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What Is Runtime Regression?

A runtime regression is a sustained slowdown in SQL Server work compared with a relevant earlier baseline.

A runtime regression occurs when a query, procedure, or job becomes slower than it was under comparable conditions. The change may follow a deployment, data growth, a new plan, or a shift in concurrent workload.

Definition

A regression is more than an unusually slow execution. It is a meaningful change against a previous stable pattern, ideally confirmed across repeated runs or similar workload periods.

How to confirm one

  • Compare the same operation before and after the suspected change.
  • Check run frequency, parameters, and data volume alongside elapsed time.
  • Look for a plan change, blocking, waits, or resource contention.
  • Identify the first affected run and correlate it with releases or operational events.

Operational example

After a schema change, a procedure's median duration rises from 300 milliseconds to four seconds. The first slow runs line up with the release, and the execution plan shows a scan where an index seek was previously used. The team can investigate the plan change with a specific time boundary.

Common pitfalls

Calling every outlier a regression creates noisy alerts. Comparing runs with different parameters or workload sizes can also suggest a slowdown where none exists. Confirm that the comparison is like for like.

SQL Cockpit context

SQL Cockpit helps teams review runtime trends and historical executions so they can notice sustained changes and connect them with other SQL Server events.

FAQ

What is the difference between an outlier and a regression?

An outlier is an unusual run. A regression is a persistent or repeatable deterioration relative to comparable earlier runs.

Does a regression always mean the query changed?

No. Data distribution, statistics, contention, and infrastructure changes can all affect runtime.

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