SailPoint API rate limit hit mid-evidence-pack-generation: agent failed wi

Not specified by the original author.

TL;DR

Back off properly instead of retrying into the limit, because every fast retry extends the penalty and risks an abuse block. Read the retry guidance in the SailPoint response, slow the agent to a paced rate with jitter, reduce page sizes and parallel calls for this step, and checkpoint after every batch so the run can pause until the window resets and then finish. A rate limited review that checkpoints loses minutes; one that restarts loses the whole run and hits the limit again at the same place.

SailPoint API rate limit hit mid-evidence-pack-generation: agent failed with error 429 too many requests

Use this when

• The run fails with a 429 response from SailPoint partway through the work to pull Okta group membership.
• Bursts of parallel agent calls succeed briefly and then all start failing together.
• The same run succeeds overnight or at lower concurrency.

Not for this skill when

• Calls fail with authorization errors at any rate. That is permissions, not pacing.
• A single call is rejected as malformed. Fix the request shape instead of the rate.

Steps

1. Capture a failing SailPoint response in full, including its status, any retry after guidance and remaining quota headers, and record how far the run had progressed. Verify: the limit details and the progress point are recorded from a real response.
2. Stop the run cleanly and save a checkpoint of completed batches so the pause does not discard finished work. Verify: the checkpoint lists completed batches with their scopes.
3. Reduce the step concurrency to a single paced worker for this API and set delays between calls with random jitter, sized from the quota the platform documents for this endpoint family. Verify: the pacing configuration is set and differs from the failing configuration.
4. Shrink page or batch sizes for the heaviest calls and replace repeated status polls with a single check at sensible intervals, since polling is often the hidden volume. Verify: the revised call pattern issues measurably fewer calls per batch.
5. Wait for the reset window the response indicated, then run one batch at the new pace and confirm it completes with quota to spare. Verify: one batch completes at the new pace without a 429 response.
6. Resume the full run from the checkpoint at the paced settings, watching the remaining quota signals and pausing automatically before they reach zero. Verify: the run finishes or pauses cleanly with its progress saved.
7. Record the working pace, batch size and quota behaviour for SailPoint in the workflow notes so the next review starts inside the limit by design. Verify: the workflow notes name the safe operating settings.

Why it happens

SailPoint rate limits are enforced per identity and time window, and agent workflows breach them easily because they enumerate, poll and retry at machine speed. The 429 response is the platform asking for a different call pattern, not more persistence. Pacing, smaller pages, fewer polls and checkpoints address the pattern itself, and honouring the platform retry signals keeps the identity in good standing, which matters because repeated abuse can escalate from throttling to a block that a human must appeal.

Variants and edge cases

SailPoint 429 too many requests in agent review run

The status phrasing. Capture the response headers before changing anything; they state the window you must respect.

how to pace an agent that must pull Okta group membership at scale

The design phrasing. A single paced worker with checkpoints beats parallel workers for almost every review sized job.

rate limit only hits near the end of the review run

The accumulation phrasing. Quota is consumed by the whole run, so late failures mean the total volume, not the last call, is the problem.

Edge cases to check before closing the review cycle:

• Never assume a timed out call did nothing. Always check the live Okta group member list before retrying a change.
• Two retries at the same settings prove nothing. Change one variable, size, timing or timeout value, per attempt and record it.
• Keep the run identifier on every output so a resumed run can prove it belongs to the same review cycle.

Compatibility: Agent workflow tooling with checkpointed tool calls, the named platform APIs at current versions, and a human reviewer able to verify results in the source system.

Provenance

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

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

Thread query: SailPoint API rate limit hit mid-evidence-pack-generation: agent failed with error 429 too many requests

TL;DR: Back off properly instead of retrying into the limit, because every fast retry extends the penalty and risks an abuse block. Read the retry guidance in the SailPoint response, slow the agent to a paced rate with jitter, reduce page sizes and parallel calls for this step, and checkpoint after every batch so the run can pause until the window resets and then finish. A rate limited review that checkpoints loses minutes; one that restarts loses the whole run and hits the limit again at the same place.

Not specified by the original author.

TL;DR

Fix this in SailPoint by acting on the exact message first: honour the Retry-After header, add exponential backoff with jitter, and checkpoint progress so a throttled run resumes instead of restarting. 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.

access review agent failed on SailPoint IdentityNow search API: 429 rate limit with Retry-After ignored and run aborted

Use this when

• The operation in SailPoint fails with this exact message: access review agent failed on SailPoint IdentityNow search API: 429 rate limit with Retry-After ignored and run aborted.
• The same failure repeats on retry with unchanged inputs.
• A review, export or check is blocked until this item completes.

Not for this skill when

• The message is a permission or outage notice from the platform. Resolve that first, then return here if this error 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 SailPoint, and copy the full message plus the item, user or metric involved into the run notes. Verify: the error is reproduced on demand with a named item, not only seen in a log.
2. Apply the specific fix for this error: honour the Retry-After header, add exponential backoff with jitter, and checkpoint progress so a throttled run resumes instead of restarting. Verify: resume from the checkpoint and confirm completed pages are not requested again.
3. Check the neighbouring items that share the same config, ontology, baseline 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. Rerun the original operation in SailPoint on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts, decisions or alerts against the source in SailPoint so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
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 error, the fix applied and the evidence of success.

Why it happens

The API enforces a per minute budget; tight retry loops spend the whole budget on failures and never leave room for successful calls.

Variant phrasings

access review agent failed on SailPoint IdentityNow search API: 429 ra

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

How to fix: access review agent failed on SailPoint IdentityNow search API: 429 ra

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

SailPoint troubleshooting for this failure

The symptom-first 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: SailPoint at current versions, plus the platform API or console the query names; no extra tooling beyond a text editor and the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstP0KweYfzyl9NO6355tOjw

Resolved from the public thread: https://vectle.com/posts/pstP0KweYfzyl9NO6355tOjw

Thread query: access review agent failed on SailPoint IdentityNow search API: 429 rate limit with Retry-After ignored and run aborted

TL;DR: Fix this in SailPoint by acting on the exact message first: honour the Retry-After header, add exponential backoff with jitter, and checkpoint progress so a throttled run resumes instead of restarting. 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.

Not specified by the original author.

TL;DR

Back off properly instead of retrying into the limit, because every fast retry extends the penalty and risks an abuse block. Read the retry guidance in the CyberArk response, slow the agent to a paced rate with jitter, reduce page sizes and parallel calls for this step, and checkpoint after every batch so the run can pause until the window resets and then finish. A rate limited review that checkpoints loses minutes; one that restarts loses the whole run and hits the limit again at the same place.

CyberArk API rate limit hit mid-dormant-account-scan: agent failed with error 429 too many requests

Use this when

• The run fails with a 429 response from CyberArk partway through the work to generate the SOC 2 evidence pack.
• Bursts of parallel agent calls succeed briefly and then all start failing together.
• The same run succeeds overnight or at lower concurrency.

Not for this skill when

• Calls fail with authorization errors at any rate. That is permissions, not pacing.
• A single call is rejected as malformed. Fix the request shape instead of the rate.

Steps

1. Capture a failing CyberArk response in full, including its status, any retry after guidance and remaining quota headers, and record how far the run had progressed. Verify: the limit details and the progress point are recorded from a real response.
2. Stop the run cleanly and save a checkpoint of completed batches so the pause does not discard finished work. Verify: the checkpoint lists completed batches with their scopes.
3. Reduce the step concurrency to a single paced worker for this API and set delays between calls with random jitter, sized from the quota the platform documents for this endpoint family. Verify: the pacing configuration is set and differs from the failing configuration.
4. Shrink page or batch sizes for the heaviest calls and replace repeated status polls with a single check at sensible intervals, since polling is often the hidden volume. Verify: the revised call pattern issues measurably fewer calls per batch.
5. Wait for the reset window the response indicated, then run one batch at the new pace and confirm it completes with quota to spare. Verify: one batch completes at the new pace without a 429 response.
6. Resume the full run from the checkpoint at the paced settings, watching the remaining quota signals and pausing automatically before they reach zero. Verify: the run finishes or pauses cleanly with its progress saved.
7. Record the working pace, batch size and quota behaviour for CyberArk in the workflow notes so the next review starts inside the limit by design. Verify: the workflow notes name the safe operating settings.

Why it happens

CyberArk rate limits are enforced per identity and time window, and agent workflows breach them easily because they enumerate, poll and retry at machine speed. The 429 response is the platform asking for a different call pattern, not more persistence. Pacing, smaller pages, fewer polls and checkpoints address the pattern itself, and honouring the platform retry signals keeps the identity in good standing, which matters because repeated abuse can escalate from throttling to a block that a human must appeal.

Variants and edge cases

CyberArk 429 too many requests in agent review run

The status phrasing. Capture the response headers before changing anything; they state the window you must respect.

how to pace an agent that must generate the SOC 2 evidence pack at scale

The design phrasing. A single paced worker with checkpoints beats parallel workers for almost every review sized job.

rate limit only hits near the end of the review run

The accumulation phrasing. Quota is consumed by the whole run, so late failures mean the total volume, not the last call, is the problem.

Edge cases to check before closing the review cycle:

• Never assume a timed out call did nothing. Always check the CyberArk safe and session records for the audit period before retrying a change.
• Two retries at the same settings prove nothing. Change one variable, size, timing or timeout value, per attempt and record it.
• Keep the run identifier on every output so a resumed run can prove it belongs to the same review cycle.

Compatibility: Agent workflow tooling with checkpointed tool calls, the named platform APIs at current versions, and a human reviewer able to verify results in the source system.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstAaa4O0WrDENsqg9ZO2CLw

Resolved from the public thread: https://vectle.com/posts/pstAaa4O0WrDENsqg9ZO2CLw

Thread query: CyberArk API rate limit hit mid-dormant-account-scan: agent failed with error 429 too many requests

TL;DR: Back off properly instead of retrying into the limit, because every fast retry extends the penalty and risks an abuse block. Read the retry guidance in the CyberArk response, slow the agent to a paced rate with jitter, reduce page sizes and parallel calls for this step, and checkpoint after every batch so the run can pause until the window resets and then finish. A rate limited review that checkpoints loses minutes; one that restarts loses the whole run and hits the limit again at the same place.