Matt Gordon: Database DevOps – Episode 313

Challenges

  • Managing the evolution of SQL Server and addressing technical debt.
  • Dealing with performance issues caused by abstraction layers like ORMs.
  • Ensuring effective database schema design to improve performance.

Solutions

  • Implementing best practices for database schema design.
  • Continuously improving SQL Server environments based on performance tuning.
  • Utilizing tools and techniques to manage and reduce technical debt.

Benefits

  • Enhanced database performance and reliability.
  • Improved efficiency in managing SQL Server environments.
  • Stronger support for developers through better database practices.

Matt is a Microsoft Data Platform MVP and has worked with SQL Server since 2000. He is the leader of the Lexington, KY Data Technology Group and a frequent domestic and international community speaker. He’s an IDERA ACE alumnus and Redgate Community Ambassador. His original data professional role was in database development, which quickly evolved into query tuning work that further evolved into being a DBA in the healthcare realm. He has supported several critical systems utilizing SQL Server and managed dozens of live site SQL Server implementations. As a Microsoft Lead Data Architect at Centric Consulting, he works with customers large, medium, and small to migrate to the cloud, make their data estate operate efficiently, and find the right tools and solutions within the Microsoft Data Platform.

Topics of Discussion:
[03:08] Matt’s career journey and overcoming a fear of public speaking.
[05:42] Changes and consistencies in working with SQL Server over the years.
[07:18] Advice on the process and tools for database change management and DevOps.
[12:29] Recommendations for database monitoring and observability.
[19:30] Specific monitoring tool recommendations and their pros and cons.
[24:04] The role of ORMs and their impact on database performance.
[30:59] Thoughts on the evolution of microservices and database architecture patterns.
[36:55] Considerations for working with small versus large database sizes.