Daily Reading List – June 1, 2023 (#101)

I read lots of interesting things today, and you’ll find pieces below that cover team dynamics, software architecture, artificial intelligence, and more. Jump in!

[blog] Why Aren’t They Saying Anything? Are you not hearing about problems you know exist in the team, org, or company? Why aren’t people speaking up? This post outlines why, and should motivate us to be better at giving feedback, hearing feedback, and creating space for it.

[blog] AI in software development: What you need to know. My colleague Priyanka does a good job explains some of the myths and realities of AI for software teams.

[blog] Optimising platform spend with cluster autoscaling. Moving to the cloud doesn’t make a huge difference if you don’t take advantage of the many automation levers you get access to. This team used GKE’s autoscaling capabilities to save real money, and make safer changes.

[article] Google’s Generative AI Stack: An In-Depth Analysis. To me, a complete generative AI experience should help those who want to build models, consume models in their apps, and use AI to get their work done.

[blog] 7 Ways to Improve Your Documentation Developer Experience. Good advice whether we’re talking about internal-facing docs for your own devs, or external docs for other users of your products.

[blog] Generative AI – Best Practices for LLM Prompt Engineering. It’s fun to see so much material helping so many people get smarter on a complex topic quickly. I like this post on the different types of prompts that generate different types of results.

[article] Adopting Continuous Deployment at Lyft. Recording and transcript of a talk that looks at details on what they deployed, how they did it, and when they did it.

[blog] Cloud CISO Perspectives: Late May 2023. Some considerations for digital sovereignty, along with lots of links to new security content.

[blog] Unleashing the Power of BigQuery Connected Sheets: The Perfect Fusion of BigQuery and Google Sheets. Most enterprise data sits in spreadsheets, so might as well make it easier to join that data to what’s in your data warehouse!

[blog] How to simplify unstructured data analytics using BigQuery ML and Vertex AI. Related to “staying where you are”, I like that you can invoke pre-trained ML models via SQL from within BigQuery. Good demo here.

[article] Why You Need a Multi-Cloud and Multi-Region Deployment Strategy. Color me skeptical on this advice. Multi-region, absolutely. Multi-cloud as a way to improve resilience, I don’t see it.

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Author: Richard Seroter

Richard Seroter is currently the Chief Evangelist at Google Cloud and leads the Developer Relations program. 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 Chief Evangelist at Google Cloud, Richard leads the team of developer advocates, developer engineers, outbound product managers, and technical writers who ensure that people find, use, and enjoy Google Cloud. 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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