Cumulocity IoT Streaming Analytics provides streaming analytics and intelligent automated actions on fast-moving big data to the Cumulocity IoT platform.
- Analytics Builder has a “Machine Learning” analytics block that can be used to execute Cumulocity IoT Machine Learning models in real-time with streaming data as part of simple or complex Analytics Builder models.
- Analytics Builder has a “Counter” analytics block for tracking total inputs and repeated inputs.
- Usability improvements to the Cumulocity IoT transport to help EPL developers 1) identify tenant options, 2) identify details and roles either of the user or the microservice service user, 3) split Measurement events into individual fragments and series for better performance when filtering on incoming events and 4) receive a response when creating or updating predefined types (Alarm, Operation, Event, Measurement, MeasurementFragment and ManagedObject).
Release Notes are available at:
https://cumulocity.com/guides/apama/apama-release-notes/
Apama-specific release notes are available at: http://techcommunity.softwareag.com/ecosystem/communities/public/apama/.links/documentation-apama