InfoQ Homepage Platform Engineering Content on InfoQ
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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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Continuous Delivery for Foundational Platforms
Ian Nowland explains why standard CI/CD models fail for foundational platforms, sharing lessons from AWS and Datadog on how engineering leaders can implement safe progressive deployments.
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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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SafeChat: Building AI-Powered Safety Systems at Scale in a Real-Time Marketplace
Bruna Pereira shares how DoorDash built a scalable AI moderation platform. Learn how combining cheap classifiers with LLM scoring reduced incidents and cut latency in real-time chat.
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Producing the World's Cheapest Tokens: A How-to Guide
Meryem Arik explains how to cut AI inference costs by up to 90% by optimizing batch sizes, hardware selection, and request scheduling for high-volume, non-real-time workloads.
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From ms to µs: OSS Valkey Architecture Patterns for Modern AI
Dumanshu Goyal explains how moving from proxied architectures to direct access in Redis/Valkey slashes tail latency to microseconds, lowers costs, and eliminates single points of failure.
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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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The Rust High Performance Talk You Did Not Expect
Ruth Linehan discusses Momento’s 3-year migration from Kotlin to Rust, explaining how the borrow checker speeds up delivery velocity and why Rust lowers overall engineering costs in production.
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Road to Compliance: Will Your Internal Users Hate Your Platform Team?
Davide de Paolis shares how to scale internal compliance and platform engineering without breaking developer velocity, detailing automated feedback loops and "minimum viable governance" on AWS.
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Enhancing Reliability Using Service-Level Prioritized Load Shedding at Netflix
Anirudh Mendiratta and Benjamin Fedorka explain how Netflix handles massive traffic storms using service-level prioritized load shedding and client-side attempt budgets to protect critical path APIs.
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Write-Ahead Intent Log: a Foundation for Efficient CDC at Scale
Vinay Chella and Akshat Goel explain why they outgrew traditional CDC at scale. They share how they built Write-Ahead Intent Log (WAIL) using a proxy layer to decouple data replication.
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Confidently Automating Changes across a Diverse Fleet
Netflix engineer Casey Bleifer explains how the company is automating fleet-wide code changes and migrations at scale, driving adoption timelines down from months to mere days with confidence.
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