Starting an Informatica Intelligent Data Management Cloud (IDMC) taskflow from code is easy. Knowing what happened to it afterward is harder.

In most pipelines I've reviewed, the "monitoring" is a scheduled job that fires the taskflow and hopes for the best. When a run hangs, gets suspended, or quietly fails at 2 a.m., nobody finds out until a downstream report is empty.

This post walks through a small Python framework that fixes that. It:

Authenticates to IDMC and renews the session when it expires

Starts a taskflow and captures its run ID

Polls run status with exponential backoff and a hard timeout

Treats FAILED, SUSPENDED, and timeouts as distinct outcomes

Sends alerts through pluggable notifiers (Slack, Amazon SNS, or anything else)

Emits structured JSON logs you can query in CloudWatch, Datadog, or Splunk

All of it fits in about 300 lines and works the same on a laptop, in a container, or inside AWS Lambda.

Note: IDMC endpoint paths and status values can vary by pod and release.…