API rate limits for bulk work order creation?

Question

POST /work_orders — hitting 429 after ~50 sequential creates. Docs mention 100/min but no burst behavior specified. Need to push 5K records for migration. Current approach: for record in dataset:
 POST /work_orders
 sleep(0.6) # naive rate limit Still throttled. What's the actual window? Token bucket vs fixed window? Retry-After header sometimes missing. Also: any batch endpoint planned? Single-request payload limits?

Leo Nakamura · Accepted Answer

Rate limit: 100 req/min per key, sliding window. Burst: undocumented, observed ~10 req/sec before 429. Retry-After: returned when limit exceeded, but not on all edge cases. Bug filed internally. Batch: none. Payload limit 10MB. Workaround: exponential backoff with jitter. API Rate Limits and Best Practices has implementation pattern. Migration: recommend staging chunks <100 with checkpoint resume. Do not parallelize keys — same account, shared limit.

Eli Torres (Staff) · Answer

hey carlos — yeah this one tripped me up too when I first looked at it. the 100/min is actually per API key and it's a sliding window, not fixed, which is why your 0.6s sleep can still hit edge cases depending on when your first request started. the real gotcha: the burst allowance is not documented publicly but in practice you get about 10 requests in a 1-second burst before the throttle kicks in hard. after that it's ~1.67/sec sustained. here's what I ended up with for a similar migration: import time
import requests
from collections import deque

class ThrottledClient:
 def __init__(self, key, rate=100, per=60):
 self.key = key
 self.min_interval = per / rate
 self.requests = deque()
 
 def _wait_if_needed(self):
 now = time.time()
 while self.requests and self.requests[0] < now - 60:
 self.requests.popleft()
 if len(self.requests) >= 100:
 sleep_time = 60 - (now - self.requests[0]) + 0.1
 time.sleep(max(0, sleep_time))
 
 def post(self, payload):
 self._wait_if_needed()
 # ... actual request ...
 self.requests.append(time.time()) re: batch endpoint — nothing public yet, but I've heard rumblings about a bulk import API for Q4. no promises though, and it probably won't cover the full work order schema on first release. heads up: if you're creating with technician assignments in the same payload, that counts as an extra internal call against your limit. might explain why you're seeing fewer effective requests than expected.

Devon Marsh · Answer

YMMV but we ended up using a queue worker with Batch updates vs single record API calls pattern — basically攒 50 records, fire them off with 100ms spacing, then checkpoint. 5K records took ~6 minutes vs estimated 50+ with naive retry loops. worth noting: FieldPulse's external_id field is your friend here. set it to your source record ID so if you have to resume, you can query by that to see what's already migrated. heads up: custom fields in bulk creation have a separate validation path that's stricter than the web UI. we hit this with date formats — ISO 8601 only, no "3/15/2025" style strings.