I estimated 25 seconds. I measured 39.17.
- Work
- Distributed forecasting on Step Functions
- Role
- Architecture and build
- Period
- 2025
- AWS
- Step Functions
- CDK
- Time series
The brief
The forecasting job ran serially and took 52 minutes against a platform ceiling of 15. It had to be split without losing traceability or blowing up the observability bill. I designed the state machine, deployed it with CDK, and measured every decision before leaving it in.
How it is built
The serial version took 52 minutes against a platform ceiling of 15, so I split it with a Map state over Step Functions, 6 Lambdas, S3 and DynamoDB, deployed with CDK. I set max_concurrency=8 because the account quota was 10, not because 8 was optimal.
I tried gradient boosting expecting it to win. AR(1) won. For metrics I chose DynamoDB over CloudWatch because at that cardinality CloudWatch cost 44 USD a month.
One caveat
My estimate was off by 57%. I leave it written down because the gap between estimating and measuring is the work.
Where it breaks
It breaks at 510 products
Where and why
514 bytes per Map element against the 256 KB Step Functions state ceiling. Past that number the Map has to be paginated or the payload moved to S3.