Three hundred issues of this little daily post! I’m sure I’ll really find my voice by the time I reach issue eight hundred. A few of the items today really got me thinking and I hope you enjoy the list.
[article] AI Product Management. Building AI apps (not platforms) comes with risks to consider and plan for. This is a great article for teams about to embark on that journey.
[blog] Flutter Made Easy: 5 Tools to Build Better Apps Faster. I’ve given up on ever getting into frontend work, but maybe better tools and generative AI assistance will get me there.
[blog] Security, Maintainability, Velocity: Choose One. Tyler says that without careful consideration, you’ll find yourself choosing security, maintainability, or velocity for your software development.
[site] Build the future of AI with Meta Llama 3. Meta shipped the latest version of their Llama model with some impressive performance numbers. Relatedly, you can try it out on Google Cloud’s Vertex platform.
[blog] What you missed from Firebase at Cloud Next ‘24! The Firebase booth was PACKED with people looking at tech and asking questions. Check this out for videos of their talks.
[blog] Securing Prometheus with Istio Ambient. Quick post, but it highlights the “it just works” outcome of the new data plane in the Istio service mesh.
[blog] Optimize Applications with Performance Configuration Testing. Can you A/B test infrastructure setups in production? That’s what Bruno proposes here, and cloud platforms make it easier to run such experiments.
[blog] Use Log Analytics for BigQuery Usage Analysis on Google Cloud. It doesn’t matter if you generate tons of logs if you have to way to use them. This post shows how to more easily analyze logs produced by your data warehouse.
[blog] Tune Gemini Pro in Google AI Studio or with the Gemini API. While tuning a model can feel intimidating, it really does seem like we’re making this very approachable.
[blog] Introducing LLM fine-tuning and evaluation in BigQuery. While the previous example is for experimentation, this post shows more of a production-grade fine tuning scenario.
[article] Java services hit hardest by third-party vulnerabilities, report says. Plenty of risk to go around, but pay special attention to your (patched) dependencies for Java.
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Richard Seroter's Architecture Musings 