InfoQ Homepage Architecture & Design Content on InfoQ
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Agile Architecture
Matthew Parker attempts to dispel the myth that architecture does not need to be agile.
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Human-centric Machine Learning Infrastructure @Netflix
Ville Tuulos discusses the tools Netflix built for the data scientists and some of the challenges and solutions made to create a paved road for machine learning models to production.
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CRDTs in Production
Dmitry Martyanov talks about how PayPal developed a distributed system dealing with consistency issues and shares lessons learned in developing the system based on an eventually consistent data store
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Building Resilience in Production Migrations
Sangeeta Handa shares Netflix’s migration stories, what helped them build resilience, why resilience is important, and what Netflix Billing Infrastructure is doing to avoid taking downtime.
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Scaling Slack - The Good, the Unexpected, and the Road Ahead
Mike Demmer talks about the major changes that Slack has made to the service architecture to meet the needs for larger and larger enterprise customers.
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Buckets, Funnels, Mobs and Cats or: How We Learned to Love Scaling Apps to the Cloud
The authors discuss how to migrate apps to the cloud using funnels and buckets, and then scale them and test for resilience.
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Modern Messaging with RabbitMQ, Spring Cloud and Reactor
Arnaud Cogoluègnes demos messaging apps built with RabbitMQ with Reactor on Spring Cloud. Code used in this talk is made available for download.
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Netflix Play API - An Evolutionary Architecture
Suudhan Rangarajan talks about what patterns Netflix observed in their previous architectures and how they arrived at a list of practices to create an Evolutionary Architecture.
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Paying Technical Debt at Scale - Migrations @Stripe
Will Larson talks about why migrations are the only mechanism to effectively manage technical debt as their company and code grow, and what makes running them so hard.
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AI for Software Testing with Deep Learning: Is It Possible?
Emerson Bertolo discusses lessons learned when using pre-trained Convolutional Neural Networks (CNN) models, Image Detection APIs and CNN's built from scratch for this purpose.
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Deep Representation: Building a Semantic Image Search Engine
Emmanuel Ameisen gives a step-by-step tutorial on how to build a semantic search engine for text and images, with code included.
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The Great Migration: from Monolith to Service-Oriented
Jessica Tai provides an overview of trade-offs and motivation for the SOA migration and discusses Airbnb’s architectural tenets around service building.
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