InfoQ Homepage application performance management Content on InfoQ
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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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Code Archaeology
David Mitchell shows how to create visualizations out of code: building a map for a large, legacy code base, creating visuals without drawing, and explaining a roadmap to bring code under control.
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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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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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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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Monitoring Serverless Architectures
Rafal Gancarz provides an overview of monitoring capabilities required for serverless apps -metering, logging, tracing, auditing, alerting-, and helpful AWS services.u
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Do You Really Know Your Response Times?
Daniel Rolls talks about the use of histogram metrics to monitor response times, explains how reservoir sampling can help, and shares good and bad practices when monitoring response times.
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Monitoring Bash Microservices at Scale
Paul Bellamy covers epic fails experienced moving to microservices using the RED method to monitor what matters, and production outages they solved with detailed telemetry.
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Speedup Your Java Apps with Hardware Counters
Sergey Kuksenko discusses how Performance Monitoring Unit works, what Hardware Counters are, which tools have friendship with Java and how to use HWC for speeding up our Java applications.
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Winston: Helping Netflix Engineers Sleep at Night
Sayli Karmarkar discusses Winston, a monitoring and remediation platform built for Netflix engineers.
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Implementing Microservices Tracing with Spring Cloud and Zipkin
Marcin Grzejszczak and Reshmi Krishna describe how to do distributed tracing with Spring Cloud Sleuth and Zipkin, demoing incorporating these technologies into an existing stock trading application.