Part of my Redgate work is with customers who need to monitor their database servers. With estates growing quickly, both in scale and types of database platforms used, keeping an eye on everything can be challenging. Add in the lack of staff growing as quickly are the number of servers, and I find many companies seeking out monitoring tools to better help them manage the entire estate..

When someone evaluates a tool, one of the first questions from many people is about load. They are concerned about the load a tool puts on the system, which is always some amount. Most tools say they use less than 2% of total resources, some might hedge at 5%. Hopefully, there's no more impact than 5%, though that might seem to high, especially if you have a busy database server already.

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Are you looking forward to SQL Server 2025? Or perhaps you think this is just another release, or perhaps you are not looking for new features or capabilities in your environment. Maybe you don't care about new things, but are looking for enhancements to features introduced in 2017/2019/2022. There is certainly no shortage of things that can be improved from previous versions (cough graph *cough).

I ran across an article on the five things that one person is looking forward to in SQL Server 2025. It's a good list, and the things included make me consider an upgrade. Certainly, any improvements in the performance area, especially with all the investments made in Intelligent Query Processing over the last few versions, are worth evaluating. They might help your workload, or they might not, but if they do, then upgrade.

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I had to make a few changes to a SQL Saturday event recently. The repo is public, and some of the organizers submit PRs for their changes, and others send me an email/message/text/etc. for a change. In this case, an organizer just asked for a couple of image updates to their site. I opened VS Code, created a branch, added a URL for the images, and submitted my own PR. After the build, I deployed it.

And it didn't work.

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When talking about DevOps, the goal is to produce better software over time. Both better quality as well as a smoother process of getting bits to your clients. There are a number of metrics typically used to measure how well a software team is performing, and one of the things is Change fail percentage. This is the percentage of deployments that causes a failure in production, which means a hotfix or rollback is needed. Essentially we need to fail forward or roll back to get things working.

For most people, a failed deployment means downtime. I've caused a service to be down (or a page or an app) because of a code change I made. This includes the database, as a schema change could cause the application to fail. Maybe we've renamed something (always a bad idea) and the app hasn't updated. Maybe we added a new column to a table and some other code has an insert statement without a column list that won't run. There are any number of database changes that might require a hotfix or rollback and could be considered a failure.

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Many of us are faced with choices and decisions constantly in our jobs. How do we approach a problem? What should we do as a team to get the work done? How do we code or manage or test or do something else with a database?

Maybe more importantly, how long do we spend deciding?

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At an event recently, I had a chat with someone after one of my sessions. I had been speaking on DevOps and ways to better structure your team and build software. After the session, one person asked me if I'd read The Mythical Man Month and if I felt we'd gotten a lot better at building software since that book was published.

I do think we have gotten better, way better, in fact. I caught another review of the book a while back from the Pragmatic Engineer. That view looked at what's changed in 50 years since the first edition, as well as contrasting the world today. You have to subscribe to read that one, but I'll give you a few thoughts from me on the book itself and the review.

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I've been reading an interesting book that looks at some of the ways that we can better build software in enterprises. One of the side notes in the book is that the tech companies have the funding and the ability to disrupt many other types of businesses, not just technology. Google, Amazon, Microsoft, and others have delved into other types of industries, potentially pushing others out.

We see Amazon becoming as much a shipping and logistics company as they are a retailer. There was a unionization vote, which passed in 2022. Recently, another one failed. Amazon continues to fight these efforts, trying to prevent workers from collectively negotiating the terms of their employment.

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At a recent event, I had a student ask about how to get started as a data professional. What types of things should they do? What platform should they work on or learn? Where should they focus time? What tools are available?

Those are all good questions and many of you likely have your own advice. I'll give a few things to think about today, which are good for anyone that might want to get into the data field. I think this is still one of the better technical careers. I've suggested this to my kids, though only one of them went into a technical area. One is a therapist for autistic children and one helps run the ranch while pursuing a graduate degree in literature.

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I saw an article on AI usage that is based on an upcoming book that suggests redesigning the world around new tech, not adding it to existing things. The first example is how electricity was introduced to existing factories, but it only provided some incremental gains until new factories were redesigned around electric motors. There's also an example given about reworking hotels to remove the front desk since that feature isn't needed. Instead, people could walk in, and an employee with a tablet could find them to check them in.

I'm all for rethinking and redesigning processes. I do think we have a huge glut of software in many organizations that exists because processes have evolved across time, but not everything and we keep our old software. When we have a new need or want a new capability, we add new software (or add features), but we don't necessarily throw out all the old software, processes, or habits. That wouldn't be practical, often because when we implement something new, it might not meet all our needs. Or at least we don't know it meets our needs at first.

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As a part of my job, I often work with customers on how they can get database code into a version control system. That's Git for the most part today, which is the most popular system in the world. I'm comfortable using Git for many basic tasks, but I am not an expert by any means. I've used version control for years, and quite a few systems, and I like Git as a way of managing code.

I have been surprised how many people aren't comfortable with version control or Git. Many don't have the habit, but are amenable to it. What I'm amazed by in 2025 is how many people don't use it, given that so many tools we use to work with databases, and even other systems, will store items in Git. This isn't just for development code, but also for infrastructure code. Lots of data tools and servers can store data in Git and use it to deploy changes to all kinds of systems. I'd have expected more people to know Git.

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