Microservices are still where software is heading

If you’re struggling to keep up with what seems like a software ecosystem moving at warp speed, here’s a handy blog post from the folks at O’Reilly: The Topics to Watch in Software Architecture

It’s a ranking of popular terms included in speaker proposals for the company’s upcoming Software Architecture Conference, and highlights what many folks have been suggesting for years. Namely, that while the specific technologies and trends come and go, the general direction of software architecture remains heading steadily toward “microservices” (No. 1 on the list for 2 years running) and toward the “cloud” (No. 4, up from No. 5). And it remains heading steadily away from—or, to use the list’s terminology, migrating away from—monolithic architectures.

As this happens, you see certain terms skyrocket in popularity in the course of only a year—”serverless,” “mesh,” “Kubernetes,” “agile” and “testing,” to name a few. It seems probable that in the years to come, some of these will grow in popularity and others will fade (“container,” for example, saw a precipitous drop) but the arrow of progress will continue in the same direction toward microservices and toward the cloud and/or cloud-native.

If there’s a takeaway in this (aside from the fact that it’s fun to look at ranked lists), it’s that any given specific technology probably is not the answer to all that ails your IT practice, at least not for long. But general architectural practices and development processes can act as reliable polestars, pointing you in the right direction. How, exactly, you get there is less important than just getting there—the sooner, the better.

The concerns never stop

Baltimore ransomware nightmare could last weeks, with more big consequences (Ars Technica): This is a terrifying attack in its scope, affecting everything from home purchases to bill payment. And while Baltimore’s IT practices are particularly poor, even subpar practices can lead to trouble. 

Why your CloudOps staff is quitting (InfoWorld): The advice to standardize rather than try to hire superstars is good advice. Adopting technologies that simplify people’s jobs rather than burdening them with even more will help keep them around.

Scale changes everything

Sony’s deal with Microsoft blindsided its own Playstation team (Bloomberg): Sony’s internal communication aside, the money quote is here: “If you aren’t spending billions of dollars a year on data centers, servers and network gear, you can’t keep up.” Sony isn’t, so it needs a partner—even a once fierce rival—if it’s going to own video-game streaming now that Google is in the game.

Data first, then AI

Becoming a machine learning company means investing in foundational technologies (O’Reilly): Some good advice here. You don’t go from zero to AI, but instead need to get the right data engineering in place.  

4-2x.png AI for upskilling

CIOs turn automation on their own departments (Wall Street Journal): From chatbots to cloudops, there are lots of simple efficiencies AI-like tech can deliver today.

AT&T sees business gains from artificial intelligence and machine learning (ZDNet): This story has a lot of interesting examples, ranging from using data science to determine kiosk locations to predicting and fixing network issues.

How artificial intelligence is already disrupting financial services (Barron's): Fraud detection is a common example, but the explainability of algorithms is also a concern. So banks are investing in learning what skills they’ll need and teaching them to employees.

Google Glass takes on Microsoft HoloLens with new augmented reality eyewear for businesses (GeekWire): Unlike the last go-round, this time Google is focused squarely on the enterprise. Depending on your industry, it might be very well worth considering how this type of enterprise-focused AR could improve what employees can do.


Webinar: Deploying Kubernetes to Drive Business, Not Complexity (Pivotal)

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Improve Event Management With the DevOps Techniques of Continuous Monitoring and Automation (Gartner; subscription required) 

The Application Leader’s First 100 Days (Gartner; subscription required) 

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