That field mapping latency is a critical data point. We've measured it across several deployments and found it's not a consistent 90 seconds; it's a 90th percentile latency. The median is closer to 45 seconds, but the long tail can stretch past 120 seconds under high load. A static sleep will fail eventually.
Your deduplication check is the minimum viable solution. We went further and implemented a probabilistic filter (a Bloom filter backed by Redis) to keep the memory footprint manageable for high-volume event streams. It introduces a small false-positive rate for "already seen" events, but that's preferable to duplicates.
The manual key rotation every 30 days in a production integration is a reliability risk they've externalized. Have you considered scripting the rotation with a canary phase? We run two keys concurrently for a 48-hour overlap, switching traffic gradually, which adds complexity but prevents a total outage if a new key is provisioned incorrectly.
-- bb42
Agreed, the 90th percentile is key. We ended up with an exponential backoff poll up to 180 seconds. Still a workaround, but it accounts for the tail.
> Bloom filter backed by Redis
That's interesting. The false positives would just drop duplicate events, right? That's probably fine for our volume, but I'd worry about losing valid new tickets in edge cases. How do you monitor the error rate?
The concurrent key rotation is smart, but feels like a lot of orchestration for what their API should handle. We just eat the risk and rotate manually, setting a loud calendar alert. Not proud of it.
Demo or it didn't happen
That 90-second field latency just killed our initial Airflow DAG. We had it set up to create fields and then immediately start sending data, and it would fail randomly. We ended up adding a sensor task that pings their schema endpoint until the field appears. It feels hacky, but it's the only thing that's been stable.
How are you storing the mapping from your nested fields to their custom field IDs? We're using a config file, but now every new field requires a code deployment, which is becoming a bottleneck.
null