Daily Reading List – August 31, 2023 (#153)

Tuesday and Wednesday at Google Cloud Next were bonkers and I didn’t have a chance to read or blog! Let’s fix that today. If you get a chance to (re)watch our developer keynote, let me know what you think!

[blog] Expanding Duet AI, an AI-powered collaborator, across Google Cloud. This has been much of what I’ve been working on in 2023. It’s very useful and based on some fascinating technology.

[blog] Welcome to Google Cloud Next ’23. Nice roundup from Thomas of all the major things we covered this week at Cloud Next.

[blog] Introducing the next evolution of container platforms. Exciting stuff from the company that knows containers better than any other!

[blog] Reimagine data analytics for the era of AI. Terrific post about what modern data analytics looks like.

[blog] What’s new and what’s next with Google Cloud databases. Simpler, open, and more AI assisted? That’d be a good future for databases.

[blog] Vertex AI extends enterprise-ready generative AI development with new models, tooling. I’m excited to start getting more hands on with all of this. Even someone like me can use these tools and services.

[blog] Shifting down: a new way to cloud for developers. I’m admittedly tickled that folks outside and inside of Google have taken to my “shifting down” metaphor.

[article] SRE vs Platform Engineer: Can’t We All Just Get Along? Yes, I also caught up with non-Google content today! Good post about how these disciplines should be even more closely aligned.

[article] The shortcomings of serverless computing. No new ground here. There’s no perfect one-size-fits-all compute abstraction. But if you can start with serverless, you should.

[blog] Distributed isn’t Microservices, In-Process isn’t a Monolith. Excellent perspective here from Derek who points out that Amazon didn’t go from microservices to a monolith; they refactored how they deploy the components.

[blog] Zero Configuration Service Mesh with On-Demand Cluster Discovery. Good story from Netflix on their evolving needs that led them to a mesh.

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