I caught this post about a career presentation from Kendra Little and it resonated a bit with me. The summary of the post (it's a bit long) is that there is valuable work that supports and benefits a team of people, called glue work. However, glue work isn't necessarily technical and it isn't necessarily recognized as valuable by management. In fact, it might unintentionally lead you from a career in engineering to one in project management.

I haven't been someone who has been marginalized in positions, who has been taken for granted or expected to do certain tasks. I think some people get taken advantage of, and this is especially true for women, who both volunteer more and are volunteered by others more for these tasks. While I have been quick to document decisions or actions, and sometimes help out with project work, I do that in addition to any technical work. I've felt that as a developer, my job is to produce code. If I can help with other things, then I'm a Developer+, but I ultimately know that code my clients can use is what matters.

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For the last few years, we've seen no shortage of cloud migration stories and felt pressure from management who wanted to migrate our systems to the cloud. It seems that almost everyone I speak to has a story of having to move a system out of their owned or leased data center into a public cloud from some vendor. A lot of this is the movement of VMs from one place to another, which has me scratching my head. If we're just running VMs, surely we can do this cheaper in our own data center.

Perhaps, though there are a lot of costs to setting up or running a data center, and it's not easy getting a system in place that allows a bit of self-service for our customers. Especially while ensuring that images used are properly patched and secured, while ensuring lots of easy connectivity to storage that can be reconfigured easily. It might not be worth the effort for a few dozen VMs, but if you have hundreds of systems, maybe it is.

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I was chatting with a friend recently about routines and some of the helpful or silly things we do. I mentioned that when I played adult baseball, we often had Sunday morning games and a routine of mine was to drive to town, stop at a 7-11, and get a large cup of coffee and an apple fritter. It was a comforting habit that I still have today, often stopping when I have a morning flight to do the same thing in the way to the airport.

Only in Denver though, not when I'm flying out of other cities and returning home.

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I went to San Francisco for Small Data SF, a conference sponsored by Mother Duck. The premise of the event was that smaller sets of data are both very useful and prevalent. The manifesto speaks to me, as I am a big fan of smaller sets of data for sure. I also think that most of the time we can use less data than we think we need, especially when it's recent data. That often is more relevant and we end up with contorted queries that try to weight new or old data differently to reflect this. Maybe the best line for me is this one:

Bigger data has an opportunity cost: Time.

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When I was younger, I had a variety of jobs, but in most of the positions I had to work hard for stretches. Really hard, as in more than 8 hours a day or 40 hours a week. Often as I was starting a new position, it took some time for me to develop some understanding, some skill, and some muscle memory. In some jobs, especially in restaurants, I also had to build the physical skills to be on my feet for many hours.

In technology, I've often found myself unsure of how to approach a new position, aware I had knowledge gaps about how things worked, and often, I was naïve or ignorant of some piece of technology my employer used. Even at jobs where I started as a developer or DBA on a known platform (ASP or SQL Server), I sometimes encountered some aspects of the technology that I hadn't used in the past (like clustering).

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I was asked this question recently: is it more likely that AI will replace humans or assist them in their work?

It's a good question. If you think about the way AI is being hyped in 2024, many people think AI is, or will soon be, replacing people and we need less of them in work. I guess the simplified view is that AI can do the jobs of many people, but I'm not sure the world is that simple. What I think is more likely is that AI becomes a lever that assists a few people in getting more work done and potentially replacing other, less knowledgable humans.

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It seems there's quite a dichotomy in the technology workforce. On one hand I hear about the Great Resignation where many employees are leaving their jobs because of RTO (return to office) mandates or some other dissatisfaction with their job. On the other, I've seen quite a few people who were laid off and are struggling to find new positions. On the third hand, there is no shortage of companies who report they are struggling to find and hire talented people for some positions.

I don't quite know what to think, but I do know that employment seems to be harder to come by. If you are looking for a job, I believe you need your own sustainable learning plan. If your organization can't find qualified talented staff, then the organization definitely needs a continuous learning plan.

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I was listening to someone at Microsoft talk about their product recently. I can't disclose which one it was, but lots of people use this product and are impacted by changes. The particular thing that caught my attention was that the presenter noted there was a breaking change in the new version for some people. This wasn't a huge change or one that would affect a lot of people, but it was a breaking change for a few.

Another attendee asked this question: I would tend to do xxx instead of what you showed, so why would you do this?

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I was watching a video called Microservices are Technical Debt. In it, the person being interviewed said that a lot of people really have a distributed monolith. That caught my eye since I've worked with a number of customers who are trying to adopt microservice architectures for their applications. I think this is less a performance/scaling choice than a reworking of their software development teams, and I'm not sure they will end up with a better system.

What is a distributed monolith? I am not an expert, but this appears to be a place where all the services still depend on each other. For example, I might have a service getting user profile info that an app calls, with another service getting previous orders, and a third service that returns inventory. In a monolith, if any of these are down, the others don't work. In a distributed monolith, these might be built independently, but perhaps the core app/web page still requires all these to be working to show the user something.

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