Pause Your ML Pipelines for Human Review Using AWS Step Functions + Slack

Have you ever wanted to pause an automated workflow to wait for a human decision?

Maybe you need approval before provisioning cloud resources, promoting a machine learning model to production, or charging a customer’s credit card.

In many data science and machine learning workflows, automation gets you 90% of the way — but that critical last step often needs human judgment.

Especially in production environments, model retraining, anomaly overrides, or large data movements require careful human review to avoid expensive mistakes.

In my case, I needed to manually review situations where my system flagged more than 6% of customer data for anomalies — often due to accidental pushes by customers.

Before I implemented a proper workflow, this was handled informally: developers would directly update production databases (!) — risky, error-prone, and unscalable.

To solve this, I built a scalable manual approval system using AWS Step Functions, Slack, Lambda, and SNS — a cloud-native, low-cost architecture that cleanly paused workflows for human approvals without spinning up idle compute.

In this post, I’ll walk you through the full design, the AWS resources involved, and how you can apply it to your own critical workflows.

Let’s get into it Read More