scalability
scalability on Beyond Market Intelligence: a running collection of 31 stories we have gathered and hand-picked because they are worth your time. Every post here touches on scalability in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around scalability, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Switchyard: NVIDIA’s Open Source Routing Library
Stop overspending on AI inference. NVIDIA’s Switchyard, a newly released open-source routing library, offers a powerful solution: intelligent request routing. By directing less demanding AI tasks to more cost-effective models, Switchyard significantly reduces both latency and expense—often with minimal impact on overall quality. Explore how this innovative approach optimizes your AI infrastructure. For a glimpse into the creative possibilities unlocked by advanced AI models, see our recent article, "Everyone's Testing Claude Fable 5.1 On Code."
Presentation: Instrumentation at Scale: Having Your Performance Cake and Eating It Too
Unlock full system visibility without performance compromise. Brian Martin, drawing on his experience at IOP Systems, presents "Instrumentation at Scale: Having Your Performance Cake and Eating It Too," exploring strategies for low-overhead instrumentation. Learn about atomic primitives, per-CPU sharding, and eBPF integration—critical techniques for software architects and engineering leaders. Discover how to maintain comprehensive insights without sacrificing speed. For deeper exploration of performance optimization, see our article, "This Python Library Can Run Pandas Workloads Up to 20x Faster."
Presentation: Beyond Line Charts: Why Some Diversity in Telemetry Visualization Is Long Overdue
For years, system observability has relied too heavily on line charts, obscuring critical insights. Yao Yue, drawing on 15 years of experience operating large-scale systems, argues it's time for a change. This presentation, "Beyond Line Charts," explores the fundamental limitations of this default visualization and demonstrates how engineering leaders can transform telemetry data to directly address capacity, latency, and fleet-sizing challenges.
Presentation: From DVDs to Global Streaming: How Netflix’s Commerce Architecture Actually Evolved
Join us as Kasia Trapszo illuminates Netflix’s remarkable journey, transforming from a U.S.-based DVD service to a global streaming powerhouse. This presentation details the evolution of their commerce architecture, navigating complex international payments, regulatory hurdles, and the shift from monolithic systems to domain-driven design. Discover how Netflix re-architected its infrastructure to handle massive live-event demand, demonstrating the enduring principle that exceptional systems thrive through continuous adaptation. For deeper insights into flexible data workflows, explore "AWS Introduces Specification Driven Composition."
Building a Proper Backend for My LangGraph AI Agent
Moving beyond demo agents, building a robust backend for your LangGraph AI agent is crucial for handling real-world data, like booking information. This post details the practical steps to transform a prototype into a reliable system capable of persistent storage and retrieval. We'll explore key architectural considerations and best practices for ensuring data integrity and scalability. For broader insights into building AI safety systems at scale, consider “Presentation: SafeChat,” which details DoorDash’s approach to content moderation.
![SSOG-Attention: Sum Of Separable Gaussians as a sub-quadratic and scalable alternative to SDPA. [R]](https://preview.redd.it/pepwlp93opjh1.gif?width=320&crop=smart&s=2c59acf93fb52e53083ca4ef7d9885451e6c387b)
SSOG-Attention: Sum Of Separable Gaussians as a sub-quadratic and scalable alternative to SDPA. [R]
Scaled dot-product attention (SDPA) faces a significant scalability bottleneck, exhibiting O(N²·d) complexity. A new approach, Sum Of Separable Gaussians (SSOG), offers a compelling alternative. SSOG learns a few Gaussian atoms per head, geometrically steering them for efficient computation—achieving a reduced complexity of O(N·√N·d). Experiments demonstrate SSOG’s superiority on smaller datasets like CIFAR100 and equivalent, faster convergence on larger datasets like IN1k, while maintaining memory efficiency. Explore the full details and results in the blog post and repository.
Three OpenAI Engineers Shipped A Million Lines. Your Ten-Hour Agent Run Starts Here.
Three OpenAI engineers recently achieved a significant milestone: shipping a million lines of code, paving the way for extended agent runs—now available for you. This marks a pivotal shift towards more autonomous and capable AI workflows. Explore the possibilities of ten-hour agent executions, designed to tackle complex tasks with unprecedented efficiency. For deeper insights into the challenges of automated evaluation, consider our article, "Why You Shouldn’t Always Trust LLMs as Judges," available on our site. Discover how this advancement empowers your data journey.
Presentation: Producing the World's Cheapest Tokens: A How-to Guide
Meryem Arik’s presentation, "Producing the World's Cheapest Tokens: A How-to Guide," offers actionable strategies for dramatically reducing costs in LLM inference. Designed for software architects and engineering leaders, Arik explores critical trade-offs across hardware, runtimes, and decoding techniques to achieve order-of-magnitude savings in high-volume, non-real-time workloads. Discover how smart queue reordering and other innovations can transform your data management approach. For further exploration of AI governance, see our recent article, "IBM and Red Hat Expand Lightwell."
fru - Fast Random Forest Implementation [P]
Introducing Fru, a newly published, high-performance Random Forest implementation built in Rust. Featuring Python and R bindings, Fru delivers significant speed advantages over established libraries. Benchmarks show Fru outperforming scikit-learn by factors in Python and exceeding the ranger package in R, sometimes by several times—enhanced by a novel permutation importance implementation. Its layered design enables seamless integration with data tools like pandas and polars.
How Pinterest Secures AWS Infrastructure at Scale with a Centralized Terraform Pipeline
Pinterest manages its expansive AWS infrastructure with a sophisticated, centralized approach. Recently, they unveiled the Resource Provisioner Pipeline (RPP), a custom Terraform execution engine designed for secure, scalable resource provisioning. The RPP enforces least-privilege access and mandates dual-control reviews, adding critical guardrails to GitHub Actions workflows. This architecture ensures stringent security protocols as Pinterest continues to scale. For further insight into automation strategies, explore “Stripe Uses Graph Search and State Machines to Automate Database Remediation.”
Presentation: Keeping ChatGPT Fast as AI Development Accelerates
As AI development accelerates, maintaining speed and scalability presents a hidden challenge—systemic performance costs beyond simply adding GPUs. In this presentation, Martin Spier of OpenAI reveals how agentic workflows, while boosting code change volume, impact product performance at global scale. He shares how deploying always-on AI agents can automate critical optimization tasks like profiling and regression detection. Discover strategies for continuous performance management—a vital consideration as demonstrated by Cloudflare’s recent introduction of Cloudflare Computer, a runtime designed specifically for AI agents.
Cloudflare Launches Persistent, Stateful, Computer-like Environments for Agents
Cloudflare is redefining the landscape for AI agents with Cloudflare Computer, a new open-source runtime providing a more persistent and stateful environment—essentially, a digital "computer"—instead of fleeting containers. Built upon Cloudflare Isolates for rapid serverless execution, Computer promises significant cost reductions, speed improvements, and enhanced scalability for AI workflows. This innovative approach addresses a critical need as AI increasingly transforms incident response, as explored in our recent article on AI's impact on engineering teams.
Exclusive: Mirendil inks $100M+ Google Cloud deal to scale self-improving AI
Mirendil, a leader in AI-native spreadsheet technology, has secured a significant partnership with Google Cloud, valued at over $100 million. This expansion will dramatically scale Mirendil’s compute infrastructure, fueling research into self-improving AI systems. The focus? Accelerating scientific discovery and propelling advancements in AI development itself. This investment underscores Mirendil's commitment to a future-focused approach to data management. For a broader look at AI’s impact on personalized experiences, explore our piece on how startups are leveraging AI for e-commerce recommendations.
Article: Runtime-Agnostic AI Workflows: A Pattern for Production Durability and Fast Eval Iteration
AI workflows face a fundamental challenge: production durability clashes with rapid iteration. Ensuring reliability through persistence and distribution inherently slows down the fast feedback loops crucial for evaluating LLM output. Mateus Moury’s article, "Runtime-Agnostic AI Workflows," explores a pattern designed to resolve this tension, enabling both robust production deployments and accelerated experimentation. Discover how to achieve this balance and build more resilient AI systems.
Texas halts new data centers as governor calls for audits
Texas’s rapid data center boom is facing a critical pause. Governor Abbott has ordered audits and halted approvals for new facilities, citing concerns over strain on the state’s power grid. Previously a magnet for tech companies seeking favorable regulations and plentiful energy, Texas now demonstrates that even robust infrastructure has limits. This development highlights a growing tension between data-intensive innovation and resource management.
Presentation: Microservices Platforms: When Team Topologies Meets Microservices Patterns
Accelerate your microservices delivery with a strategic blend of Team Topologies and proven patterns. Chris Richardson’s presentation explores how internal platforms, built around six key areas—security, observability, build, and deployment—can minimize cognitive load for development teams. Richardson shares practical strategies to avoid common platform engineering challenges and maximize efficiency. Discover how to empower stream-aligned teams and unlock faster innovation. For a deeper dive into the broader context, see our related article, "Platform Engineering Maturity Emerges as a Key Differentiator for Enterprise AI Success."
Presentation: Parting the Clouds: The Rise of Disaggregated Systems
The future of cloud databases is shifting. Murat Demirbas’s presentation, "Parting the Clouds: The Rise of Disaggregated Systems," explores this evolution, driven by the need for greater cost efficiency and scalability. Demirbas details how decoupling compute from storage—a concept foreshadowed by classical Paxos—unlocks elastic scaling and robust fault isolation. He analyzes the network tradeoffs and emerging self-assembling database designs shaping this transformative architecture. For deeper insight into related trends, explore "AWS Lambda's Self-Managed Code Storage" and its implications.
Nscale buys Anyscale as it seeks to own more of the AI compute stack
Nscale, a British AI neocloud provider, is strategically expanding its AI compute stack with the acquisition of Anyscale, a software startup specializing in scaling AI workloads. This move positions Nscale to offer a more comprehensive solution for businesses navigating the complexities of distributed AI. Anyscale's expertise in scaling across diverse infrastructure complements Nscale’s existing capabilities. As Murat Demirbas explored in "Parting the Clouds," this shift towards disaggregated systems is driven by evolving cloud economics and a demand for greater efficiency.
Cloudflare Makes Internal DNS Generally Available
Cloudflare has made Internal DNS generally available, simplifying network management by unifying private and public DNS operations on a single platform. This authoritative and recursive DNS service delivers enhanced control and streamlined workflows for private networks. Consolidating DNS infrastructure reduces complexity and improves security, empowering organizations to manage their data more effectively. For deeper insights into the computational demands of modern AI models, explore our recent article, "How Much Does a Local LLM Actually Cost to Run?"
Multi-Tenant SaaS: Which Architecture Would You Choose? [D]
Navigating multi-tenant SaaS architectures for sensitive data, particularly with RAG and LLMs, demands careful consideration. For your Sri Lankan document platform, a global RAG layer alongside user-specific RAG (Option 1) presents a compelling starting point. It avoids the complexities and costs of fine-tuning while enabling access to a curated knowledge base for accurate, general responses, supplemented by private document search. Scalability to thousands of users is readily achievable with this design.
Understanding GPU Inference Workloads [D]
Delve into the complexities of GPU inference workloads with our latest exploration, sparked by a community discussion on sourcing compute. We're investigating common pain points encountered when utilizing services like RunPod or Vast.ai, seeking to understand your experiences and optimize deployment strategies. Share your insights in the comments or via direct message – your feedback is invaluable. For a deeper dive into related challenges within live streaming deployments, see our discussion on "CICD / KAFKA / KUBERNETES / Interview questions (MLE)."
How to pick an AI model in 2026
Navigating the AI model landscape in 2026 will demand a strategic approach. Choosing the right model requires prioritizing specific task performance, cost-effectiveness, and integration capabilities. Expect a market saturated with specialized models, making broad, general-purpose options less appealing. Focus on evaluating models based on rigorous benchmarks and real-world application testing. Consider scalability and ongoing maintenance costs as critical factors. For deeper insights into optimizing infrastructure alongside AI investment, explore our article, "Uber’s Zero Growth Stack."
CICD / KAFKA / KUBERNETES / Interview questions (MLE) [R]
Preparing for a Machine Learning Engineer interview focused on live streaming deployments? Your friend should prioritize questions around CI/CD pipelines, Kafka for data streaming, and Kubernetes for orchestration. Expect deep dives into topics like schema management, fault tolerance, and scaling strategies within these systems. Understanding how to debug deployment issues and monitor performance in a live environment is also key. For a more detailed look at building end-to-end ML platforms, see our recent article, "Recent project I worked on: End to End Edge ML platform."
Podcast: Rethinking Data: Moving From the Traditional Three-Tier Web Stack to Client-Side Event Sourcing
Johannes Schickling challenges conventional wisdom in our latest podcast, "Rethinking Data." He details his journey moving beyond the traditional three-tier web stack to a local-first architecture, sharing his experience building Overtone—a music curation app—with client-side event sourcing and SQLite. This episode unpacks the practical trade-offs inherent in event sourcing and CRDTs, offering valuable insights for developers seeking a more agile data management approach. For further exploration of evolving architectures, see our article, "An Evolutionary Architecture Pattern for Managing AI’s Pace of Change."