Most API pipeline failures are green DAGs producing incomplete data. A practical guide to running Apache Airflow on AWS for SaaS and API extraction: choosing between MWAA provisioned, MWAA Serverless and self-managed, the pool setting that silently stops throttling when you go deferrable, retry and pagination design, secrets handling, and the four cost lines that actually move.
Jira's built-in reports stop at the board boundary. This guide walks through a Jira analytics pipeline built on AWS Lambda, S3 and Athena, organised around the four failure families that actually bite: the removed search endpoint, silently truncated changelogs, incremental loads that duplicate rows, and an S3 layout that quietly inflates your query bill.
You re-run the same extract for the same window and get a different set of rows. Nothing errored. You were paginating a result set that kept changing while you read it. Here's how to build a Zoho CRM to S3 pipeline whose runs are repeatable, from closed read windows to Bulk Read and deletions.