A Q&A video session covering SQL Server DBA questions crowdsourced from a voting site, recorded from a park in Zhengzhou, China. Topics include running DBCC CHECKDB on AG secondaries for large databases, tempdb bottleneck diagnosis, Dynamic Data Masking adoption, performance testing for AG migrations, using AI tools for SSRS/Power BI reporting, career advice for laid-off DBAs, and moving from DBA to BI roles. Also mentions new podcast distribution channels for the Office Hours series.

3m read timeFrom brentozar.com
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Questions this post answers

Is it safe to run DBCC CHECKDB on a synchronous secondary replica in an Always On Availability Group for a 25TB database?

Running full DBCC CHECKDB against a sync secondary can be risky for very large databases because tempdb can fill up, especially compared to using PHYSICAL_ONLY, which is lighter weight. For a 25TB database, offloading checks to a secondary is common practice, but tempdb sizing and monitoring needs careful planning to avoid failures on such large integrity checks. See how other teams size tempdb for large-scale integrity checks by following database discussions on daily.dev.

How can I tell if my SQL Server workloads are actually bottlenecked on tempdb contention?

High tempdb latency alone does not prove user impact; you need to correlate tempdb wait stats with actual query duration or blocking on the affected sessions to confirm a real bottleneck. Simply observing elevated tempdb latency is not sufficient evidence that end users are experiencing slowdowns from it. Keep up with practical SQL Server performance diagnosis tips through daily.dev.

How popular is Dynamic Data Masking adoption in SQL Server among companies?

Dynamic Data Masking sees mixed adoption across organizations, with some treating it as a genuinely useful compliance feature and others viewing it as a largely unused or 'dead' feature that doesn't get much real-world traction. Its uptake varies significantly depending on company compliance needs and awareness of the feature's limitations. Track how database security features like masking get adopted in practice via daily.dev.

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