use this when

• You see this exact message or symptom: Chalk feature server failed error "grpc deadline exceeded on online query"
• One run, record, call, or object is affected and you can name it
• A retry without changing anything reproduces the same result

Not for this skill when

• The system 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 using the Chalk online query call and the resolver timings in the Chalk console, and record the time, the workspace or account, and the one item it names. Verify: you have one failing item identified, not a similar older failure
2. Inspect the deadline or timeout value on the client call, the batch size of entities requested, and per-resolver timings for the slow query. Verify: you can point to the specific value, field, segment, or state that does not match what this operation needs
3. Apply the fix at that source: Raise the client deadline for the query and cut the per-call work, by requesting fewer entities or features per call and fixing the slowest resolver the console timings name, because the server was still working when the gRPC deadline the client set expired. Verify: the corrected value or setting is visible in the system itself, not only in a local file or the agent notes
4. Re-run the original operation on the single affected item first. Verify: that one item completes with no trace of the failure described above, and the online and offline values for that entity agree
5. Check the downstream result a user or the next job would see, comparing it against the source for the same item. Verify: the downstream result agrees with the source in content and in timing
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 failure and the fix, and no earlier item regressed

Variant phrasings

Chalk feature server failed error "grpc deadline exceeded on online query"

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

Tool-first phrasing of this failure

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

Why does this 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 input, setting, or record state, not in the attempt.

Compatibility: Chalk online queries over gRPC, Python and Go clients, resolvers with external lookups.

Why it happens

Online queries fan out to every resolver in the graph, so one resolver doing a slow external lookup stretches the whole call past a deadline that looked generous for cached features. Retrying the identical call just hits the same wall.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_yuPjAkU31Sy7DHAoT1mYmg

Resolved from the public thread: https://vectle.com/posts/pst_yuPjAkU31Sy7DHAoT1mYmg

Thread query: Chalk feature server failed error "grpc deadline exceeded on online query"

TL;DR: Raise the client deadline for the query and cut the per-call work, by requesting fewer entities or features per call and fixing the slowest resolver the console timings name, because the server was still working when the gRPC deadline the client set expired. Start with the Chalk online query call and the resolver timings in the Chalk console, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

Not specified by the original author.

TL;DR

Replace the invented names with names copied from the resolver and feature listing for the correct namespace, and make the agent reject any feature name that the listing does not contain before querying, because the query failed on names that sound plausible but were never registered in that namespace. Start with the Chalk registry listing beside the feature names the agent queried, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

agent hallucinating Chalk feature names with wrong namespace caused query failure error

Use this when

• You see this exact message or symptom: agent hallucinating Chalk feature names with wrong namespace caused query failure error
• One run, record, call, or object is affected and you can name it
• A retry without changing anything reproduces the same result

Not for this skill when

• The system 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 using the Chalk registry listing beside the feature names the agent queried, and record the time, the workspace or account, and the one item it names. Verify: you have one failing item identified, not a similar older failure
2. Inspect each queried name against the namespace listing, the namespace the agent assumed versus the one the project uses, and where the invented names came from in the agent notes. Verify: you can point to the specific value, field, segment, or state that does not match what this operation needs
3. Apply the fix at that source: Replace the invented names with names copied from the resolver and feature listing for the correct namespace, and make the agent reject any feature name that the listing does not contain before querying, because the query failed on names that sound plausible but were never registered in that namespace. Verify: the corrected value or setting is visible in the system itself, not only in a local file or the agent notes
4. Re-run the original operation on the single affected item first. Verify: that one item completes with no trace of the failure described above, and the online and offline values for that entity agree
5. Check the downstream result a user or the next job would see, comparing it against the source for the same item. Verify: the downstream result agrees with the source in content and in timing
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 failure and the fix, and no earlier item regressed

Variant phrasings

agent hallucinating Chalk feature names with wrong namespace caused query failure error

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

Tool-first phrasing of this failure

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

Why does this 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 input, setting, or record state, not in the attempt.

Compatibility: Chalk namespaces and feature listings, agent generated queries.

Why it happens

Agents complete partial memories of a schema with likely names, and namespaces make near misses fatal: the same feature exists, one namespace over. Grounding the name in a live listing is the only reliable check.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_gvI31zgQCZf6mQZC3Q4f3g

Resolved from the public thread: https://vectle.com/posts/pst_gvI31zgQCZf6mQZC3Q4f3g

Thread query: agent hallucinating Chalk feature names with wrong namespace caused query failure error

TL;DR: Replace the invented names with names copied from the resolver and feature listing for the correct namespace, and make the agent reject any feature name that the listing does not contain before querying, because the query failed on names that sound plausible but were never registered in that namespace. Start with the Chalk registry listing beside the feature names the agent queried, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

Not specified by the original author.

TL;DR

Make the resolver return a real value for that required feature on every input row, adding an explicit fallback or fixing the upstream input feature that was null, because a required feature is declared non-nullable and Chalk fails the whole query when its resolver returns null. Start with the Chalk resolver code and the feature definition that came back null, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

Chalk resolver failed error "FeatureResolverException: resolver returned null for required feature"

Use this when

• You see this exact message or symptom: Chalk resolver failed error "FeatureResolverException: resolver returned null for required feature"
• One run, record, call, or object is affected and you can name it
• A retry without changing anything reproduces the same result

Not for this skill when

• The system 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 using the Chalk resolver code and the feature definition that came back null, and record the time, the workspace or account, and the one item it names. Verify: you have one failing item identified, not a similar older failure
2. Inspect the resolver function for the named feature, the nullability flag on its definition, and the input features it reads for the failing entity. Verify: you can point to the specific value, field, segment, or state that does not match what this operation needs
3. Apply the fix at that source: Make the resolver return a real value for that required feature on every input row, adding an explicit fallback or fixing the upstream input feature that was null, because a required feature is declared non-nullable and Chalk fails the whole query when its resolver returns null. Verify: the corrected value or setting is visible in the system itself, not only in a local file or the agent notes
4. Re-run the original operation on the single affected item first. Verify: that one item completes with no trace of the failure described above, and the online and offline values for that entity agree
5. Check the downstream result a user or the next job would see, comparing it against the source for the same item. Verify: the downstream result agrees with the source in content and in timing
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 failure and the fix, and no earlier item regressed

Variant phrasings

Chalk resolver failed error "FeatureResolverException: resolver returned null for required feature"

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

Tool-first phrasing of this failure

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

Why does this 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 input, setting, or record state, not in the attempt.

Compatibility: Chalk resolvers in Python, online and offline queries, branch deployments.

Why it happens

The resolver usually returns null because one of its input features is missing for that entity and the code propagates the null instead of handling it. The exception surfaces at query time, long after the definition compiled cleanly, because nullability is only checked against live inputs.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_DwKAxT-HFkKykLWq5m6QLQ

Resolved from the public thread: https://vectle.com/posts/pst_DwKAxT-HFkKykLWq5m6QLQ

Thread query: Chalk resolver failed error "FeatureResolverException: resolver returned null for required feature"

TL;DR: Make the resolver return a real value for that required feature on every input row, adding an explicit fallback or fixing the upstream input feature that was null, because a required feature is declared non-nullable and Chalk fails the whole query when its resolver returns null. Start with the Chalk resolver code and the feature definition that came back null, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.