InfoQ Homepage Presentations
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How To Run on Three Clouds at Once, and When Not To
Ross McFarlane and Kevin Holditch explain how Form3 engineered a triple active multi-cloud architecture across AWS, GCP, and Azure to deliver ultra-resilient, regulatory-compliant payment systems.
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Accelerating Performance by Incrementally Integrating Rust Into Existing Codebase
Lily Mara explains how engineering teams can achieve 100x function-level speedups and lower infrastructure costs by using PyO3 to incrementally refactor critical Python codebases into Rust.
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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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Platform Engineering in the Age of AI
The panelists discuss how internal developer platforms adapt for AI-assisted engineering, balancing standardization, guardrails, and developer autonomy to shape next-gen platform engineering.
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A Solopreneur's Journey: From Engineer to Puzzle Master and Storyteller
Joe Cassavaugh shares how he built a $2M+ solopreneur game franchise. He discusses tech stack evolution, Unity refactoring, content pipelines, and building sustainable software.
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From AI Agent Demo to Production: Automated Testing and Evaluation
Zhou Yu explains why 95% of AI agents fail to reach production and shares how simulation-driven evaluation, synthetic users, and automated CI/CD testing unlock enterprise deployment.
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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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From S3 to GPU in One Copy: Rethinking Data Loading for ML Training
Onur Satici discusses Vortex, an open-source columnar file format designed to bypass CPU bottlenecks, enabling ultra-fast S3-to-GPU data streaming and dynamic query pruning at up to 60 Gbps.
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Instrumentation at Scale: Having Your Performance Cake and Eating It Too
Brian Martin explains how to achieve high-performance instrumentation without massive runtime overhead, comparing Rust metrics libraries, counter designs, and eBPF system telemetry techniques.
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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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Beyond Line Charts: Why Some Diversity in Telemetry Visualization Is Long Overdue
Yao Yue explains why line charts often fail during production incidents and shares how software architects & engineering leaders can transform telemetry data to answer critical operational questions.
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Running AI at the Edge: Running Real Workloads Directly in the Browser
James Hall explains why engineering teams should shift AI workloads on-device. He shares local inference strategies, WebGPU optimization techniques, and architecture choices for zero-trust privacy.
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