Adam Leventhal introduces DTrace, using a case study o solve a performance problem.
Michael Hausenblas introduces containers, microservices and dealing with security, monitoring and troubleshooting using Apache Mesos/Marathon and Kubernetes.
Luke Kosewski describes Flow, how it adds value to a microservice architecture, what preconditions must be met for such a recovery mechanism to succeed, and tells the story of a 2015 Q4 outage.
Alex Rasmussen examines some lessons learned while building record-setting sorting systems at UC San Diego.
Matt Warren takes a look at how to measure, what to measure and how get the best performance from .NET code, considering examples from the Roslyn codebase and StackOverflow (the product).
Alan Ngai and Premal Shah discuss best practices on monitoring distributed real-time data processing frameworks and how DevOps can gain control and visibility over these data pipelines.
Jamshid Mahdavi explains how WhatsApp has developed their server components, the deployment processes, and how they monitor, alert, and repair the inevitable failures in a billion-users service.
Luca Marturana covers the current state of the art for container monitoring and visibility, including real use cases with pros/cons of each and focuses on advanced container visibility techniques.
Runar Bjarnason presents how to get started with the Scalaz-Stream library, shows some examples, and how we can combine functional streams into large distributed systems.
John Oliver takes a look at both G1 and Shenandoah, explaining how they work, what are their limitations, providing tuning advice. He also looks at recent and future changes to garbage collection.
Monica Beckwith talks about G1 pause (young and mixed) composition, G1's remembered sets and collection set and G1's concurrent marking algorithm, providing performance tuning advice.
Chris Newland discusses performance-boosting techniques used by the JVM’s JIT and introduces JITWatch, a tool helping to get the best JVM performance for a code.
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