microservices
microservices on Beyond Market Intelligence: a running collection of 10 stories we have gathered and hand-picked because they are worth your time. Every post here touches on microservices 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 microservices, 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.
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."
Pods as Workers, Not Agents: Rethinking the Deployment Unit for AI Agents on Kubernetes
Running AI agents on Kubernetes often prompts a critical question: should each agent occupy its own Pod? The kagent project offers a compelling alternative, arguing that dedicating individual Pods to agents—which can be bursty, short-lived, and require human interaction—is inefficient. Agent-substrate introduces a control plane to intelligently schedule logical "Actors" onto robust, long-lived worker Pods, optimizing resource utilization. Explore this transformative approach, further detailed in Mark Silvester’s insightful piece, and consider how it redefines the deployment unit for AI agents.
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."
Article: Enabling Evolutionary Architecture Through the Preservation of Change Locality
Why do seemingly minor features trigger complex cross-team negotiations? This article, "Enabling Evolutionary Architecture Through the Preservation of Change Locality," explores how boundary drift erodes change locality, increasing cognitive load. Authors Michael Fischer, Nicholas Lawrence, and Monica Karekar present practical sociotechnical strategies—redistributing mechanics, exposing essential policy, and rehearsing exception paths—to restore domain boundaries and foster a truly evolutionary software architecture. For further insight into related technologies, see our article, "Embabel Agent Framework Reaches 1.0."
How is your enterprise tracking AI agent telemetry? Groundcover thinks it should never leave your cloud
The rise of AI agents is fundamentally reshaping enterprise data management, particularly how telemetry is tracked. Groundcover thinks it should never leave your cloud, offering a compelling alternative to traditional observability platforms. With $160 million in funding, the company is challenging established players like Datadog and Splunk by prioritizing customer-controlled data storage and a predictable, host-based pricing model. Explore how this approach, combined with eBPF technology, is transforming observability into infrastructure for autonomous software, as discussed further in our recent article, "Smallest.
Presentation: The Free-Lunch Guide to Idea Circularity
Recognizing that truly novel ideas in technology are rare, Holly Cummins’s presentation, "The Free-Lunch Guide to Idea Circularity," offers a critical perspective for engineering leaders. Cummins maps historical architectural tradeoffs to current cloud, microservices, and AI hype cycles, revealing recurring patterns. She connects financial, technical, epistemic, and sleep debt to illuminate how shifting assumptions impact sustainability and proven engineering disciplines. For deeper insights into related infrastructure considerations, explore "AWS Lambda's Self-Managed Code Storage Lifts the Account Quota, Not the Function Size Limit."
Article: The Hard-Stop Rule: From 3 HCM Monoliths to 120 Domain Microservices
For five years, a payroll and HR software team achieved a remarkable transformation: dismantling three monolithic systems into over 120 domain microservices—all without a dedicated migration budget. This pull-based approach, detailed in Prashanth Pasham’s article "The Hard-Stop Rule," prioritized building new features as independent services, sidestepping legacy modifications. Discover the tools, strategies, and challenges encountered during this ambitious rebuild, and learn how costs were effectively managed. For further insight into AI's evolving role, explore "Microsoft launches AI cybersecurity model," also available on our site.
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."
DoorDash Uses Envoy and Valkey for a 1.5M RPS Proxy Cache with 99.99999% Availability
DoorDash achieves unparalleled data efficiency with Entity Cache, a novel proxy caching platform built on Envoy and Valkey. This innovative solution reduces redundant service-to-service requests within their microservices architecture, handling over 1.5 million requests per second with an impressive 99.99999% availability. Through caching, event-driven invalidation, and robust failure handling, Entity Cache optimizes performance and ensures consistent reliability. For those interested in exploring related advancements in data analysis, consider our survey on deep learning for scRNA-seq analysis.
Linkerd 2.20 Delivers Smarter Traffic Management and Dramatic Efficiency Gains
Linkerd 2.20 significantly elevates Kubernetes networking with smarter traffic management and dramatic efficiency gains. This release, announced by the Linkerd community, delivers key enhancements across performance, observability, and control. As a CNCF-graduated service mesh, Linkerd remains the leading lightweight choice for Kubernetes, empowering teams to optimize application delivery. Explore the new features to discover how Linkerd 2.20 streamlines operations and unlocks greater resource utilization within your existing infrastructure.