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.
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.
Itamar Syn-Hershko shows using various technologies -Storm, Node.js, Riemann, collectd, D3.js, ELK, PagerDuty, Slack - to power Forter’s service and keep it highly available and under control.
Tal Weiss shows how you can easily write your own JVM agent to capture accurate performance data for virtually any type of application from Java microservices to reactive actor systems in Scala.
Atlassian Hybrid Cloud/On-Premise Software Delivery and the Journey to 300,000 Applications in the Cloud
George Barnett discusses techniques for building the supporting infrastructure for a hybrid model, and how to make monitoring, deployment tools, and shared services work effectively.
Brittany Young discusses a framework for identifying the performance metrics that matter most to users, looking at improving the development life cycle by knowing common mobile performance blind spots
In this solutions track talk, sponsored by AppDynamics, Tom Levey discusses how to monitor UX, identify bottlenecks, and measure the revenue impact by turning on the lights inside a mobile app.
Ashley Puls methods and tools that can be used to uncover and resolve performance problems arising in Java web applications that use the Spring Framework.
Matt West explains how to use technologies like CloudStack, Beanstalk, Gearman, mod_gearman, Nagios, nagconf and other tools to monitor large web applications at scale deployed in the zCloud.
Ariel Tseitlin discusses Netflix' failure-based suite of tools, collectively called the Simian Army, used to improve resiliency and maintain the cloud environment.
Roy Rapoport discusses how Netflix uses metrics to monitor and manage their operating environment along with some notes about their event management system.
Bhaven Avalani and Yuri Finklestein discuss 4 aspects encountered at eBay when dealing with monitoring data: reduction of data entropy, robust data distribution, metric extraction, efficient storage.