InfoQ Homepage Performance Content on InfoQ
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Wobserver: Easy to Integrate Monitoring and Debugging
Ian Luites introduces wobserver, discussing the background of the project and showing how to mount it into a Phoenix application, hook it up to Prometheus, and deploy it behind a load balancer.
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Refactoring Elixir - Lessons Learned from a Year on Exercism.Io
Devon Estes discusses some common, but less than optimal, solutions to some of the problems on exercism.io followed by refactoring, showing the performance improvements and tradeoffs made.
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Deep Learning @Google Scale: Smart Reply in Inbox
Anjuli Kannan describes the algorithmic, scaling, deployment considerations involved in a an application of cutting-edge deep learning in a user-facing product: the Smart Reply feature of Google Inbox
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Enabling High Performance Real-time Analytics for IoT Environments
Mahish Singh discusses how to use methodologies during design, development, deployment and operation for delivery of analytics platforms which offer real-time SLAs.
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Loquat: A Design for Large-scale Distributed Applications
Christopher Meiklejohn introduces Loqaut, a design for large-scale actor programming on the Erlang virtual machine.
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React+Redux at Scale
Daniel Cousineau looks at how React and Redux scale, not just in terms of quantitative performance, but in terms of architecture and team participation.
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Serverless Platform: Scientific Computation @Scale
Diptanu Choudhury talks about the platform they are developing at NASA for running computations as functions which would make it easier for researchers to program their applications & algorithms.
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Avoiding React Performance Pitfalls
Alex Grigoryan discusses the performance problems found and their solutions moving from Backbone/Java to React/Node.js at @WalmartLabs.
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Scaling with Apache Spark
Holden Karau looks at Apache Spark from a performance/scaling point of view and what’s needed to handle large datasets.
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An Introduction to Distributed Tracing and Zipkin
Adrian Cole overviews debugging latency problems using call graphs created by Zipkin and reviews the ecosystem, including tools to trace other languages and frameworks.
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Java Performance Engineer's Survival Guide
Monica Beckwith provides a step-by-step approach to finding the root cause of any performance problem in a Java app, showcasing through an example a few performance tools and the performance process.
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Deep Learning for Image Understanding at Scale
Stacey Svetlichnaya discusses strategies and challenges building deep learning systems for object recognition at scale, using automatic labels in Flickr image search as a case study.
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