AI Observability Challenges in FinOps as a DBA

I was performing research for requested AI work and noticed that I was viewing the risks from a database perspective.  As the saying goes in the tech industry, “Once a DBA always a DBA…”  As foreign as some of the views were, much of it feels familiar and I simply begin to look at it […]

Exposing a SQL injection vulnerability you’ve never heard of

This article documents a SQL injection vulnerability I discovered in sys.sp_dbmmonitorupdate, a Microsoft-signed system stored procedure. For other SQL Server security vulnerabilities I’ve discovered, see the full series here.

Limiting Checkpoints

Pros and Cons of Database Sharding for Performance and Maintenance

Large databases usually have a negative impact on maintenance time, scalability and query performance. For maintenance, these large single databases have to be backed up daily while the amount of actual changing data might be small. For performance, tables without correct indexes result in full table or clustered index scans. As the data grows the total query time increase linearly. How can we decrease downtime for the maintenance window for large databases and optimize the performance of daily queries?

BIT_COUNT II

Five Intelligent Query Processing Features in SQL Server 2022 That Quietly Tune Your Workload

Learn about a few new features built into SQL Server 2022 that can help improve performance on your workload.

SQL Server Contained Availability Groups Configuration

In a previous tip on Orphaned User Detection for SQL Server High Availability Databases, we have seen how to identify when there are orphaned database users in an Availability Group database. Is there a way where we no longer need to worry about missing database users or different SID values between primary and secondary databases in an Availability Group?

From SQL Server On-Premises to Claude Desktop: How I built a Full MCP Pipeline

Learn how to get started with an MCP server that can query your SQL Server database.

Parameter Sniffing in Production: How a 200ms Query Became a 90-Second Outage

Learn how parameter sniffing appeared in a real system and how the issues were solved.

Concurrency and Baseline Control: Level 5 of the Stairway to Reliable Database Deployments

As database development scales across multiple contributors, concurrency becomes an inherent aspect of the process. Changes that are individually correct may still conflict when developed against a shifting baseline. This level introduces a disciplined approach to managing parallel changesets by controlling their scope, identifying overlap, and resolving conflicts through realignment. By ensuring that only one changeset retains its original baseline while others are adapted accordingly, deployments remain predictable and consistent. Once released, changesets are treated as immutable, and further evolution proceeds through new, forward-only changes.