InfoQ Homepage Infrastructure Content on InfoQ
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Spritely: Infrastructure for the Future of the Internet
Christine Lemmer-Webber and David Thompson discuss Spritely's vision for a decentralized web, explaining capability-based security, actor models, and local-first tech to build resilient apps.
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Fixing the AI Infra Scale Problem by Stuffing 1M Sandboxes in a Single Server
Felipe Huici discusses scaling microVM sandboxes for AI workloads, explaining how millisecond cold boots, high density, and stateful scale-to-zero achieve efficient, secure cloud isolation.
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A Few Predicted Talks From QConAI 2030
Meryem Arik shares 2030 predictions on rising token costs, parallel agent architectures, non-developer app explosion, vendor lock-in, incoming AI regulations, and shifting software engineering roles.
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Beyond Prompting: Context Engineering for Production-Grade AI
Ricardo Ferreira explains how context engineering overcomes LLM latency, cost, and memory limitations in AI systems, sharing architectural lessons from building a custom Alexa backend with Redis.
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Prompt to Prod: Engineering an Autonomous SDLC at Scale
Andrew Swerdlow shares how Roblox transitions from AI autocomplete to fully autonomous software development with "Prompt to Prod," covering safety guardrails, infrastructure, and metrics.
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Why Fetch When You Can Sync? Building Local-First Apps on a Sync Engine Architecture
James Arthur explains how extending reactivity to the server via Electric and TanStack DB replaces manual data fetching with real-time sync for high-performance, agentic web applications.
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Understanding Progressive Collapse: How To Avoid A Cascading Failure
Sam Newman explains how to apply civil engineering’s concept of progressive collapse to digital systems, sharing actionable techniques to mitigate cascading failures in complex cloud architecture.
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From Fab To Token - The State Of The Market
Jordan Nanos explains how hardware constraints, data center scale, and chip co-design shape modern AI performance and tokenomics from silicon to inference.
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Adopting Memory-Safety and Fine-Grained Compartmentalisation with CHERI
David Chisnall explains how CHERI architecture unifies hardware capabilities and pointer metadata to deliver memory safety and fine-grained, efficient software compartmentalization.
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Autonomous Data Products for the Autonomous Era: Rethinking Data Architecture for GenAI
Jörg Schad discusses how to bridge the gap between prototypes and production by standardizing data access for GenAI, using autonomous data products to prevent context rot and ensure safety.
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Platform Engineering for Everyone - Success Can’t Be Coded
Max Korbacher shares why internal developer platforms fail and how engineering leaders can build successful, product-minded platforms by focusing on people and process over raw technology.
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Chaos Engineering GPU Clusters
Bryan Oliver explains how to apply chaos engineering to massive GPU clusters. Learn how to handle hardware variability, NUMA nodes, and network faults to secure your AI infrastructure.
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