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Development

Featured in Development

What I Wish I Knew When I Started with Green IT

Ludi Akue discusses how the tech sector’s rising emissions impact our global climate goals. Drawing from her experience as a CTO, she explains seven key lessons for implementing Green IT. She shares insights on LCA assessments, the paradox of microservices, and why FinOps doesn’t always equal green.

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Architecture & Design

Featured in Architecture & Design

Andres Almiray on How to Release Any Software to Any OS with JReleaser

Andres Almiray, a serial open-source contributor and the creator of JReleaser, discusses the project's state, noting that the tool is usable across any ecosystem, not just Java. He also touches on the Common House Foundation's mission.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Evaluating AI Agents in Practice: Benchmarks, Frameworks, and Lessons Learned

This article introduces practical methods for evaluating AI agents operating in real-world environments. It explains how to combine benchmarks, automated evaluation pipelines, and human review to measure reliability, task success, and multi-step agent behavior. The article also discusses the challenges of evaluating systems that plan, use tools, and operate across multiple interaction turns.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Image Processing for Automated Tests

Stefan Dirnstorfer discusses the shift from DOM-based testing to visual UI agents. He explains why LLMs often fail at precision tasks - like spotting one-pixel shifts or broken road networks - and shares how advanced image registration and "Chain-of-Thought" vision processing are essential for reliable QA. Learn why combining generative AI with classical algorithms is the future of automation.

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DevOps

Featured in DevOps

Change as Metrics: Measuring System Reliability through Change Delivery Signals

System changes are the primary driver of production incidents, making change-related metrics essential reliability signals. A minimal metric set of Change Lead Time, Change Success Rate, and Incident Leakage Rate assesses delivery efficiency and reliability, supported by actionable technical metrics and an event-centric data warehouse for unified change observability.

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AI, ML & Data Engineering

QCon London 2026: Ontology‐Driven Observability: Building the E2E Knowledge Graph at Netflix Scale

Prasanna Vijayanathan and Renzo Sanchez-Silva, both Engineers at Netflix, presented “Ontology‐Driven Observability: Building the E2E Knowledge Graph at Netflix Scale” at QCon London 2026, where they discussed the design and implementation of an end-to-end knowledge graph that models the Netflix user experience.

Michael Redlich
on Mar 18, 2026

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Topics

What I Wish I Knew When I Started with Green IT

Andres Almiray on How to Release Any Software to Any OS with JReleaser

Evaluating AI Agents in Practice: Benchmarks, Frameworks, and Lessons Learned

Image Processing for Automated Tests

Change as Metrics: Measuring System Reliability through Change Delivery Signals

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Choose your language

News

QCon London 2026: Ontology‐Driven Observability: Building the E2E Knowledge Graph at Netflix Scale

QCon London 2026: All Tech Debt is Not Created Equal

Google Open-Sources the Common Expression Language for Python

QCon London 2026: The Hidden Power of Boring Problems

QCon London 2026: From DVDs to Global Streaming How Netflix’s Commerce Architecture Actually Evolved

QCon London 2026: Managing Asynchronous APIs at Scale

DoorDash Builds DashCLIP to Align Images, Text, and Queries for Semantic Search Using 32M Labels

Image Processing for Automated Tests

Beyond the Code: Hiring for Cultural Alignment

Information Flow: The Hidden Driver of Engineering Culture

QCon London 2026: Ontology‐Driven Observability: Building the E2E Knowledge Graph at Netflix Scale

QCon London 2026: Reliable Retrieval for Production AI Systems

QCon London 2026: Behind Booking.com's AI Evolution: The Unpolished Story

QCon London 2026: Uncorking Queueing Bottlenecks with OpenTelemetry

QCon London 2026: Shipping Constantly with Humans and Beyond at Monzo

AI Is Amplifying Software Engineering Performance, Says the 2025 DORA Report

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