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Topics

Featured in Development

Go Channels: Understanding Happens-Before for Safe Concurrency

This article dives into the happens-before semantics of Go channels, explaining how they relate to memory visibility, synchronization, and concurrency correctness. We'll examine subtle pitfalls, illustrate them with examples, and explore the architectural implications for system designers.

Go Channels: Understanding Happens-Before for Safe Concurrency

All in development

Architecture & Design

Featured in Architecture & Design

If Architectures Could Talk, They’d Quote Your Boss

Software architecture reflects how organizations communicate and make decisions. Failures stem from misaligned incentives, unclear ownership, and structural gaps—not technical flaws. Architects must design not just systems, but the conditions for systems to thrive, using platform thinking to reduce friction and foster autonomy.

If Architectures Could Talk, They’d Quote Your Boss

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Deploy MultiModal RAG Systems with vLLM

Stephen Batifol discusses building and optimizing self-hosted, multimodal RAG systems. He breaks down vector search, nearest neighbor indexes (FLAT, IVF, HNSW), and the critical role of choosing the right embedding model. He then explains vLLM inference optimization (paged attention, quantization) and uses Mistral's Pixtral to detail multimodal large language model architecture.

Deploy MultiModal RAG Systems with vLLM

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Creating Impactful Teams Across Diverse Work Environments

Natan Žabkar Nordberg shares actionable strategies for creating impactful teams across diverse work environments, focusing on the link between culture, diversity, and ROI. He discusses how to build trust through early delegation, empower teams with guided autonomy (using improv examples), and improve communication via a "session 0" framework, offering key takeaways for all engineering leaders.

Creating Impactful Teams Across Diverse Work Environments

All in culture-methods

Featured in DevOps

From Grassroots to Enterprise: Vanguard's Journey in SRE Transformation

Christina Yakomin shares Vanguard's SRE transformation: from quarterly testing of monoliths to a mature DevOps model with continuous delivery. She explains the SRE coaching hub, self-service tools, and advanced techniques like request-rate autoscaling. She details modern challenges, including region failure game days and testing AI-backed contact centers.

From Grassroots to Enterprise: Vanguard's Journey in SRE Transformation

Events

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QCon San Francisco 2025

Get production-proven patterns from the leaders who scaled a GenAI search platform to millions, migrated a core ML system without downtime, and architected a global streaming service from the ground up.

Early Bird ends Nov 11.

QCon AI New York 2025

Move beyond AI demos to real engineering impact. Discover how teams embed LLMs, govern models, and scale inference pipelines to accelerate development securely.

Early Bird ends Nov 11.

QCon London 2025

Benchmark your systems against leading engineering teams. See what really works in FinOps, modern Java, and distributed data architectures to balance cost, scale, and reliability.

Early Bird ends Nov 11.

InfoQ Homepage Presentations Data Pipelines for Real-Time Fraud Prevention at Scale

AI, ML & Data Engineering

Data Pipelines for Real-Time Fraud Prevention at Scale

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49:58

Summary

Mikhail Kourjanski discusses the architecture of PayPal’s data service which combines a Big Data approach with providing data in real time for decision making in fraud detection.

Bio

Mikhail Kourjanski is the Lead Data Architect at PayPal, responsible for the data architecture of the PayPal real-time decisioning platform is that handles billions of events per day and maintains dozens of petabytes of data.

About the conference

QCon.ai is a AI and Machine Learning conference held in San Francisco for developers, architects & technical managers focused on applied AI/ML.

Recorded at:

May 23, 2018

by

Mikhail Kourjanski

This content is in the AI, ML & Data Engineering topic

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