Voice Of The DBA podcast

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A report of cloud Kubernetes usage shows that these resources are being under-utiliized, over-provisioned, and costing more than necessary for many organizations. From the previous year, average CPU declined from 13% to 10%, and memory is used at only around 23%. Companies are over-provisioning their clusters, which is understandable. No one wants to have systems overloaded and users complaining about performance. However, this is a similar tension to what we see with virtualization on-premises. Operations people want to leave plenty of CPU/RAM/IO headroom for systems to handle bursting or increasing workloads. Management wants to get all the use they can out of their investment and would prefer we provision systems as closely as possible to their expected workloads. Containers and orchestrators should allow a closer match, but only if there are workloads that burst enough to require additional containers and pods to be deployed. That does happen with memory occasionally at a little over 5% of containers exceed their memory, but that’s not a significant amount. Managing a Kubernetes cluster is a specialized skill and most organizations don’t have the skills or experience to do it well. My view is that if you want to use an orchestrator, you’re better off letting the cloud providers manage the infrastructure and scale up and down as needed. There are autoscaling technologies to help Operations staff better manage their capacity and costs, but this is an additional skill people need. While I do think some companies are adopting cloud native technologies and rewriting their applications to run in containers and Kubernetes clusters, I find many more companies are hesitant to adopt a very complex technology on top of the complexity of teaching their developers to work within containers for their applications. Certainly in the Microsoft space, I don’t see a lot of database servers running in containers. Despite some of the advantages of upgrades and downgrades, the unfamiliarity with the ins and outs of containers leads most teams to continue to manage the database separately. Resource matching to a workload is a problem we’ve had for years and Kubernetes doesn’t make this any easier to deal with. The cloud is supposed to help us better manage our resources, but there is a lot of knowledge needed to do this well. Add in the cost/performance issues in the cloud and it’s no wonder that many companies have overprovisioned their resources to ensure systems continue running. I don’t know whether lots of IT staffers are optimistic about their workload growth or scared of potential problems from overloaded systems, but unless organizations carefully manage all their resources, they are likely to continue to see larger cloud bills than they like. Steve Jones Listen to the podcast at Libsyn, Spotify , or iTunes . Note, podcasts are only available for a limited time online.…

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The End of SQL Server 2019

2 days ago

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Well, not really the end. I doubt anyone running SQL Server 2019 is going to stop (or upgrade) just because mainstream support ended. Actually, I wonder how many of you know that SQL Server 2019 passed out of mainstream support on Feb 28, 2025. I do think the 6 or 7 of you running Big Data Clusters likely knew this was the end of any support. I saw a report in the Register on this, which includes a survey of which versions are still running. This is from an IT asset firm and matches Brent Ozar’s Population report . 44% of you are running SQL Server 2019, which is the largest percentage. Since there’s an additional 32% of you running versions older than 2019, I’m sure that upgrading isn’t a priority. It seems like just a couple of years ago that SQL Server 2019 was released. At the end of February Microsoft ended mainstream support for this version. There will still be security fixes released, but no more cumulative updates. The Register says if you don’t upgrade, you might run into a bug and not get a fix (unless you buy extended support), but that’s never worried me. If I haven’t hit a bug 5 years in (or likely 3-4years after my last upgrade), I’m not too worried. If I run into something it’s likely from new code and I’ll just change the code to work around the issue. I do expect to run a database platform for a decade, and I am glad that Microsoft continues to supply security patches for this period. While I certainly want every database firewalled, reducing the attack surface area of known vulnerabilities is good. I also find myself less concerned about the security of older versions. If there is a big security vulnerability discovered in 2017 tomorrow that exists in previous version and I had a 2012 server, I’d just prioritize an upgrade then. Upgrades are hard, eat a lot of valuable time, and don’t necessarily provide many benefits. Most applications tend to use basic CRUD features and whatever was available at the time in that version. If I use a tally table to split strings in 2017, I’m unlikely to rewrite that code to use STRING_SPLIT with an ordinal if I upgrade to 2022. That certainly isn’t a selling point for me to upgrade. My boss knows that isn’t something we’d take advantage of in older code. I’m not a bleeding edge person, and I wouldn’t push for upgrades. If you want to stay somewhat current with versions and are running 2019, I’d be waiting to test my application on SQL Server 2025 at the end of the year or early 2026. If I were mandated to stay current, I’d still be doing that, not jumping to 2022 right now. However, I do recommend that everyone patch their systems with cumulative updates to ensure their security is up to date. There have been several security patches in the past few years that you should have applied and if you haven’t, this is a reminder to do so soon. Steve Jones Listen to the podcast at Libsyn, Spotify , or iTunes . Note, podcasts are only available for a limited time online.…

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Monoliths and Microservices

4 days ago

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I have run into a lot of people in the last few years that love decoupled software and microservices. It seems many people are aiming to move their work in this direction, and while I see some appeal, I also see tremendous additional complexity that has moved out of the software into the operations and debugging space. As I read the book Observability Engineering , I found myself thinking the complexity of setting up more logging and instrumentation in an observability framework as well as the costs of managing a system start. That caused me to think this is overkill for most software. To be clear, I don’t think that Uber could have been built as a few monoliths, and there are other examples of such systems, but most of us don’t work at that scale. There are lessons to be learned about large, real-time software systems, and certainly Google, Amazon, Spotify, Netflix, etc. can help us understand how certain techniques work better at scale, but most of us don’t work at that scale. Scale to me is thousands of connections and terabytes of data. Those companies tend to work at a couple orders of magnitude above that. Those are also companies that must have real time systems up to survive. The vast majority of companies I’ve worked at might suffer a loss with an outage of a system, but honestly, we could survive a day or two of recovery. Heck, look at all of the companies that have had portions of their digital infrastructure knocked offline from ransomware the last few years. Some failed, but most didn’t. The incident sucked for IT staff, but those companies survived. I still remember the SQL Slammer worm forcing us to take our entire network offline for multiple days at a large software company. We still ran sales, and support, and other systems independently or from paper. Granted that was 20 years ago, but I’m sure Redgate and many other organizations could survive a few weeks with no network. Uber on the other hand, that would be a disaster for them. They would likely survive, but at a high cost. How many people would jump to a new service and never look back? I was reading a piece on coupling and complexity , which I’ll discuss a bit in another article, but it got my thinking of how often I see people overcomplicating their work by trying to move to a decoupled world instead of hiring and training people to adopt better architectures and communicate better. After all, moving to microservices isn’t going to avoid the training issue. You’ll still have to teach people more. And while you’re at it, force every developer to pass a SQL test every year. That might help you build better systems as well. SQL isn’t going away and better SQL coding in will result in much better applications everywhere. Steve Jones Listen to the podcast at Libsyn, Spotify , or iTunes . Note, podcasts are only available for a limited time online.…

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More Supply Chain Attacks

7 days ago