Analyzing Response Time Distributions for Microservices
10:20 - 11:10
The end to end response time of a network of microservices tends to have a wide distribution with a long tail at the 99th percentile, even if the mean is short. By collecting the response time distributions and throughput for request traces we can see how the individual microservices respond, but to combine these distributions and find which microservice is contributing the most to the 99th percentile requires application of montecarlo simulation. This talk will explain how this technique works and investigate tools ranging from Excel plugins to R packages that can implement montecarlo models.
Adrian Cockcroft has had a long career working at the leading edge of technology. He’s always been fascinated by what comes next, and he writes and speaks extensively on a range of subjects. At Battery, he advises the firm and its portfolio companies about technology issues and also assists with deal sourcing and due diligence.
Before joining Battery, Adrian helped lead Netflix’s migration to a large scale, highly available public-cloud architecture and the open sourcing of the cloud-native NetflixOSS platform. Prior to that at Netflix he managed a team working on personalization algorithms and service-oriented refactoring.
Adrian was a founding member of eBay Research Labs, developing advanced mobile applications and even building his own homebrew phone, years before iPhone and Android launched. As a distinguished engineer at Sun Microsystems he wrote the best-selling “Sun Performance and Tuning” book and was chief architect for High Performance Technical Computing.
He graduated from The City University, London with a Bsc in Applied Physics and Electronics, and was named one of the top leaders in Cloud Computing in 2011 and 2012 by SearchCloudComputing magazine. He can usually be found on Twitter @adrianco.