InfoQ Homepage Performance Content on InfoQ
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High Performance Batch Processing
Mahmoud Ben Hassine and Michael Minella walk through performance tuning and scaling Spring Batch applications via the enhancements of 4.1.
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Enabling .NET Apps with Monitoring and Management Using Steeltoe
Dave Tillman discusses using the Steeltoe Management frameworks to enable a .NET application with performance monitoring, management diagnostic endpoints, and distributed tracing on PCF.
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Restoring Confidence in Microservices: Tracing That's More Than Traces
Ben Sigelman talks about rethinking distributed tracing in terms of the most vital organizational problems that microservices introduced.
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Jupyter Notebooks: Interactive Visualization Approaches
Chakri Cherukuri talks about how to understand and visualize machine learning models using interactive widgets and introduces the widget libraries.
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How Fast is Spring?
Dave Syer attempts to show, with the help of benchmarks, that the Spring Framework is not as slow as some say, and why some apps might have a longer start time.
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Heavyweights: Tipping the Scales with Very Large Foundations
Jim Basler provides an update on the Very Large Cloud Foundry Environment (VLCFE) user group and capabilities for tackling the challenges of hosting 10s of thousands of applications.
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Yes, I Test in Production (And So Do You)
Charity Majors talks about testing in production and the tools and principles of canarying software and gaining confidence in a build, also instrumentation and observability .
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Achieving Hyper-Productivity through the Use of Microservices and PCF
Thomas Seibert, Gregor Zurowski describe how their delivery performance has increased by using microservices and PCF and how their ecosystem allows for scaling to a multitude of teams.
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Enterprise Systems Built with Microservices are Designed to Expect Failures, But Then What? How Do We Handle Failures?
Dalia Borker explores the use of caching frameworks to improve resilience and performance in enterprise microservices systems with Redis, Pivotal Cloud Cache, and Hazelcast.
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Radical Realizations with Tracing & Metric Visualizations
David Crawford, Sean Keery share insights about combining tracing data & metrics with animated traffic dashboards to convey a more comprehensive understanding of the variables in play.
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Massively Scaling MySQL Using Vitess
Sugu Sougoumarane gives an overview of the salient features of Vitess, and at the end, covers some advanced features with a demo.
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Monitoring AI with AI
Iskandar Sitdikov discusses a solution, tooling and architecture that allows an ML engineer to be involved in delivery phase and take ownership over deployment and monitoring of ML pipelines.
