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Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.

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InfoQ Reading List

Google Adds Cycle-Level Kernel Profiling to XProf

Google has added a Kernel Profiling suite to XProf. This is its open-source profiler for TPU workloads. Now, developers can see cycle-level details in custom Pallas kernels. Before, these kernels appeared as single opaque blocks in trace captures.

By Claudio Masolo

Article: Modular Edge Computing at Multi-Tenant SaaS Scale on Cloudflare Workers

At multi-tenant SaaS scale, a monolithic edge worker creates deployment coupling and broad blast radius. The article presents a modular Cloudflare Workers architecture using service bindings, with image optimization as a worked example of per-tenant format negotiation and device-aware sizing. It covers multi-CDN differences, staged releases, configuration, and testing.

By Chintan Tank

Elastic Beanstalk Adds Cluster Mode, Running Applications on Shared EKS Clusters

AWS has added Cluster Mode to Elastic Beanstalk, running applications on EKS clusters the service creates and operates. Clusters are assigned by subnet set and cannot be changed afterward, direct cluster access is service-managed, and AWS recommends separate clusters for untrusted or regulated workloads. The mode adds EKS and Auto Mode fees that EC2 discounts do not reduce.

By Steef-Jan Wiggers

Google Open-Sources AX a Kubernetes Style Orchestrator for Autonomous AI Agents

Google has open-sourced AX, an orchestrator designed for managing autonomous AI agent workloads. AX operates on a runtime, Agent Substrate, treating agents as stateful actors. It provides resource-efficient task suspension and resumption to optimise performance and reduce latency in idle phases. It features a control plane with Kubernetes-style primitives for managing agent tasks and resources.

By Olimpiu Pop

GitLab Duo Expands Self-Hosted AI Options Through Microsoft Foundry

GitLab has expanded GitLab Duo Self-Hosted to support models deployed through Microsoft Foundry, letting organizations run GitLab's AI development capabilities against models hosted in their chosen Azure environment.

By Craig Risi

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