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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

Trustworthy Productivity: Securing AI Accelerated Development

Autonomous AI agents amplify productivity but can cause severe damage without safeguards. Defend the ReAct loop—context, reasoning, and tools—through provenance gates, planner-critic separation, scoped credentials, sandboxed code, and STRIDE/MAESTRO threat modeling. With robust logging, bounded autonomy, and red-teaming, agents can deliver trustworthy productivity while minimizing risk.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Powering Enterprise AI Applications with Data and Open Source Software

Francisco Javier Arceo explored Feast, the open-source feature store designed to address common data challenges in the AI/ML lifecycle, such as feature redundancy, and low-latency serving at scale.

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.