Monday, November 11, 2013

Application Performance Management for distributed real-time data processing


As one of the most important requirements is real-time user interaction, Application Performance Management at scale is encoded into our engineering DNA. It starts with architecture, and continues in solution design to the development ,test and production environment.

The Kweo distributed real-time data processing stack consists of the following major components:

  • The stack Netty as event-driven network application framework 
  • Apache Kafka as a fault-tolerant, high throughput distributed messaging system 
  • Storm / Trident for distributed and fault-tolerant real-time computation 
  • Apache Cassandra as a fault-tolerant, distributed column oriented database

The challenge

We needed an APM solution which works in our development, test and production environment. The solution needed to be able to provide:

  • Infrastructure system monitoring and alerting 
  • Application monitoring and alerting 
  • Application Performance Management 
  • Shows response time, CPU cost, API breakdown, suspensions (garbage collection)and IO time for each trace 
  • Real-User monitoring 
  • Historical metric storage up to 365 days 
  • Runs in our environment and not as an external SaaS model 
  • Can be used for deep distributed transaction tracing and as a distributed profiler 
  • Always on, every transaction can be traced 
  • Can trace through our stack above end-to-end 
  • Works well in Amazon EC2 
  • Supports tracing through Apache, PHP, Java, zeromq and custom protocols

Read more here

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