Category: Daily Reading List

You’ll find a whole lot of advice in today’s reading list. Advice on public speaking, changing IT culture, being resilient in a crisis, and even how to A/B test!

[blog] Long Document Summarization Techniques with Java, Langchain4J and Gemini models. Dan looks at three techniques you can use to summarize big docs with Java and your favorite LLM.

[blog] The Product Model in Traditional IT. Can you bring the product model to other types of orgs? This post looks at when it can work with traditional IT teams, when it doesn’t, and what has to change.

[blog] Programming, Fluency, and AI. Important post from Mike. If you’re not fluent in the thing you’re doing with the AI, you’re easily replaceable by AI. Don’t skip depth.

[article] The Anatomy of Slow Code Reviews. Slow reviews are a motivation killer. Google measures this closely. Here’s a post that explores the source of code review challenges.

[blog] The secrets of public speaking. Brian offers up some very good advice for those trying to improve their public speaking, or build up their confidence in the first place.

[blog] How I sent 500 million HTTP requests to 2.5 million hosts. Loved this. It’s a good answer to “what happens when I submit a web request” while also showing how you’d optimize a lot of calls.

[article] How To Be More Resilient: 6 Steps To Success When Life Gets Hard. There’s no pill or item to purchase to make you more resilient. Most of this advice from Eric relates to attitude.

[blog] BigQuery QUALIFY Clause: Towards Cleaner SQL Queries. I’ve got very dated SQL syntax knowledge. QUALIFY is not in my wheelhouse, but now I know more about it.

[article] Why Ruby on Rails Is Still Worth Your While as a Developer. Ruby is a tier-2 language at this point—viable, but not as vendor-supported or used as others—but that doesn’t mean it’s not a good language to work with.

[article] There’s a Smarter Way to A/B Test. Running A/B tests on your product can be expensive. This article proposes different assignment rules that let you run shorter trials.

[article] AI Success Depends on Tackling “Process Debt.” Don’t use AI to automate or augment bad processes. Use this technology moment to rethink processes and start fresh.

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Folks on my team are analyzing (digital) watering holes where developers hang out. There’s no one place! It seems to differ by experience, region, and whether you’re in a big company or a freelancer. What are your top three hangouts? Tell me in the comments.

[paper] Searching for Best Practices in Retrieval-Augmented Generation. Good paper that expresses opinions after an investigation of techniques and practices for RAG with LLMs.

[blog] Vertex AI Studio vs. Google AI Studio: Choosing the Right AI Tool for Your Startup. We offer a couple of different surfaces today for those building with AI. I thought this was a solid comparison.

[blog] State of the Cloud 2024. I’m not ready to start using “AI Cloud” as a term, but what are tech leaders and investors thinking about the future of cloud? This report sheds some light.

[article] You could learn a lot from a CIO with a $17B IT budget. JPMorgan Chase has a massive IT budget and team, and does a ton of meaningful work. Here’s a good story about their approach.

[blog] Building PDF Open Source Services with Angular & GCP — Handling long processing tasks. Yesterday’s reading list contained an item about long-running HTTP requests. This post shows a real implementation of such a pattern.

[article] Creating Stability Is Just as Important as Managing Change. I work in a fairly dynamic place where things change often to meet the changing market needs. This post on “stability management” is important for those that don’t want to overly unnerve teams during times of change.

[blog] Optimizing CI with Bazel and Kaniko in Cloud Build. Bazel is used by lots of folks as a flexible build tool. This post goes keep into how to use it with a cloud-based CI tool.

[blog] Meta’s approach to machine learning prediction robustness. Learn more about how the Meta Ads business delivers a reliable and high-quality ML predictions solution.

[blog] Get started with Gemma on Ray on Vertex AI. Do some fine-tuning of the newest open Gemma model and see what the steps look like.

[article] The Big Interview: Solo.io CEO Idit Levine gets “Ambient.” I don’t see many long-form interviews of tech folks anymore, so this was refreshing. It’s a good read about a leader and space that’s evolved over time.

[article] 8 reasons developers love Go—and 8 reasons they don’t. Love and hate are strong emotions, but better than feeling “meh” about something. These are valid reasons you’ll like or dislike Go.

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I’m still emptying out a long reading queue from the vacation break. You’ll find some good advice in the items listed below.

[blog] Avoiding long-running HTTP API requests. Good post from Derek. There are a few patterns to consider when dealing with a request that can take a long time to process.

[blog] Building Flexible and Maintainable Go-Lang Apps. I admittedly didn’t know Google created a dependency injection framework for Go named Wire. Now I do.

[blog] RAG API powered by LlamaIndex on Vertex AI. This offers up a good walkthrough of a powerful LLM orchestration framework that you can use to customize results based on your corpus of data.

[blog] Chrome Prompt Playground. AI is definitely going to replace some work that engineers do. Simon used Claude to quickly build a playground interface for the built-in Chrome LLM.

[blog] Understanding BigQuery data canvas: how to easily transform data into insights with AI. I need to play with this more, but I like the idea behind this UX for exploring and analyzing data. The post points to a demonstration you can run yourself.

[blog] Boost performance of Go applications with profile-guided optimization. This is a very cool Go feature. Pass in CPU profiling info and get an optimized build. Here’s how to test that out.

[blog] Share your streaming data with Pub/Sub topics in Analytics Hub. This is very cool. Most hyperscale clouds offer a “data exchange” type experience to sell your business data. But we’ve added the ability to also publish streaming Pub/Sub topics for outsiders to subscribe to.

[blog] Introduction to Federated Learning. Train locally (on device, in your data center), upload a trained model, and aggregate all those models into a complete model. It’s a powerful concept that’s applied today in a few cases.

[article] Survey Surfaces Lots of Software Supply Chain Insecurity. AI chatter can drown out other topics, but don’t sleep on supply chain security. Security professionals aren’t.

[blog] AI Conundrums. Here’s a series of musings from Stephen that is well worth your time to read.

[blog] Scaling Chick-fil-A’s Design System from Tool to Service. I don’t think I’ve heard the term “DesignOps” before, but let’s roll with it. The CFA team takes a broad approach to design team work.

[blog] Counting Gemini text tokens locally. Maybe you use on LLM for small requests, and another for giant ones? How can you count input tokens to know which LLM to call? Our latest Python SDK has a local tokenizer that does the job.

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And I’m back. That was an excellent week off full of sun and fun. I tinkered around with a few tech things—reading books on data science, building a Kafka demo—but I mostly disconnected and embraced the free time. My reading queue was full of interesting items, hot takes, and educational material. Dig in.

[article] How DevProd teams got funded: 20 real-world examples. Do you have a formal developer productivity program in your team? Where does the funding come from?

[article] This AI cloud: How Google Gemini will help everyone build things faster, cheaper, better. I chatted with David at ZDNet about AI-assisted development and the future of this type of technology.

[blog] Serving a billion web requests with boring code. Here’s an excellent post with a good set of lessons learned about technology choices and design patterns.

[blog] FleetOps: Can the GKE Enterprise Stack Help Self-service Platforms Sync and Swim? Are integrated stacks “back”? Did they ever leave? Paul writes up a post that looks at an integrated GKE experience that forms the foundation of a good developer platform.

[docs] Migrate from AWS to Google Cloud: Migrate from Amazon RDS for SQL Server to Cloud SQL for SQL Server. I thought this provided a good set of advice for most any “from –> to” database migration. There are obviously some specific details to the target and destination listed here, but many parts of the workflow are general purpose.

[blog] What is Spring Modulith? Introduction to modular monoliths. If you like some of the loose coupling of a distributed system but appreciate the understand-ability of a monolithic app, you might like the “modular monolith” pattern. Here’s an example in Spring Boot.

[blog] TDD. You’re Doing it Wrong. Test-driven development is a useful practice, but there are wrong ways to do it, as John points out here.

[podcast] Navigating Corporate Giants: Jeffrey Snover and the Making of PowerShell. Listen (or read the transcript) to this conversation with Jeffrey who fought hard to build PowerShell within Microsoft.

[blog] DevRel’s Death as Zero Interest Rate Phenomenon. Not wrong, and it’s a good thing. No more devrel talking to devrel and working on whatever seems interesting. Now it’s about being aligned to biz priorities, demonstrating deep expertise, and owning the delivery of an outstanding dev experience.

[article] AI’s moment of disillusionment. Matt’s been on this “skeptic” thread for a while, but always with an eye towards folks making good choices. Don’t fall into either extreme of recklessly applying AI to everything, or, sitting entirely on the sidelines.

[blog] Latest Gemini features support in LangChain4j 0.32.0. I’m not disillusioned about AI when I keep seeing the positive progress towards quality tooling and libraries that help folks build useful systems. Great new stuff in this Java library.

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I’m glad to be home after a busy work week out of town. I’m a single dad next week while my wife and son are on a trip together, so I’m taking it as vacation. I’ll be back with this reading list on July 8th!

[blog] Making Vertex AI the most enterprise-ready generative AI platform. Lots of news here, including Gemini 1.5 Flash going GA, Gemini 1.5 Pro introducing 2 million input tokens, the Imagen 3 image-generation model is in preview, context caching, provisioned throughput, and much more.

[blog] Google Cloud expands grounding capabilities on Vertex AI. There’s a really good story here for those building low-code or code-based AI agents.

[blog] 5 Myths About Zero Trust in the Cloud, Busted. There’s a vendor angle here, but it’s still a useful look at zero trust if you’re unfamiliar with the idea.

[blog] Doubling calculation speed and other new innovations in Google Sheets. I might spend more time in Google Sheets than VS Code. That’s not a flex; it’s a cry for help. But, it’s a good thing I like Sheets.

[blog] Open challenges for AI engineering. Great presentation and writeup from Simon that looks at what’s new in AI and open challenges for the industry.

[blog] Gemma 2 is now available to researchers and developers. This open model has proven fairly popular, and the new version is performant, fast, and efficient.

[blog] Developer Experience Is Still Developing. Forrester folks have been doing solid research into developer experience, and this post teases a new report they have. Worth reading!

[blog] How to: Build a Chat Web Application with Streamlit, Cloud Run and Gemini Flash. Very straightforward demo, and it shows off the power of APIs, frameworks, and serverless.

[blog] Deploy Python pipelines on Kubernetes using the Flink runner. If you want to geek out on data streaming this weekend, you could try following along with this post.

[blog] My 5 favorite ways of keeping the technical axe sharp. How do you stay on top of things? Maybe reading this daily list is one of your strategies. This post looks at a few ways to stay sharp.

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We had a great customer council meeting today in New York, and I love it when customers can be in a room with us for a day to provide feedback and hear about roadmaps. Back home tomorrow.

[blog] Gemini 1.5 Pro 2M context window, code execution capabilities, and Gemma 2 are available today. Each of these is super valuable. Even larger input context for one-shot requests into the LLM. Use Gemini to execute and iterate on Python code. And access our latest open model.

[article] What GitHub Pull Requests Reveal about Your Team’s Dev Habits. Looking for hidden patterns in your git transactions? Some researchers did just that.

[blog] “It’s a Balance” isn’t always the answer. I liked this post that explored a handful of decision making approaches to use based on the situation at hand.

[blog] Infrastructure as Code Landscape Overview 2024. Brian uses this post to look at declarative resource-oriented provisioning tools, so not things like Ansible, Chef, or Docker. If you’ve heard of all of these tools, you are a wizard.

[blog] Transformation Regrets. We often just hear survivor stories about how great something was. History is written by the winners! But where have things gone wrong on product transformations? Marty covers that here.

[blog] 110 new languages are coming to Google Translate. More than half a billion people speak the languages we just added to Google Translate.

[blog] Structuring Go Code for CLI Applications. The “right” project structure is the one that works for you, but most of us can pick up good practices from others.

[article] How Expedia Group Moved From 21 Platform Stacks to 1. Consolidation is so hot right now! Good teams are looking to reduce redundancy is their platforms, tools, and stacks.

[blog] Enhancing Netflix Reliability with Service-Level Prioritized Load Shedding. Cool post from Netflix about how they smartly throttle pre-fetch requests to ensure that user-initiated requests get priority under load.

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I like East Coast trips because my West Coast meeting times don’t kick in until late morning. The downside? It’s relentless after that. In today’s reading list, I can across some solid advice on a variety of topics.

[blog] Unlock the Power of Conversational AI: RAG 101 with Gemini & LangChain. The post is accompanied by a notebook if you want to follow along with this scenario.

[article] Survey Surfaces Varying Levels of Enthusiasm for AI Coding Tools. Execs are ready to go on AI-assisted coding, developers not as enthusiastic. And I’m surprised that so few are running POCs to help introduce these tools.

[article] AI Work Assistants Need a Lot of Handholding. This Wall Street Journal piece looks at productivity tools, and features a short silly quote from me.

[article] The Right Way to Go “All In”. Good piece that talks about striving for greatness not JUST be being obsessive about one “identity”, but by maintaining your self-complexity.

[blog] Tips for troubleshooting Google Cloud Load Balancing backends. Whether on-premises or in the cloud, your application traffic doesn’t follow a straight path from the user to the app. There’s lots of proxy components in between, and it’s helpful to know how to troubleshoot them!

[article] Building a Platform Team at a 153-Year-Old Company. Here’s a nice roadmap for those with a deeply established IT team that wants to embrace an engineering transformation.

[article] Why Cross-Functional Collaboration Stalls, and How to Fix It. The answer is not “better executive alignment” which I found refreshing. Read this for ways to fix your “collaboration drag.”

[blog] Advancing systems research: Synthesized Google storage I/O traces now available to the community. Do you want 2.5 billion storage I/O traces from Google? I don’t know your life; maybe this is the best day ever for you. Either way, it’s cool that we’re opening up this data for others to access and explore.

[blog] Old Books that Every Architect Should Read. Plenty of tech books slink into irrelevance once a new version of software gets released, or the industry trends shift significantly. But others remain fairly timeless, as Gregor points out here.

[article] DevTools Marketing That Works, According to Developers Themselves. Adam offers up some good advice for those trying to authentically market their developer tools to a skeptical audience.

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Long day in New York today, but a great chance to chat with customers and new friends. The challenge is real with implementing AI, but wise leaders see the potential!

[blog] What Is ChatGPT Doing … and Why Does It Work? I probably shared this last year when it came out, but I came across this post again and found it useful.

[blog] Leveling up FinOps: 5 cost management innovations from FinOps X 2024. I was inexplicably staying at the hotel where this event was going on last week. I like the new scenario modeling tool.

[article] 4 keys to writing modern Python. Lots of folks are using Python nowadays, and this article highlights some new language features.

[blog] Is your AI workload secure? Sita offers up a good perspective about AI security frameworks and why they matter.

[article] This Is How To Have A Long Awesome Life: 4 Secrets From Research. None of these are shocking, nor do they require a weird pod to sleep in. Just make good choices.

[blog] Build Rag With Llamaindex To Make LLM Answer About Yourself, Like in an Interview or About General Information. LangChain has a lot of attention, but there are a handful of viable orchestration frameworks out there. Check out LlamaIndex.

[blog] why we no longer use LangChain for building our AI agents. Or maybe don’t use an LLM orchestration framework at all? This post says these frameworks can add unnecessary overhead.

[blog] GKE under the hood: What’s new with Cluster Autoscaler. With benchmarks! These Kubernetes autoscaling improvements are baked into GKE, and we’re seeing some fairly significant results.

[article] Measuring Developer Experience at Google. This piece looks at how we measure, not what. Abi digs into a recent research paper that explains our Engineering Satisfaction survey.

[article] Platform Engineering: Lessons, queries from the First Hype Cycle. Check out this take on a recent Gartner assessment of the platform engineering space.

[article] JetBrains AI Assistant to integrate Google Gemini AI models. The IDE maker is mixing and matching models for developers who want AI assistance. Maybe a trend?

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Flew to New York today and got some work done on the plane . Then took a long, meandering ride from the airport to the city. Do you have anything fun planned this week?

[blog] Common Anti-Patterns in Go Web Applications. I love me some anti-patterns! This post is easy to read, and goes through a dozen or so patterns and anti-patterns for web apps. Applies to non-Go apps as well.

[blog] The 7Rs of Cloud Migration: Guide to a Seamless Migration Strategy. Are we up to 7 “R’s” now? Here’s one take on all the approaches you should take when migrating an app to the cloud.

[article] Build your own Large Language Model (LLM) From Scratch Using PyTorch. Few folks should be building models from scratch, but it doesn’t mean you shouldn’t know how to do it!

[article] Survey Surfaces Extent of Web Application Security Crisis. It looks like we’re all writing more code and custom software. Cool, but have you also adjusted downstream ops and security practices to keep up? Doesn’t look like it.

[blog] Cloud CISO Perspectives: 3 promising AI use cases for cybersecurity. Automation and AI offer us one path out of this web app security crisis. Phil and team offer up a useful summary here.

[article] Identify — and Develop — Your Natural Strengths. This article reminds us to not over-index on weaknesses, but rather, double-down on your strengths. I think that’s true, although I am reading a book now that says the strengths that got you where you are keep you from “seeing” how to adjust next.

[article] HTMX for Java with Spring Boot and Thymeleaf. If you want to write less JavaScript, keep an eye on HTMX. I liked this walkthrough.

[article] 3 Ways AI Can Support Your Marketing Team. These reasons apply to those outside of Marketing too. Generative AI offers an interesting way to identify new viewpoints, apply creativity, and personalize results.

[article] Caching at Multiple Levels. Short post, but I like the point. Look at the embedded picture to appreciate all the different places we utilize caching in a modern app stack.

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Today was a good day. A lot got done, and I’m excited about the things my team is doing. I’m off tomorrow as part of a long weekend staycation, but will be back Monday. In the meantime, enjoy a fun list of things to read!

[blog] Infrastructure as Code reminds me of “make run-all”. Brian offers a mix of a history lesson along with a look forward at generated/rendered config files.

[blog] Announcing Anthropic’s Claude 3.5 Sonnet on Vertex AI, providing more choice for enterprises. This looks like an excellent step forward from Anthropic, and you can already access this model in most cloud platforms.

[article] How do work environments impact developer focus and productivity? Engineers want space for deep work and private spaces to avoid interruption. Makes sense!

[blog] From notebook to Cloud Run service in 10 minutes: applied to Gemini Function Calling. Good post from Karl that shows you, step by step, how to move from a Jupyter notebook to a running app.

[blog] Enhancing Cloud Usage Forecasting, Monitoring & Optimizing. I like how Etsy takes a proactive approach to FinOps and optimizing their cloud infrastructure around their target metric.

[article] What Drives Ninety-Nine Percent of Performance. Steve makes a strong point about the mistake of focusing on the minor details and missing the “big holes” in our fundamentals.

[blog] Bringing file system optimizations to Cloud Storage with hierarchical namespace. This service is widely used, and still underrated. While it’s offered “folders” for a while, these were simulated structure, not a real one. With hierarchical namespaces, it’s even more powerful.

[blog] Putting Go’s Context package into context. It’s helpful to understand this important Go package. This post goes into a lot of useful details.

[blog] Pay The Creators: A Manifesto. Here’s the first post from the “Freeman and Forrest” team that is looking to help tech creators get compensated for their work.

[blog] Benchmarking results for vector databases. The Redis folks are feeling frisky and punching back a bit. Here, they take on all comers and say they’ve got the fastest option for vector databases.

[blog] PostgreSQL pgvector: Eliminating the Need for a Dedicated Vector Database. Speed isn’t the only factor in your vector database choice, and maybe you want to use your existing PostgreSQL database to support those workloads. Yugabyte offers a good deep dive.

[article] The Most Strategic Leaders Excel in 4 Disciplines. This is good, and represents a look at what a self-aware and mature leader is comfortable doing. I’m barely either of those.

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