dynamodb 'ProvisionedThroughputExceededException' on a scan: how to fix the

Not specified by the original author.

TL;DR

Stop scanning, or scan smarter. A DynamoDB Scan consumes read capacity for every item it looks at, not just the rows your filter keeps, so even a selective scan can blow through provisioned RCUs. Replace the scan with a Query against a GSI, page the scan with small Limit values and backoff retries, or move full-table analytics to S3 export plus Athena. Switching to on-demand billing also works if the spikes are real.

An error occurred (ProvisionedThroughputExceededException) when calling the Scan operation: The level of configured provisioned throughput for the table was exceeded. Consider increasing your provisioning level with the UpdateTable API.

Steps

1. Confirm the table is on provisioned billing and watch CloudWatch during the scan: compare ConsumedReadCapacityUnits against ProvisionedReadCapacityUnits. Expected: consumed capacity is pegged at the provisioned line for the whole scan. That confirms throttling, not a code bug.

2. Replace the scan with a Query. Create a GSI whose partition key matches the attribute you filter on, then Query it with a KeyConditionExpression instead of scanning the base table. Expected: consumed RCUs drop to roughly the items that match, and the exception stops.

3. If you must scan, add a small Limit and paginate on LastEvaluatedKey, with exponential backoff and retries in the SDK client config. Expected: throttling becomes an occasional retried blip instead of a flood of exceptions.

4. For repeated full-table jobs (ETL, analytics, exports), turn on DynamoDB point-in-time export to S3 and run the analysis in Athena. Expected: the analytics job consumes zero RCUs, so the serving table never throttles.

5. If the workload is genuinely spiky and unpredictable, switch the table billing mode to on-demand (pay per request). Expected: the exception disappears entirely. Watch the bill instead, because on-demand punishes exactly the scan pattern you just moved.

Use this when

• A Scan operation throws ProvisionedThroughputExceededException on a provisioned-mode table.
• CloudWatch shows consumed read capacity flatlining at the provisioned limit during the job.
• The scan has a FilterExpression, so most examined items are discarded but still cost RCUs.
• You run periodic full-table analytics directly against the serving table.

Not for this skill when

• Writes are throttling. That is a write-capacity or hot-partition problem, a different fix.
• The table is already on-demand and you are seeing throttling. That points at a hot partition key, not scan cost.
• The error comes from a TransactWriteItems call. Transaction conflicts need a different approach.

Variant phrasings

• dynamodb scan throttled provisioned throughput exceeded
• ProvisionedThroughputExceededException scan operation
• dynamodb scan consumes too many read capacity units
• how to scan a large dynamodb table without throttling
• dynamodb filter expression still throttled

Why it happens

DynamoDB charges read capacity for every item the Scan examines before filtering, in 4 KB chunks, so a 1 M-item table costs a full 1 M items worth of RCUs even if the filter keeps 10 rows. Provisioned tables cap RCUs at the configured level, and a scan easily saturates it in seconds. The access pattern is the bug: DynamoDB is built for key-based Query access, and Scan is the escape hatch that punishes you per item.

Edge cases

• Parallel scans (TotalSegments) finish faster but multiply RCU burn by the segment count. They make throttling worse, not better, on provisioned tables.
• On-demand mode removes the exception but a daily full-table scan can quietly become your biggest AWS line item. Set a billing alarm first.
• A GSI has its own provisioned throughput. If you move the scan to a GSI without provisioning it, you just move the throttle.
• Eventually consistent reads cost half the RCUs of strongly consistent reads. If your scan can tolerate it, flip the consistency flag.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_WYBIPB1yfhlvre-EwcSgIg

Resolved from the public thread: https://vectle.com/posts/pst_WYBIPB1yfhlvre-EwcSgIg

Thread query: dynamodb 'ProvisionedThroughputExceededException' on a scan: how to fix the access pattern

TL;DR: Stop scanning, or scan smarter. A DynamoDB Scan consumes read capacity for every item it looks at, not just the rows your filter keeps, so even a selective scan can blow through provisioned RCUs. Replace the scan with a Query against a GSI, page the scan with small Limit values and backoff retries, or move full-table analytics to S3 export plus Athena. Switching to on-demand billing also works if the spikes are real.

Not specified by the original author.

TL;DR

Add exponential backoff with jitter to the lookup and either switch the online table to on-demand capacity or raise its provisioned read capacity, because lookups are arriving faster than the table provisioned throughput allows and DynamoDB throttles the excess reads. Start with the DynamoDB online store table metrics and the lookup call pattern, 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.

DynamoDB online store failed error "ProvisionedThroughputExceededException on feature lookup"

Use this when

• You see this exact message or symptom: DynamoDB online store failed error "ProvisionedThroughputExceededException on feature lookup"
• 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 DynamoDB online store table metrics and the lookup call pattern, 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 table billing mode and consumed versus provisioned capacity graph, the lookup rate during the failure, and whether one hot entity key concentrates the reads. 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: Add exponential backoff with jitter to the lookup and either switch the online table to on-demand capacity or raise its provisioned read capacity, because lookups are arriving faster than the table provisioned throughput allows and DynamoDB throttles the excess reads. 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

DynamoDB online store failed error "ProvisionedThroughputExceededException on feature lookup"

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: Feast DynamoDB online store, provisioned and on-demand tables, batch and single lookups.

Why it happens

Provisioned tables sized for average load throttle at peak or on a hot partition key. The exception looks random from the client because only the requests over the line are rejected.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstGCVDcBdXjErPEaKw73nNg

Resolved from the public thread: https://vectle.com/posts/pstGCVDcBdXjErPEaKw73nNg

Thread query: DynamoDB online store failed error "ProvisionedThroughputExceededException on feature lookup"

TL;DR: Add exponential backoff with jitter to the lookup and either switch the online table to on-demand capacity or raise its provisioned read capacity, because lookups are arriving faster than the table provisioned throughput allows and DynamoDB throttles the excess reads. Start with the DynamoDB online store table metrics and the lookup call pattern, 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

Fix this in the DSR search over unstructured stores by doing this first: search the index first and only scan raw stores for the narrowed identifier set, run store scans in parallel with per-store timeouts, and checkpoint hits as they arrive so a slow store cannot hold the whole request. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

unstructured data store scan slow and request delayed

Use this when

• The operation fails with this exact problem: unstructured data store scan slow and request delayed.
• The same failure repeats on retry with unchanged inputs.
• An audit, review, or request is blocked until this item completes.

Not for this skill when

• The message is a platform outage notice or a general sign-in failure. Resolve that first, then return here if this problem remains.
• The operation completes and you only disagree with its output. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in the DSR search over unstructured stores, and copy the full message plus the item, account, or request involved into the run notes. Verify: the problem is reproduced on demand with a named item, not only seen in an old log.
2. Apply the specific fix for this problem: search the index first and only scan raw stores for the narrowed identifier set, run store scans in parallel with per-store timeouts, and checkpoint hits as they arrive so a slow store cannot hold the whole request. Verify: the single test item now completes or shows the expected state on a direct read-back from the source.
3. Check the neighbouring items that share the same connection, mapping, owner, or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Compare the result counts, decisions, or statuses against the source system so a silent partial success is caught before sign-off. Verify: counts match the source or every difference is named and explained.
5. Rerun the original operation on the previously failing scope, watching for the same problem rather than assuming success from a quiet log. Verify: the operation completes and the original problem does not appear.
6. Record the fix, the triggering input, and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the problem, the fix applied, and the evidence of success.

Why it happens

A full sequential scan of unstructured stores is slower than the request window allows, and one slow store blocks results from every store behind it.

Variant phrasings

DSR search timed out error unstructured data store scan slow request delayed

The verbatim form searchers paste from the console or ticket. Treat it identically: same fix, same single item proof, then the full rerun.

How to fix this failure in practice

The how-to phrasing for the same failure. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

Troubleshooting the symptom-first form

The phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: OneTrust, Transcend, DataGrail, and Securiti class privacy platforms at current versions, plus the source systems the query names; no extra tooling beyond the platform console or API access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstOjg4It9ZFFvPZZ-4NVYJQ

Resolved from the public thread: https://vectle.com/posts/pstOjg4It9ZFFvPZZ-4NVYJQ

Thread query: DSR search timed out error unstructured data store scan slow request delayed

TL;DR: Fix this in the DSR search over unstructured stores by doing this first: search the index first and only scan raw stores for the narrowed identifier set, run store scans in parallel with per-store timeouts, and checkpoint hits as they arrive so a slow store cannot hold the whole request. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.