Wednesday 16th September, 2015
12:45pm to 2:15pm
Data / Integration Track
Do you live in a world where StackTraces aren’t quite enough? There is no easy way for you to predict how a certain set of services might be called or what their usage patterns are? Does everything work in DIT/SIT/UAT/PELT until you hit production and strange things start to happen due to distribution of services? Solution: Use RabbitMQ (AMQP protocol) and spring proxies/interceptors to enable an out-of-band instrumentation to trace requests and gain deep knowledge about how certain requests perform in a distributed system. In 2014, as part of infrastructure wide changes, I introduced calltracing(tm) as a way to correlate requests from a single user across E*Trade's heterogeneous systems. This ""trace"" is then consumed by various big-data analytic tools to produce aggregated reports. Zipkin(tm) is a collector, digester and a visualization front-end for the aggregated data. in other words, it’s a distributed tracing system that can show timing data for services that are on various nodes. Zipkin manages both collection and lookup of data through a collector and a query service. In this session, i will discuss specifically how E*Trade’s disparate services are stitched together using RabbitMQ(AMQP protocol) and Spring Proxies to form the enablement tier to provide data to Zipkin.
Sign in to add slides, notes or videos to this session