Daily Wrap Up – January 13, 2023 (#009)

Lots of Google Cloud stuff today. I apologize for nothing! But also some other great content around best practices, choosing frameworks, and writing good requirements docs.

[blog] Why you shouldn’t fear a “sink or swim” cloud adoption (it beats these four alternatives). My latest piece is up on Google Cloud’s “Transform” blog and advises you to resist the urge always to hedge bets.

[blog] Trends in Data and AI to align with. My former colleague Lak has some smart perspectives on some real trends and their impact.

[blog] GKE Cost Optimization: 10 Steps For A Lower Cloud Bill In 2023. This will be a year of “cost optimization” as folks try to right-size and manage costs.

[blog] YugabyteDB Testing Approaches: An Insider’s Guide. I like learning how a variety of companies do software delivery, and this post digs into database provider Yugabyte and how they think about software testing.

[article] Angular vs. React: How to Choose the Right Framework for You. I don’t do a ton of front end work (very little, actually), but I’ve kept an eye on this space, and these two frameworks are two of the most popular.

[blog] Google Meet will now save you from embarrassing memory lapses during presentations. I spend a lot of my day in Google Meet, and this update will definitely help me present better.

[blog] How to Write a PRD That Actually Helps You Build Products. We write a LOT of product requirement docs at Google, so I enjoyed reading through this Reforge piece about what a good PRD looks like.

[blog] Colab + BigQuery — Perfect Together. Test beds are such a useful way to learn new tech. I like the Colab environment and you can use this notebook as a no-cost way to experiment with Python and BigQuery.

[blog] CircleCI incident report for January 4, 2023 security incident. It was a bad security breach, but good for CircleCI to share a detailed report about what happened and what they learned from it.

[blog] Reading and storing data for custom model training on Vertex AI. Good post that shows you the various options for stashing your data, and why you might choose each for your ML model training.

[blog] BigQuery 101: A Beginner’s Guide to Google’s Cloud Data Warehouse. In-depth write up that gives very useful context about BigQuery.

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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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