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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

Where Architects Sit in the Era of AI

As AI evolves from tool to collaborator, architects must shift from manual design to meta-design. This article introduces the "Three Loops" framework (In, On, Out) to help navigate this transition. It explores how to balance oversight with delegation, mitigate risks like skill atrophy, and design the governance structures that keep AI-augmented systems safe and aligned with human intent.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

NextGen Search - Where AI Meets OpenSearch Through MCP

In this article, authors Srikanth Daggumalli and Arun Lakshmanan discuss next-generation context-aware conversational search using OpenSearch and AI agents powered by Large Language Models (LLMs) and Model Context Protocol (MCP).

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Empowering Teams: Decentralizing Architectural Decision-Making

Peter Hunter & Elena Stojmilova share Open GI's journey from a slow, legacy monolith to a cloud-native SaaS platform. They detail how adopting Team Topologies and a decentralized architectural approach empowered teams. Key practices discussed include utilizing Domain-Driven Design to create a Context Map, implementing the Advice Process with Architectural Principles, and more.

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.

All in devops

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Martin Fowler on Enterprise Rails

Martin Fowler likens DHH to Kent Beck and draws conclusions about the future of Ruby and Rails in enterprisey settings.

Obie Fernandez
on Jul 11, 2006

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Topics

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

Where Architects Sit in the Era of AI

NextGen Search - Where AI Meets OpenSearch Through MCP

Empowering Teams: Decentralizing Architectural Decision-Making

Overload Protection: the Missing Pillar of Platform Engineering

Helpful links

Choose your language

News

Martin Fowler on Enterprise Rails

Magika 1.0: Smarter, Faster File Detection with Rust and AI

HL is a Fast, Rust-Based JSON Log Viewer Offering up to 2GiB/s Parsing Speed

Lessons Learned in Migrating to Micro-Frontends by Luca Mezzalira at QCon SF

Where Architects Sit in the Era of AI

InfoQ Announces January Online Architect Cohort Focused on Socio-Technical Leadership

Architecture in a Flow of AI-Augmented Change

Lessons Learned from Migrating a Legacy Test Suite to Gauge with Kotlin

Empowering Teams: Decentralizing Architectural Decision-Making

Leading from Any Position: Richard Bown on Humane Engineering Organizations

QCon AI New York 2025: Moving Mountains: Migrating Legacy Code in Weeks Instead of Years

OpenAI at QCon AI NYC: Fine Tuning the Enterprise

NextGen Search - Where AI Meets OpenSearch Through MCP

AWS Debuts “DevOps Agent” to Automate Incident Response and Improve System Reliability

Netflix Migrates to Amazon Aurora: 75% Performance Boost and 28% Cost Reduction

Yelp Publishes Blueprint for Managing S3 Server-Access Logs at Massive Scale

QCon AI New York

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