InfoQ Homepage Performance Content on InfoQ
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Java at Speed: Getting the Most out of Modern Hardware
Gil Tene discusses some of the optimizations and capabilities that the latest crop of JVMs are able to apply when running on the latest servers, and performance issues with financial applications.
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Better: Fearless Feedback for Software Teams
Erika Carlson introduces effective feedback, with strategies for giving, receiving, and processing feedback, and the challenges and rewards of using feedback as a tool to improve team performance.
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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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