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Development

Featured in Development

How to Use Apache Spark to Craft a Multi-Year Data Regression Testing and Simulations Framework

Vivek Yadav, an engineering manager from Stripe, shares his experience in building a testing system based on multi-year worth of data. He shares insights into why Apache Spark was the choice for creating such a system and how it fits in the "traditional" engineering practices.

All in development

Architecture & Design

Featured in Architecture & Design

Architecting Planet Scale, Modern Apps in the Cloud

George Mao shares a deep dive into evolving a basic web application to a planet-scale, global architecture. He walks through five stages of maturity, focusing on adding enterprise-grade security, achieving global high availability and disaster recovery, optimizing content delivery costs with CDNs, and implementing globally consistent persistence using serverless technologies.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Securing AI Assistants: Strategies and Practices for Protecting Data

Andra Lezza explains the criticality of data security for AI copilots, detailing the OWASP AI Exchange threat model and the OWASP Top 10 LLM risks. She reviews two copilot architectures - independent (single domain) and integrated (multi-tenant) - listing specific threats, controls, and best practices like granular authorization, templates, and DevSecOps to secure the entire AI data supply chain.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Transforming Life Sciences: AI, Vibe Coding, and Drug Development Acceleration

In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Satish Kothapalli about the transformative impact of AI and vibe coding in life sciences software development, the acceleration of drug development timelines, and the evolving roles of developers in an AI-augmented environment.

All in culture-methods

DevOps

Featured in DevOps

Overload Protection: The Missing Pillar of Platform Engineering

Overload protection is often overlooked in platform engineering, leaving teams to create inconsistent, fragile fixes. Centralized rate limits, quotas, adaptive controls, and clear visibility give services predictable ways to handle traffic spikes, reduce reliability debt, and prevent cascading failures across systems.