When NOT to Retry

Concepts covered: paPermanentFailure, paPoisonPill

Retry as a tool is so often correct that engineers begin to apply it reflexively. The reflex causes outages of its own. Some failures will never succeed on a second attempt, and retrying them wastes compute, fills up logs, and hides the underlying problem. Knowing the categories where retrying is wrong is as important as knowing how to retry properly. The pipeline that retries correctly on transient errors and refuses to retry on permanent ones is the pipeline that operates predictably. Three Categories That Should Not Be Retried Validation Failures Validation failures occur when input data does not match the expected shape. A field that the contract said was required is missing. A timestamp is in the wrong format. A foreign key points to a row that does not exist. None of these will resol

About This Interactive Section

This section is part of the Failure Modes and Error Handling: Beginner lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

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