DataStax’s new LunaML to support Kaskada deployment

DataStax’s new LunaML to support Kaskada deployment

Kaskada, acquired by DataStax in January, offers an open-source based unified events processing engine aimed at helping enterprises build real-time machine learning applications.

Database-as-a-service (DBaaS) provider DataStax is releasing a new support service for its open-source based unified events processing engine, Kaskada, that is aimed at helping enterprises build real-time machine learning applications.

Dubbed LunaML, the new service will provide customers with “mission-critical support and offer options for incident response time as low as 15 minutes,” the company said, adding that enterprises will also have the ability to escalate issues to the core Kaskada engineering team for further review and troubleshooting.

The company is offering two packages for raising tickets by the name of LunaML Standard and LunaML Premium, which in turn promises a 4-hour and 1-hour response time respectively, the company said in a blog posted on Thursday.

Under the standard plan, enterprises can raise 18 tickets annually. The Premium plan offers the option to raise 52 tickets in one year. Plan pricing was not immediately available.

DataStax acquired Kaskada in January for an undisclosed amount with the intent of adding Kaskada’s abilities into its offerings, such as its serverlessNoSQL database-as-a-service AstraDB and Astra Streaming.

DataStax’s acquisition of Kaskada was based on expected demand for machine learning applications.

The company believes that Kaskada’s capabilities can solve challenges of cost and scaling around machine learning applications, as the technology is designed to process large amounts of event data that is either streamed or stored in databases, and its time-based capabilities can be used to create and update features for machine learning models based on sequences of events, or over time.

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