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Development

Featured in Development

Expanding Swift from Apps to Services

Cory Benfield discusses the evolution of Swift from an app language to a critical tool for secure, high-scale services. He explains how Swift’s lack of a garbage collector eliminates tail latency and shares how its "zero-cost abstractions" rival C performance. He shares Apple’s roadmap for incremental adoption and demonstrates groundbreaking new interoperability for C++ and Java ecosystems.

All in development

Architecture & Design

Featured in Architecture & Design

You’ve Generated Your MVP Using AI. What Does That Mean for Your Software Architecture?

AI‑generated code creates implicit architectural decisions, forcing teams to rely on experimentation to validate quality attributes. To get useful results from AI, teams must clearly express trade‑offs and reasoning so the model can generate solutions aligned with desired QARs.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Building Embedding Models for Large-Scale Real-World Applications

Sahil Dua discusses the critical role of embedding models in powering search and RAG applications at scale. He explains the transformer-based architecture, contrastive learning techniques, and the process of distilling large language models into production-ready student models. He shares insights on optimizing query latency, handling document indexing, and evaluating retrieval quality.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Beyond Code: How Engineers Need to Evolve in the AI Era

In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Ben Greene about embracing AI in software engineering, expanding beyond pure technical skills to understand business context, and prioritizing human empathy in increasingly automated systems..

All in culture-methods

DevOps

Featured in DevOps

From Alert Fatigue to Agent-Assisted Intelligent Observability

As systems grow, observability becomes harder to maintain and incidents harder to diagnose. Agentic observability layers AI on existing tools, starting in read-only mode to detect anomalies and summarize issues. Over time, agents add context, correlate signals, and automate low-risk tasks. This approach frees engineers to focus on analysis and judgment.

All in devops

Events

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QCon London 2026

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Early Bird ends March 10.

Learn how leading engineering teams run AI in production—reliably, securely, and at scale.

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QCon San Francisco

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Early Bird ends March 10.

InfoQ Homepage Interviews Natalia Chechina on Scaling Distributed Erlang with SD Erlang

Natalia Chechina on Scaling Distributed Erlang with SD Erlang

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10:44

Bio

Natalia Chechina received a PhD degree from Heriot-Watt University, UK in 2011. She is now a Research Associate at the University of Glasgow and leads Scalable Distributed Erlang work package (WP3) in the RELEASE project. Natalia’s main research interests are distributed and parallel computing, Erlang, mathematical and theoretical analysis, stochastic modelling, and overlay networks.

About the conference

Begun in 2012 this now annual conference hosted in Vilnius, Lithuania brings the best of the developer world to the Baltic's. The overall theme is building stuff, we have a heavy focus on lessons from trenches from the people that were there.

Feb 13, 2015

Interview with

Natalia Chechina

by

Greg Young

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