InfoQ Homepage Programming Content on InfoQ
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Strangler Things: How to De-risk Legacy Code Migrations
Shawna Martell discusses a case study in which they disentangled systems with no customer impact and zero downtime, how they prioritize feature migration, tooling, and backwards compatibility.
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Being a Responsible Developer in the Age of AI Hype
Justin Sheehy discusses the dramatic developments in some areas of artificial intelligence and the need for the responsible use of AI systems.
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Defensible Moats: Unlocking Enterprise Value with Large Language Models
Nischal HP discusses risk mitigation, environmental, social, and governance (ESG) framework implementation to achieve sustainability goals, strategic procurement, spend analytics, data compliance.
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When AIOps Meets MLOps: What it Takes to Deploy ML Models at Scale
Ghida Ibrahim introduces the concept of AIOps referring to using AI and data-driven tooling to provision, manage and scale distributed IT infra.
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Fast, Scalable, Secure: WebAssembly and the Future of Isolation
Tal Garfinkel discusses the isolation technologies that underlie WebAssembly, and the limitations of the current state-of-the-art.
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Reach Next-Level Autonomy with LLM-Based AI Agents
Tingyi Li discusses the AI Agent, exploring how it extends the frontiers of Generative AI applications and leads to next-level autonomy in combination with enterprise data.
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Kubernetes without YAML
David Flanagan discusses using programming languages to describe Kubernetes resources, sharing constructs to deploy Kubernetes resources, and making Kubernetes resources testable and policy-driven.
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Building a Successful Platform: Acceleration, Autonomy & Accountability
Smruti Patel discusses successful platform adoption. She explores topics including failed platform-building efforts, the three pillars of a successful platform, and more.
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Lessons Learned from Building LinkedIn’s AI Data Platform
Felix GV provides an overview of LinkedIn’s AI ecosystem, then discusses the data platform underneath it: an open source database called Venice.
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The AI Revolution Will Not Be Monopolized: How Open-Source Beats Economies of Scale, Even for LLMs
Ines Montani discusses why the AI space won’t be monopolized, covering the open-source model, common misconceptions about use cases for LLMs in industry, and principles of software development.
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Building a Rack-Scale Computer with P4 at the Core: Challenges, Solutions, and Practices in Engineering Systems on Programmable Network Processors
Ryan Goodfellow discusses lessons learned and open source tooling developed while delivering a product on top of the Tofino 2 switch processor.
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Retrieval-Augmented Generation (RAG) Patterns and Best Practices
Jay Alammar discusses the common schematics of RAG systems and tips on how to improve them.
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