The vendor-driven content machines haven’t woken up yet in the new year, so I read a lot of practitioner and analyst content today. Check out some good pieces that range from very specific (ML use case) to general purpose (evaluating new tech).
[article] Why Are We So Bad at Mean Time to Repair (MTTR)? Good article that explains MTTR, and what it takes to get our systems back online faster.
[blog] What Is Cloud-Native Architecture? Not a bad writeup, but I don’t agree with chunks of it. Specifically, “cloud native” isn’t about containers or meshes. I like to say that “Cloud-native software is built for scale, built for continuous change, built to tolerate failure, and built for manageability.” And I think it’s very difficult to truly do those things without cloud-based managed services.
[blog] 6 Open-Source API Gateways. Do you use an API gateway? If you want to use one, you’ve got lots of commercial choices, as well as open source ones.
[article] Predictions for gaming in 2023. I sponsor a gaming account as part of my day job at Google Cloud, so I’ve paid more attention to the space lately. This is a good set of predictions for 2023, and even if you’re not in the gaming industry, you may get insight into how emerging tech ideas are being used.
[article] Kubernetes 1.26 Released with Image Registry Changes, Enhanced Resource Allocation, and Metrics. Saw data last month that said most Kubernetes users were 18 months behind on the latest release. Here’s another release to fall behind on! But remember, you focus on regular updates because of security updates, not just new and shiny features.
[article] Why and How to Evaluate Emerging Technologies. We can feel overwhelmed trying to keep track of all the new things going on. Don’t stress it, but also don’t completely ignore what’s happening in our industry.
[article] How to Grow Your Top Line in a Down Market. This will likely be a year when many folks retreat a bit and try to weather the economic storm. But others won’t just focus on fixing the bottom line, but also the top line.
[article] Data in 2023: Rethink the Modern Data Stack. We can process more data, and do more with it, than ever before. That’s awesome. It also means the experience has gotten richer, and more complex. This post calls out a need for simplification.
[blog] Selecting the Best Image for Each Merchant Using Exploration and Machine Learning. I liked this look at doing A/B testing and using ML to find the right image to promote a restaurant.
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