Building apps with less code and more abstractions, unit and integration test frameworks/harnesses, and continuous integration and delivery pipelines with Jenkins are all best practices and proven patterns in the enterprise for traditional apps. But they are difficult to follow with distributed systems like streaming analytics apps.
In this talk we will introduce some powerful new open source tooling based on Hortonworks Streaming Analytics Manager (SAM) that allows enterprises to easily implement these best practices. In 35 minutes, we will walk through the building of a complex streaming analytics app using a drag-and-drop approach (similar to Apache NiFi) that does the following:
• Joining streams
• Aggregations over windows (time or count based)
• Complex event processing
• Real-time streaming enrichment
• Model scoring on the stream
Once the app is built, we will create automated unit and integration tests of the streaming application, build continuous integration and delivery pipelines with Jenkins, and introduce powerful new monitoring, management, and dev-ops troubleshooting tools.