Daily Wrap Up – January 26, 2023 (#017)

What are software developers focused on right now? How can you carve out time to pay down technical debt? Is it possible to build global consistent data-driven apps? Answers to these questions and more in today’s links. Enjoy!

[site] The State of Developer Ecosystem 2022. Read through the results of this JetBrains survey of almost 30,000 developers. It’s good to see what’s hype and what’s reality.

[docs] Deploy a highly-available PostgreSQL database on GKE. If you can use a managed database, do it. But if you want to (or need to) run your own, find good guidance on setting it up in a resilient way.

[article] What Is Policy-as-Code? An Introduction to Open Policy Agent. Self-service is awesome, but how do you ensure that your growing cluster fleet stays in sync? Automated policy governance is one way.

[blog] Improving Support for Deep Learning in Etsy’s ML Platform. As more companies put AI/ML into production, I’m excited to read about lessons learned.

[blog] We invested 10% to pay back tech debt; Here’s what happened. Good story of prioritizing work to keep systems in good shape. Worth a read!

[blog] Let’s Architect! Designing event-driven architectures. The folks at AWS share some good reference guidance for those architecting event driven systems, designing events, and figuring out why this model is beneficial.

[blog] What I Learned in One Year as an SRE Trainee. As you bring new roles into your org (product manager? SRE? UX researcher?) do you have a good training program in place? Can others rotate through established teams and learn from them? Something to consider.

[blog] Turbocharge Cloud Spanner with Redis Enterprise Active-Active for Global Real-Time Applications. Well-explained use case and pattern from the folks at Redis. How do you achieve global consistency at low latency? Check it out.

[article] AtomicJar opens public beta of Testcontainers Cloud, cloud version of open source testing tool. I’m happy for my friends at AtomicJar who are solving a useful problem for devs who want better tests for their systems. Being able to run “real” versions of software like Kafka or MongoDB during test runs is powerful. Also read their letter to their community.

[docs] Forecast conditions. Here’s a cool, new functionality in Google Cloud monitoring that you can use to get a prediction about a metric you’re tracking.

[article] Why Success Doesn’t Lead to Satisfaction. There’s useful advice here. Plenty of folks who “have it all” seem unhappy and rarely will achieving that “one more thing” do it.


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Author: Richard Seroter

Richard Seroter is Director of Developer Relations and Outbound Product Management at Google Cloud. He’s also an instructor at Pluralsight, a frequent public speaker, the author of multiple books on software design and development, and a former InfoQ.com editor plus former 12-time Microsoft MVP for cloud. As Director of Developer Relations and Outbound Product Management, Richard leads an organization of Google Cloud developer advocates, engineers, platform builders, and outbound product managers that help customers find success in their cloud journey. Richard maintains a regularly updated blog on topics of architecture and solution design and can be found on Twitter as @rseroter.

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