A collection of articles I've written. Software architecture. Optimization. Random thoughts. AI.
One of the classic bugs is the memory leak. Even garbage collected languages like C# can leak memory, even if all the code is safe/managed. Sometimes such issues are easy to find and fix. Other times its difficult, for example when the memory leak only happens in production, only sometimes, in a containerized .NET service running in Kubernetes. This difficult case is the one I will cover in this post.
It started with this quote: We hit 100% DTU on user DB again yesterday
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Follow along into a deep dive into optimizing the unindexable
Msisdn LIKE '%ddd%' SQL query.
It is not easy to be a AI DBA
Do you also have the feeling AI advice often tricks you as much as it helps? I challenged a colleague who specified a fill factor of 80 of when creating a new table with a non-clustered index (in Azure SQL/SQL Server) and we asked the AI for help.
Redis is arguably the most well regarded tech of all. But many times you do not need Redis. Here are 3 examples from my last 3 jobs.
During a AI Hackathon at work I trialed a AI-powered code review plugin. Did it work?
What is more fitting as a first post than an overview of the tech used to build this site?