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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

Spec Driven Development: When Architecture Becomes Executable

Spec-Driven Development inverts traditional architecture by making specifications executable and authoritative. It transforms declared intent into validated code through AI generation and provides architectural determinism. It eliminates drift through continuous enforcement, but demands new engineering discipline in schema design and contract-first reasoning.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Somtochi Onyekwere on Distributed Data Systems, Eventual Consistency and Conflict-free Replicated Data Types

In this podcast, InfoQ spoke with Somtochi Onyekwere on recent developments in distributed data systems, how to achieve fast, eventually consistent replication across distributed nodes, and how Conflict-free Replicated Data Type (CRDTs) can help with conflict resolution when managing data.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Achieving a Culture That Works: Inclusive Leadership that Drives Lasting Success

Matthew Card discusses the intersection of leadership and inclusivity at the BBC. He explains how "changing the bar" rather than just raising it can transform team dynamics. Covering trust, psychological safety, and his "C.A.P.S." and "D.O.S.E." frameworks for resilience, he shares practical strategies for engineering leaders to eliminate toxic behaviors and empower diverse talent to thrive.

All in culture-methods

DevOps

Featured in DevOps

Platform-as-a-Product: Declarative Infrastructure for Developer Velocity

Declarative infrastructure config hides complexity, enabling developers to focus on application code. Unified YAML per service allows early cost validation, while independent CI with centralized CD balances team autonomy and deployment consistency. This standardized approach scales across organizations, making infrastructure invisible and operations automatic.

All in devops

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Topics

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

Spec Driven Development: When Architecture Becomes Executable

Somtochi Onyekwere on Distributed Data Systems, Eventual Consistency and Conflict-free Replicated Data Types

Achieving a Culture That Works: Inclusive Leadership that Drives Lasting Success

Platform-as-a-Product: Declarative Infrastructure for Developer Velocity

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Inside the Development Workflow of Claude Code's Creator

Facebook Survey Reveals Growing Adoption of Typed Python for Improved Code Quality and Flexibility

Cloudflare Year in Review: AI Bots Crawl Aggressively, Post-Quantum Encryption Hits 50%, Go Doubles

How Agoda Unified Multiple Data Pipelines Into a Single Source of Truth

Solving Fragmented Mobile Analytics: Uber’s Platform-Led Approach

Spec Driven Development: When Architecture Becomes Executable

Taking the Technical Leadership Path

Achieving a Culture That Works: Inclusive Leadership that Drives Lasting Success

What Testers Can Do to Ensure Software Security

Mistral Releases OCR 3 With Improved Accuracy on Handwritten and Structured Documents

AI-Powered Code Editor Cursor Introduces Dynamic Context Discovery to Improve Token-Efficiency

Vercel Open-Sources Bash Tool for Context Retrieval Using Local Filesystems

Platform-as-a-Product: Declarative Infrastructure for Developer Velocity

LangGrant Unveils LEDGE MCP Server to Enable Agentic AI on Enterprise Databases

Cloudflare Scales Infrastructure as Code with Shift-Left Security Practices

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