‘Is it just me, or is SQL Server quality slipping?’
I asked myself that question for couple/few years until I faced up to it: SQL Server is well into a period where Microsoft investment is waning, and Microsoft regularly isn’t able to deliver the features they promise.
I listened to ‘Surviving the A.I. Endgame’ this weekend and realized: I’ve become one of the believers that AI advances are very likely to completely change tech and knowledge roles as we know them over the next 10 years. This is going to dramatically shrink the workforce across MANY roles (and many of those impacted will be outside of the tech sector). It isn’t that people won’t be needed anymore, but far fewer people will be needed. Including people with database administrator (DBA) roles like mine.
SQL Server’s free state-based version control tooling was introduced under the ‘Data Dude’ brand, then became known as ‘SQL Server Data Tools’ (SSDT). Its extension for the (now dying) Azure Data Studio IDE is called ‘SQL Database Projects’. If you need to find documentation, you often need to know to search for specific component names like SQLPackage.exe, which is a command line utility used to deploy SSDT Projects AKA SQL Database Projects.
What are your stories of unbelievably bad performance from cloud vendors? I’ll go first. For years, Azure SQL Managed Instance’s General Purpose Tier has documented ‘approximate’ storage latency as being “5-10 ms.” This week they added a footnote: “This is an average range. Although the vast majority of IO request durations will fall under the top of the range, outliers which exceed the range are possible.”
This is the worst bug I’ve found in SQL Server to date. Previously, my top find was SQL Server Online Index Rebuild sometimes happens offline without warning. This one has taken top slot because it makes my life more difficult on a daily basis.
Background: SQL Server generates a query_hash for each query. This is stored in sys.query_store_query and it’s one of the primary ways you can identify what a query is across different Query Stores, or even the same Query Store over time, as surrogate query_id values get reset if Query Store is cleared or data ages on. The query_hash is a ‘Zobrist hash over the shape of the individual query, based on the bound (input) logical query tree. Query hints aren’t included as part of the hash.’ (Source)
I use Datadog on a regular basis, and I’m a pretty huge fan. The monitoring pack for SQL Server (and its PAAS variants) is still pretty rudimentary, but it evolves regularly. That’s NOT what I’m a fan of, though.
What makes me a raving fan is the flexibility of Datadog’s notebooks and dashboards, combined with the ability to create all sorts of custom metrics and monitors. There are always things in SQL Server monitoring packs that I have strong opinions about. Datadog lets me take what I want, build what I need that isn’t contained in that, and ignore the rest. For a team that has the budget to afford Datadog paired with dedicated database staff with the time and resources to do this work, this can be a great fit.
Asking Microsoft for support for SQL Server or Azure SQL is a lousy experience these days, whether you’re using a cheaper service tier or the more expensive support tier formerly known as “Premiere Support.” You need to know a lot about the root cause of your problem and how to solve it, or your request will be dismissed with misinformation. You’ll need data and metrics to back up your claims to get the ticket escalated, and you’ll need to provide those receipts multiple times. Once escalated to the Product Group, you may get a helpful response, but it takes a while. If the answer is relayed through a lower support tier, it often won’t make much sense.
These issues aren’t due to bad work ethics or personal failings of support workers. These are good humans trying their best. The problem is worse because it’s systemic.
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