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Software Architecture

Software Architecture knowledge cards on KnowBite — curated from specialist publications, updated throughout the day.

  1. Bliki: LLM Voice

    Sometimes when I read a post, I get the growing feeling that I'm reading the output of an LLM. I can't necessarily define why, although there are the common tells (it's not the em-dashes, it's the load-bearing tapestries). As I do this my desire to read on atrophies, sometimes to the point of revulsion There are tools out there that claim to be able to tell the difference between LLM-written prose and the…

    Martin Fowler · 2026-10-29T14:28:00Z

  2. Making Failure Diagnosis Reliable with Pensive AI

    By Praneeth Yenugutala , Victor Dusa , Anastasia Samoilova , Megan Ren , Justin Wei , Marcelo Mayworm At Netflix, data and machine learning practitioners run millions of workloads each day across orchestration systems and compute engines such as Titus, Spark, Trino, and Druid. On peak days, roughly 100,000 workloads fail. When workloads fail, the failure itself is only the beginning. Someone still needs to find the…

    Netflix Tech Blog · 2026-10-26T17:04:57Z

  3. Why are good developers so wary of agentic development?

    TL;DR Good developers’ caution about agentic development comes from knowing that built isn’t the same as working in production. I’ve been surprised by how many excellent developers have been hesitant to go all in on coding agents. These are people who usually try new ways of working before anyone else and in many cases invent new tools and practices that support building the application well. So why have we had so…

    Martin Fowler · 2026-10-29T13:50:00Z

  4. Multi‑Ratio Video Resizing for Mobile Feed and Marketing

    Serdar Cellat , Yuchen Xie , Bernadette Marcu , Blaid Burgess , Cody Jarrett , Carlos Pereira , Qing Shi , Samuel Carvajal , Manuel Pamplona , Dorothy Jung , Feiko Ritsema , Benjamin Klein , Alex Woo , Eugene Lok , Anna Pulido , Rebecka Swe , Sanford Holsapple , Ranjith Kumar Shetty Introduction Clips in the Netflix mobile app. At Netflix, a crucial part of our mission is ensuring our content looks stunning on any…

    Netflix Tech Blog · 2026-10-26T16:01:02Z

  5. Fragments: October 28

    Andrej Karpathy sees a widening gap in how people see LLM capabilities. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time. Many of my colleagues are living in a…

    Martin Fowler · 2026-10-28T12:55:00Z

  6. Beyond API Compatibility: Building a Tool to Measure the Blast Radius of Library Changes

    By Roberto Perez Alcolea , Java Platform Team Quasar connects a proposed API change with observed references in consumer repositories, giving the producer evidence for a release decision At Netflix, shared Java libraries support applications developed across a large, independently evolving repository ecosystem. A library change begins in one repository, but its impact can reach many others. Producers can see the API…

    Netflix Tech Blog · 2026-10-23T18:32:51Z

  7. Fragments: October 21

    Gergely Orosz is frustrated at those that entered his explicitly “No AI” essay competition and used AI. He goes on to say: When I start to suspect some part is AI about someone I don’t know: how can I tell how much of it is? And how much time and effort do I want to invest to figure out? I fear most people do not realize this last part: that when it takes time and effort from others to figure out what % is AI, and…

    Martin Fowler · 2026-10-21T16:51:00Z

  8. Single-tenant Titus: VM-level isolation on a multi-tenant container platform

    Samartha Chandrashekar & Nick Parker You click play on a Friday night, and in the second that follows, dozens of services answer in milliseconds. Most of them run on Titus, our internal container platform. Titus is, in essence, a Kubernetes-based container hosting platform: we keep both the control plane and the data plane (the container hosts that actually run containers) patched and up to date, so application…

    Netflix Tech Blog · 2026-10-22T22:19:12Z

  9. When Software Meets Hardware

    When software meets hardware, engineering principles remain largely the same, but the sensible defaults often change. Kuldeep Singh describes our experience modernizing a large IoT fleet of battery-powered sensors. Our familiar principles remained important; what changed was how we applied them. These practices emerged through experiments, failures, and operational experience—each challenge helping us replace a…

    Martin Fowler · 2026-10-15T13:25:00Z

  10. Single-tenant Titus: VM-level isolation on a multi-tenant container platform

    Samartha Chandrashekar & Nick Parker You click play on a Friday night, and in the second that follows, dozens of services answer in milliseconds. Most of them run on Titus, our internal container platform. Titus is, in essence, a Kubernetes-based container hosting platform: we keep both the control plane and the data plane (the container hosts that actually run containers) patched and up to date, so application…

    Netflix Tech Blog · 2026-10-22T16:15:24Z

  11. Build your slide template

    Building a slide template starts with three foundational choices — colours, fonts and layouts. Sumeet Gayathri Moghe covers the basics of color theory and how to build a reusable palette, the essentials of typography, including serif, sans-serif, handwritten and monospace fonts, plus the finer points of kerning and leading, and why a near-blank layout might serve you better than the prescribed layouts that ship with…

    Martin Fowler · 2026-10-14T14:20:00Z

  12. Ontology-Driven Observability: Building an End-to-End Knowledge Graph at Netflix Scale

    Prasanna Vijayanathan , Renzo Sanchez-Silva When Jake Paul and Mike Tyson stepped into the ring in November 2024, we delivered the fight to roughly 65 million concurrent streams. On an ordinary day our infrastructure takes in more than 2 billion requests and handles upwards of 38 million real-time logging events every second. At that scale, the whole picture doesn’t fit into a single engineering team’s head or onto…

    Netflix Tech Blog · 2026-10-16T16:01:02Z

  13. The Craft of Practitioner Voice

    A couple of months ago Jim Highsmith explained how practitioners writing for each other forms a distinct style of writing. He now adds a section to the article with more detail on the craft of how we write in this style. How the writer shows up in the prose, its four principles, the role of story, how to sensibly use AI, three levels of editing, and clarity of the audience. more…

    Martin Fowler · 2026-10-13T14:06:00Z

  14. Integrating Netflix’s Foundation Model into Personalization applications

    Authors: Divya Gadde , Ko-Jen Hsiao , Dhaval Patel and Moumita Bhattacharya The motivation for building the Netflix Foundation Model for personalization was laid out in this previous blog post. The Netflix homepage is powered by several specialized models and it requires significant time and resources to maintain and continue innovating on these individual models. Therefore, we decided to centralize member…

    Netflix Tech Blog · 2026-10-14T20:02:22Z

  15. Are Harnesses Worth the Cost?

    Naresh Jain compares coding agents building the same API service with and without a behavioral harness. A frontier model, GPT-6 Sol, passed every external evaluation either way. But a cost-optimized model, GPT-6 Luna, succeeded in only 3 of 10 unharnessed runs and all 10 with the harness. While adding the harness increased token usage and runtime for Luna, the harnessed Luna runs achieved the same 10-for-10…

    Martin Fowler · 2026-10-13T13:35:00Z

  16. DataJunction as Netflix’s answer to the missing piece of the modern data stack

    by Olek Gorajek , Samuel Redai , Yian Shang Intro Our Netflix journey from data to dashboards, particularly within the space of the experimentation platform, always presented a unique set of challenges. This blog post aims to illuminate these hurdles and explain how an innovative open-source metric platform became instrumental in overcoming some of them. We’ll showcase the critical role that DataJunction played in…

    Netflix Tech Blog · 2026-10-14T19:59:08Z

  17. Fragments: October 4

    In response to my last fragments (probably the bit about us worrying if LLMs have consciousness when we when we should be wondering why they don’t have a conscience) “Metalanguage” replied : we shipped the id and forgot the superego. classic software lifecycle. I don’t know what was on their mind, but their post immediately made me think of the classic 1956 movie Forbidden Planet. Plenty of sci-fi, and other…

    Martin Fowler · 2026-10-05T04:28:00Z

  18. Measuring the Impact of Personalized Recommendations

    By Kevin Zielnicki, Guy Aridor, Aurélien Bibaut, Allen Tran, Winston Chou, and Nathan Kallus Introduction Personalization is everywhere on the internet. It shapes the products we discover, the stories we read, the music we hear, and the movies and TV shows we watch. At Netflix, personalization has been central to the member experience for decades — from the Netflix Prize to our modern recommender system that helps…

    Netflix Tech Blog · 2026-10-14T19:57:43Z

  19. Principles for effective slides

    Not every presentation needs slides, but when they earn their place, they work as a visual channel that complements the speaker rather than replacing them. Sumeet Gayathri Moghe sets out the principles that follow from that idea — control over the rate of knowledge exposition, tight coupling between slides and speaker, minimalism by default, visuals that say more than words can, and never sending your slides out in…

    Martin Fowler · 2026-09-30T14:14:00Z

  20. TimeSeries Tiered Storage Journey: Kafka/Flink Streams to Native Cassandra Cold Reads

    By Oleksii Tkachuk , Rajiv Shringi , Chris Lohfink , Abe Ratnofsky , Kartik Sathyanarayanan Introduction In an earlier post , we introduced the TimeSeries Abstraction, our high-throughput, low-latency platform designed to store and query temporal event data at scale. It has since become the operational backbone for Netflix’s largest datasets, which now span multiple petabytes. However, managing such large datasets…

    Netflix Tech Blog · 2026-10-14T19:56:08Z

  21. Bliki: Sensible Default

    A Sensible Default is a practice that, absent some overriding context, should be used when carrying out a certain kind of task. In software development such sensible defaults might include things like “use version control”, “separate UI logic from domain logic”, “automate deployment pipelines”. The term “sensible default” is a deliberate contrast to “best practice”. Folks dislike calling things “best practice”…

    Martin Fowler · 2026-09-29T13:43:00Z

  22. Behind the Scenes: Evolving Netflix’s Ads Event Pipeline for Live — Part II

    By Yogesh Nagarur Introduction In Part 1 of this series , we shared how Netflix built the Ads Event pipeline and approached it as a system design problem: replacing fragmented pipelines with a centralized collection, enrichment, and a standard data contract. The result was Ads Event Publisher, the system that collects ad telemetry from client devices, enriches it with the context of the ad that was actually served…

    Netflix Tech Blog · 2026-10-14T19:51:35Z

  23. Fragments: September 29

    Simon Willison: The more time I spend working with coding agents, the more convinced I am that they make software engineering even harder We can do amazing things with them, but unlocking their full potential requires extraordinary discipline and knowledge This has been a constant impression I get from following Willison’s writing. While things like vibe coding get a lot of attention, the real strength of agentic…

    Martin Fowler · 2026-09-29T12:41:00Z

  24. Netflix Conductor: The Next Chapter

    Netflix Conductor : The Next Chapter by Aravindan Ramkumar on behalf of the Conductor team Conductor is the workflow orchestration engine Netflix uses to stitch micro-services into reliable, observable business processes. If you’ve followed Conductor from the outside, the last thing you heard was probably the note on its GitHub repository : Netflix discontinued maintenance of Conductor OSS to refocus its resources…

    Netflix Tech Blog · 2026-10-14T19:50:17Z

  25. Fragments: September 24

    Rob Bowley is “flipping tables in his head” with anger at the current media coverage of the danger of AI killing us all The risk I’m worried about isn’t a future machine deciding to wipe us out. It’s today’s AI, being wired into everything, carelessly and fast. Cyber attacks have already cost millions of dollars in lost economic output, often without AI being involved at all. Bowley feels the push to slow down AI is…

    Martin Fowler · 2026-09-24T15:35:00Z

  26. Running Apache Spark experiments in my sleep (and on a plane)

    By Prashanth Gedde Narayanaswamy As one of Netflix’s largest and critical data pipelines, member-sessionizer consolidates tens of billions of hourly client events, encompassing user taps, playbacks, and engagement signals, into individual viewing sessions per profile. A quick two-week tuning effort spiraled into two months when standard approaches hit a wall. Because the failures only happened at full production…

    Netflix Tech Blog · 2026-10-14T19:49:11Z

  27. Healthy Feedback

    Human collaboration, like most things, improves with feedback. But it's not obvious how to make feedback effective. Anuja Karnik and Sumeet Gayathri Moghe pass on a bevy of tips for healthy feedback, based on the principle that both praise and criticism should be seen as positive. more…

    Martin Fowler · 2026-09-24T14:10:00Z

  28. The Lifecycle of LLM-as-a-Judge: Building, Aligning, and Monitoring at scale

    By Emma Yanyang Kong , JJ Tan , Ishan Gupta , Lars Olds , Claire Campbell , David Fagnan , Ratna Kavuri , Rohan Gosain , Veli Balin , Minsu Jang , Louis Garcia Introduction Any team generating text with an LLM at scale hits the same problem. You cannot evaluate everything manually. You don't know which outputs are great, which are mediocre, and which are harmful, because you simply cannot read them all. The standard…

    Netflix Tech Blog · 2026-10-14T19:48:49Z

  29. I don't like LLMs

    I have a lot of mixed feelings about AI and LLM technology. I’m fascinated by its effect on our profession, excited by the potential gains in productivity - and thus the products we could rapidly build. On the other hand, I’m fearful of the damage AI might cause: agent swarms taking over our virtual and physical infrastructure, designing bio weapons. But, back on my first hand, LLMs might also design miracle cures…

    Martin Fowler · 2026-09-17T13:50:00Z

  30. Trading a Cloud Identity for Your Own: Workload Attestation on Managed Compute

    By Dhruv Pratap Introduction Organizations that have been around for a while usually run two identity systems side by side. One belongs to the cloud provider: IAM roles, instance profiles, execution roles. The other is your own, and it is the one your internal services actually check when they decide whether to answer a request. On infrastructure you build yourself, you can bootstrap your own identity however you…

    Netflix Tech Blog · 2026-09-25T16:01:03Z

  31. Fragments: September 16

    Reports of agentic hacking continue, in this case it happened back in May and it seems OpenAI did not disclose that they were responsible. Simon Willison sees two options: After the Hugging Face and Wiki attacks OpenAI were still unable to review their previous logs and determine that they had previously attacked RubyGems. They knew about the attack on RubyGems and made the decision not to reach out to the RubyGems…

    Martin Fowler · 2026-09-16T20:05:00Z

  32. Leave the Class Path in the Rearview Mirror

    Introducing composable, module system native and agent friendly command line tools for modern Java development By Danny Thomas, JVM Ecosystem Team Recent work on the Java language to pave the on-ramp has made it easier than ever to start a Java program and evolve it using the full language and platform. At the end of that on-ramp lies Java’s mature build and dependency management ecosystem, capable of carrying…

    Netflix Tech Blog · 2026-09-18T16:01:02Z

  33. Nail the Narrative

    Sumeet Gayathri Moghe finds many folks building presentations get tangled in building slides without a coherent narrative. He advises distilling the big idea, visualizing the audience, and building a structured storyline. more…

    Martin Fowler · 2026-09-15T15:11:00Z

  34. MAPS: Netflix’s Multimodal Asset Personalization at Scale

    By Emma Yanyang Kong , Aditya Deshpande , Asad Abbasi , Bowei Yan , David Fagnan , Ashish Rastogi , Dhaval Patel , Ray Zhang Introduction The Netflix experience is a journey of discovery. Every visual cue, from the artwork on a title to the video previews that autoplay while you browse, is there to connect you with a story you will love. We call these visual cues assets , and choosing the right one for each member…

    Netflix Tech Blog · 2026-08-28T16:01:02Z

  35. Social Media Engagement: summer 2026

    A quick survey of recent engagement of my posts on social media, indicating which service has by far the most engagement, and which service has seen a precipitous decline since early 2025. more…

    Martin Fowler · 2026-09-09T16:21:00Z

  36. A Tale of Two Flink Autoscalers

    Samuel Yeboah , Francesco Di Chiara and Mingliang Liu Today, Netflix runs two Flink autoscalers. That is exactly one more than we want. We built the first one in-house years ago, when there was no mature option suited to our platform. The second came from the Apache Flink community, and it can scale workloads our homegrown system was never designed for. We now run both in production and are steadily converging on…

    Netflix Tech Blog · 2026-08-21T16:01:01Z

  37. Fragments: September 8

    Christian Catalini says we’re in a situation where we are vastly reducing the cost of generating things, but not the cost of verifying them: . This explains why the first major AI products appeared in chat, image generation, and code assistance. Not because these were the hardest human problems, but because their outputs were relatively easy to inspect. A user can judge the tone of a message, look at an image, or…

    Martin Fowler · 2026-09-08T15:22:00Z

  38. How and Why Netflix Built a Real-Time Distributed Graph: Part 3 — Querying the graph with gRPC…

    How and Why Netflix Built a Real-Time Distributed Graph: Part 3 — Querying the graph with gRPC execution API Authors: Nilesh Mishra and Ajit Koti This is the third entry of a multi-part blog series describing how we built a Real-Time Distributed Graph (RDG). In Part 1 , we discussed the motivation for creating the RDG and the architecture of the data processing pipeline that populates it. In Part 2 , we discussed…

    Netflix Tech Blog · 2026-08-07T16:01:02Z

  39. Do you even need a presentation?

    Like me, Sumeet Gayathri Moghe is tired of poor presentations with bad slide decks. He's started to write a series of posts on how to avoid these calamities, beginning with a post that questions whether a presentation is needed at all. more…

    Martin Fowler · 2026-09-08T13:42:00Z

  40. Modeling Device Capabilities for Analytics

    by Aarti Laddha , Richard Diaz-Cool , Rishika Idnani , Venkatesh Selveraj Netflix supports a vast and evolving set of features and content types, ranging from 4K streaming and immersive audio to live streaming and cloud gaming, across a diverse ecosystem of devices. However, not all devices are created equal. Hardware limitations such as available RAM, CPU cores, display capabilities, or platform support mean that…

    Netflix Tech Blog · 2026-07-31T16:01:02Z