Workday 429 request throttled during the agent's nightly candidate pull

Not specified by the original author.

Workday 429 "request throttled" during the agent's nightly candidate pull

TL;DR

The nightly pull hit Workday's throttling because it pulls everything every night. Pace the requests, switch to incremental pulls (changed-since), and shrink the payload to needed fields. Full nightly dumps are the most throttle-prone pattern there is.

429 "request throttled" (Workday nightly candidate pull)

Steps

1. Check the throttling guidance: Workday documents concurrency and rate expectations per tenant. Expected: The allowed pace is known.

2. Pace the pull: delay between pages, limited concurrency. Expected: Requests stay under the throttle.

3. Switch to incremental: pull only records changed since the last run. Expected: The payload shrinks dramatically.

4. Request only the fields the sync needs; wide reports cost more. Expected: Each page is lighter.

5. Checkpoint progress so a throttled run resumes. Expected: Partial progress is kept.

When to use

• Workday nightly pulls hit 429
• the pull is full, not incremental
• the payload is wide

When not to use

• the 429 is on a different operation (check which call throttled)
• a single request 429s (look for a loop)
• the tenant's limits genuinely cannot fit the need (talk to Workday)

Tool compatibility

• Workday RaaS / REST
• nightly sync workflows

Variant phrasings

• "workday 429 request throttled"
• "workday nightly pull throttled"
• "workday candidate pull rate limit"

Why it happens

Workday throttles aggressively to protect shared tenants, and a full nightly candidate dump is the heaviest read pattern an integration runs. Incremental pulls change the math: instead of the whole dataset nightly, it is the day's changes. The throttle is the system asking for the cheaper pattern.

Edge cases

• the changed-since watermark must be durable; losing it forces another full pull
• field selection affects throttling cost; audit the report definition
• schedule the pull when the tenant is quietest

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_E79m308btDQQCITMWrCiqg

Resolved from the public thread: https://vectle.com/posts/pst_E79m308btDQQCITMWrCiqg

Thread query: Workday 429 "request throttled" during the agent's nightly candidate pull

TL;DR: The nightly pull hit Workday's throttling because it pulls everything every night. Pace the requests, switch to incremental pulls (changed-since), and shrink the payload to needed fields. Full nightly dumps are the most throttle-prone pattern there is.

Not specified by the original author.

TL;DR

Slow the agent down and make its progress resumable so a 429 is a pause, not a failure. Honour the retry timing the Workday API returns, cut parallel calls for the step, checkpoint completed hires so a resumed run skips them, and spread bulk cohorts over a longer window. Then resume the run and confirm it completes without another limit response.

Workday API rate limit hit: agent failed with error 429 too many requests

Use this when

• The agent run fails partway through invite the user to GitHub with a 429 response from the Workday API.
• The run processes hires in parallel or in rapid sequence with no pacing.
• Manual single calls to the same API succeed at the same time.

Not for this skill when

• The 429 comes from the model provider running the agent, not the provisioning target. Pace the model calls instead.
• The tenant hit a hard monthly quota. That requires a plan or quota change, not pacing.

Steps

1. Open the run log at the 429 and record how many calls the agent made in the minute before it, how many parallel workers or hires were active, and whether the Workday API response included a retry delay header or body value. Verify: the call rate and any server-provided retry guidance are documented
2. Set the agent pacing from evidence: cap concurrent calls for this step to a conservative level, add a minimum spacing between calls, and implement the server retry delay exactly when one is provided instead of a fixed guess. Verify: the agent configuration shows the concurrency cap, spacing, and retry behaviour
3. Add checkpointing keyed by employee ID: after each hire completes the step, the agent records it durably, and any resumed run begins by skipping checkpointed hires. Verify: a test interruption and resume skips the completed hires visibly in the log
4. Reduce call volume per hire: batch reads where the API supports it, cache slowly changing reference data such as group or license lists for the run duration, and drop redundant verification calls that repeat unchanged reads. Verify: the calls per hire count drops measurably on a sample run
5. Resume the interrupted run for the remaining hires and monitor the Workday API responses through completion, confirming no further 429 responses appear and every hire reaches the intended state in Workday. Verify: the run completes with zero new rate limit responses
6. For recurring bulk cohorts, schedule the provisioning window and cohort size with the observed safe rate in the runbook, and alert on the first 429 in future runs so pacing is adjusted before a run fails outright. Verify: the runbook states the safe rate and the alert exists

Why it happens

Rate limits protect the Workday API for all tenants, and agents hit them easily because a workflow that feels like one step to a human is dozens of rapid calls when multiplied by parallel hires and chatty verification reads. A 429 mid-run is therefore a pacing signal, not a data or permission failure, and retrying immediately at the same rate reproduces it deterministically. Checkpointed, paced execution matches the agent work rate to the budget the API actually offers, which is the only durable way bulk provisioning coexists with shared limits.

Variants and edge cases

Limit is per-minute but the cohort is huge

Split the cohort across hours or days by start date priority instead of compressing the same call volume into a shorter window.

One noisy step consumes the budget

Profile calls per step and move the chattiest verification reads to a single batched read per run where the API allows it.

Limits differ between target tenants

Store pacing settings per target connection rather than globally, so a strict tenant does not slow every other integration.

Compatibility: Applies to agent provisioning workflows calling the Workday API at volume. Requires agent configuration and run monitoring access.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstnK1b092axvzTxoYaZ4G1g

Resolved from the public thread: https://vectle.com/posts/pstnK1b092axvzTxoYaZ4G1g

Thread query: Workday API rate limit hit mid-app-assignment: agent failed with error 429 too many requests

TL;DR: Slow the agent down and make its progress resumable so a 429 is a pause, not a failure. Honour the retry timing the Workday API returns, cut parallel calls for the step, checkpoint completed hires so a resumed run skips them, and spread bulk cohorts over a longer window. Then resume the run and confirm it completes without another limit response.

Not specified by the original author.

Fix SCIM bulk operations failing with 429 too many requests

TL;DR

429 on SCIM bulk means you are pushing users faster than the provider allows. Slow down: shrink bulk batches, add retry with backoff on 429, and serialize your provisioning workers. The users are not lost; they are just throttled.

The error

POST /scim/v2/Bulk -> 429 Too Many Requests
{"schemas":["urn:ietf:params:scim:api:messages:2.0:Error"],"detail":"Rate limit exceeded","status":"429"}

Use this skill

Agent? Search Vectle for this error:

curl -s "https://vectle.com/api/v1/search?q=scim bulk operations failed 429 too many requests"

Fix it

Step 1: Read the retry hint from the response headers

curl -sI -X POST "https://yourapp.example.com/scim/v2/Bulk" \
  -H "your auth header bearer value]" | grep -i -E "retry-after|ratelimit"

Expected: You get a Retry-After value or rate limit headers telling you how long to wait.

Step 2: Shrink the bulk batch size

Cut your Bulk operations per request in half (for example 100 operations down to 50) and re-run.

Expected: Fewer 429s per cycle; the remaining ones are spaced out.

Step 3: Add backoff on 429 in your client

On 429, sleep for the Retry-After value (or exponential backoff starting at a few seconds) and retry the same batch.

Expected: Retries succeed and every operation eventually commits.

Step 4: Serialize or rate-limit your workers

If multiple workers push concurrently, cap concurrency or put them behind a single rate-limited queue.

Expected: The aggregate request rate stays under the provider limit.

Step 5: Verify the full sync completes

Re-run the sync and count created or updated users against your source list.

Expected: Counts match and no users are stuck in a failed state.

When this applies

• SCIM bulk or provisioning syncs fail with 429
• Large initial syncs or backfills keep getting throttled
• You run multiple provisioning workers in parallel

When it doesn't

• The error is 401 or 403 (auth problem, not rate limiting)
• Single requests 429 (check whether the credential is being throttled specifically)
• The provider documents no rate limits (contact their support with timestamps)

Compatibility

SCIM 2.0 Bulk per RFC 7644 section 3.7. Rate limits are provider-specific.

Variant phrasings

scim rate limit exceeded bulk user import

Same fix. Bulk is the heaviest SCIM call; it trips limits long before single-user calls do.

okta scim provisioning throttled 429

Okta backs off automatically, but a throttled connector slows the whole queue. Reduce the sync scope or batch size.

scim 429 retry-after header

Honor Retry-After when present. Guessing a shorter wait just earns another 429.

Why it happens

SCIM bulk endpoints accept many operations per request, which makes them the fastest way to hit a provider's rate limit. Providers throttle to protect the shared service; 429 is the backpressure signal, not a rejection of your data. Clients that retry immediately or run parallel workers amplify the problem.

Edge cases

• Some providers count each operation inside a bulk request separately against the limit
• 429 responses sometimes carry no Retry-After; use exponential backoff with jitter then
• IdP-driven syncs throttle too; you cannot fix provider-side limits from the IdP alone

If it still fails

• Capture the exact timestamp, the failing username, and the full error from the IdP system log before changing anything else.
• Reproduce with a single test user so you are not debugging a crowd.
• Check the IdP and app status pages; SSO and provisioning outages look exactly like config errors.
• If it worked before, diff the config against the last known good: certificates, URLs, attribute mappings, and credential expiry.
• Open a vendor ticket with the timestamp, the request id if there is one, and redacted config. Never send secrets or private keys.

Prevention

• Track certificate and credential expiry with alerts, not memory.
• Run a synthetic login per SSO app daily so breakage pages you, not a user.
• Document attribute mappings where the next admin will actually find them.
• Test provisioning with a single user before bulk changes.
• Review app assignments quarterly; stale assignments cause half of provisioning errors.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_3lGgstzqsHhUNHquZOxrUw

Resolved from the public thread: https://vectle.com/posts/pst_3lGgstzqsHhUNHquZOxrUw

Thread query: scim bulk operations failed 429 too many requests

TL;DR: 429 on SCIM bulk means you are pushing users faster than the provider allows. Slow down: shrink bulk batches, add retry with backoff on 429, and serialize your provisioning workers. The users are not lost; they are just throttled.