InfoQ Homepage Performance Content on InfoQ
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Caching for Microservices - Introduction to Pivotal Cloud Cache
Pulkit Chandra discusses how to use Pivotal Cloud Cache and its performance under load, demoing a Spring Boot app which uses Spring Data Geode to talk to a Pivotal Cloud Cache cluster.
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NDBench: Benchmarking Microservices at Scale
Vinay Chella and Ioannis Papapanagiotou discuss Netflix's Cloud benchmark system, how it was integrated with their release cycle, showcasing how multiple instances can be monitored from a single UI.
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Performance beyond Throughput: An OpenJ9 Case Study
Marius Pirvu talks about the new advancements in the area of JVM performance using the latest open source JVM technology at Eclipse OpenJ9 running with OpenJDK.
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Getting Data Science to Production
Sarah Aerni covers the nuts and bolts of the Einstein Platform, a system that enables the automation and scaling of Artificial Intelligence to 1000s of customers, each with multiple models.
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ML for Question and Answer Understanding @Quora
Nikhil Dandekar discusses how Quora extracts intelligence from questions using machine learning, including question-topic labeling, removing duplicate questions, ranking questions & answers, and more.
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Go Programming Language
Dave Cheney discusses the Go language: writing and interpreting benchmarks, using performance tools built into the Go runtime, GC and writing GC-friendly code.
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Scaling Slack
Bing Wei examines the limitations that Slack's back-end ran into and how they overcame them to scale from supporting small teams to serving large organizations of hundreds and thousands of users.
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Monitoring Modern Architectures with Data Science
Dave Casper talks about how modern data science and algorithms are being applied to "fight machines with machines".
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Handling Billions of Edges in a Graph Database
Michael Hackstein discusses graph databases, the current scalability problems and their solutions.
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Performance Mythbusting Panel
The panelists answer audience questions on real-world applied performance proofs across stacks including Java, .NET and Python.
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Control Flow Integrity Using Hardware Counters
J. Butler and C. Pierce present a system for early detection and prevention of unknown exploits. Their system uses Performance Monitoring Unit hardware to enforce coarse-grained Control Flow Integrity
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Scale @Reddit Triple Team Size w/o Losing Control
Nick Caldwell discusses his engineering team's approach to Agile development as they scaled from 40 to 120 engineers.
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