The Tool Desk
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Start with evidence, version and platform
Before changing a setting, record the SQL Server release, database compatibility level and deployment type: for example, SQL Server on premises, SQL Server on an Azure virtual machine, or Azure SQL Database. Not every control exists in every service, and defaults vary. The same setting can also behave differently across workloads such as transactional processing, reporting and batch jobs.
Use Query Store, where available, to review query and plan history and establish a baseline. Check that it is enabled and that its capture and retention configuration gives you useful coverage. SQL Server 2022 enables Query Store by default for newly created SQL Server databases, but do not assume that default applies to an existing database, another SQL Server version or an Azure service. Microsoft’s Query Store documentation describes its role in performance diagnosis.
For each candidate change, compare relevant query plans and runtime measures before and after: duration, CPU, waits, concurrency, and whether the change helps the affected queries without harming others. Define a rollback path before rollout. Some database options and scoped configurations invalidate the affected database’s plan cache, which can trigger recompilations and temporarily affect performance. Microsoft’s guidance on Query Store and compatibility-level changes recommends collecting a baseline before testing a new compatibility level.
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Which settings should you investigate?
| Control | Scope and effect | When to investigate | Main caution |
|---|---|---|---|
| Compatibility level | Database-level gate for query-processor behavior that can affect plan selection. | After an engine upgrade, when evaluating newer optimizer behavior or diagnosing plan changes. | A database-wide change can affect many queries; baseline and review regressions first. |
| MAXDOP | Can be set at query, database, server or Resource Governor workload-group scope; caps processors used for parallel plan execution. | When parallel execution, CPU use, waits or workload concurrency point to a parallelism question. | There is no safe universal number; scope precedence and platform matter. |
| Cost threshold for parallelism | Server-level advanced setting that influences when SQL Server considers a parallel plan based on estimated plan cost. | When evidence suggests the current parallel-plan selection warrants investigation. | The default 5 is a starting point, not a recommendation; unavailable to configure in Azure SQL Database. |
| Query Store hints | Query-scoped way to influence a plan in supported scenarios, without editing application SQL. | When a small number of identified queries regress and a database-wide change is unsuitable. | Diagnose and test the query first; a hint is not a substitute for understanding the regression. |
Compatibility level: separate the engine upgrade from optimizer changes
Upgrading the SQL Server engine does not require immediately raising a database’s compatibility level. Compatibility level controls exposure to query-processor changes, so raising it can change plans and query behavior. A safer sequence is to upgrade the engine while retaining the existing database compatibility level, gather a Query Store baseline, then test the newer level and inspect the affected plans and runtime behavior. See Microsoft’s compatibility-level upgrade workflow.
- Confirm the current engine version, database compatibility level and Query Store status.
- Capture representative workload history and identify important queries and their plans.
- Test the newer compatibility level in a controlled environment or rollout, then compare results across a representative business cycle.
- Investigate regressions query by query. If only a few queries are affected, assess targeted remediation rather than assuming the whole database must remain on the older level.
Microsoft recommends testing the application at the latest compatibility level before using Query Store hints. Where changing the database-wide level is unsuitable, supported query-level optimizer compatibility hints may help address an individual query. Consult Query Store hints documentation and the query-hints reference for applicability and syntax.
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MAXDOP: choose scope before choosing a value
MAXDOP limits processors used for parallel plan execution; it does not guarantee that a query will become faster. Microsoft describes the limit as applying per task, not as a total worker limit for the query: one request can create multiple tasks. The right value depends on workload and platform, so do not copy a number without understanding the machine topology, query patterns and concurrency.
MAXDOP can be configured at query, database, server or Resource Governor workload-group scope. A database-scoped value overrides the server setting unless the database value is 0; a query hint can override the database setting, while a workload-group limit can cap the resulting setting. Check all applicable scopes before attributing behavior to a single configuration. Microsoft’s MAXDOP guidance explains these interactions.
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SQL Server 2022 includes Degree of Parallelism Feedback for supported configurations at compatibility level 160. It can adjust parallelism for repeating queries and revert adjustments if performance regresses; treat it as a version- and configuration-dependent option, not a universal replacement for measuring workload behavior. Details are in Microsoft’s Degree of Parallelism Feedback documentation.
Cost threshold for parallelism: do not tune the default by reflex
This advanced, server-level setting influences when SQL Server considers parallel plans, using estimated plan cost. That cost is a relative plan-selection measure, not a prediction of elapsed time. Microsoft’s recommendation is explicit: “The default value of 5 is a starting point, not a recommendation.” It advises experienced database professionals to raise the threshold in small increments and observe a full business cycle before making further changes. The option cannot be set in Azure SQL Database; Microsoft points to MAXDOP as the parallelism control there. Read the cost threshold configuration guidance before changing it.
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- A low threshold can coincide with many CPU-light queries going parallel and parallelism-related waits. Treat that as a signal to investigate, not proof that the threshold caused the problem.
- A high threshold can leave CPU-heavy queries serial while CPU utilization is higher than optimal. This, too, is an indicator to examine alongside plans, runtime data and workload behavior.
- If you test a change, make a small adjustment and observe a full business cycle before deciding whether another adjustment is warranted.
Use Query Store hints for evidenced, query-specific regressions
Query Store hints can influence a specific query’s plan in supported scenarios without requiring a change to application SQL. They are most useful when evidence identifies a limited set of regressed queries and a database-wide compatibility-level change would have too broad a reach. First confirm the query and regression, test the latest compatibility level where appropriate, and then evaluate whether a hint is suitable. Microsoft describes the feature and its limitations in its Query Store hints documentation.
Do not disable parameter sniffing as a blanket fix
Parameter-sensitive behavior can lead to different performance outcomes for different parameter values, but disabling parameter sniffing across a workload is not a safe default remedy. Identify the affected query and compare its plans and runtime behavior for representative values. In SQL Server 2022 at compatibility level 160, Parameter Sensitive Plan optimization is enabled by default; for qualifying cases with nonuniform data distributions, it can support distinct plan handling. See Microsoft’s Parameter Sensitive Plan optimization documentation.
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A safe change-and-validation checklist
- Identify the environment: note engine release, compatibility level, platform and the setting’s available scope.
- Define the symptom: name the affected queries and the problem to improve, such as latency, CPU use or a plan regression.
- Establish a baseline: use Query Store or equivalent evidence to capture representative plans and runtime behavior.
- Check interactions: inspect query hints, database and server settings, and Resource Governor limits where relevant.
- Change one control: limit the blast radius, especially when a query-specific remedy can address a query-specific problem.
- Observe and compare: include representative workload periods and, for cost-threshold tuning, a full business cycle before further increments.
- Roll back if needed: use the preplanned reversal if results regress, and account for possible plan-cache invalidation and recompilation.
Further reading
For a book-length treatment of query plans and performance troubleshooting, see Grant Fritchey’s SQL Server 2022 Query Performance Tuning: Troubleshoot and Optimize Query Performance, published by Apress in 2022. It covers Query Store and execution plans; it is optional reading, not a prerequisite for changing settings.
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