Splunk introduces new updates for its cloud platform

Splunk announced a number of updates to its Splunk Cloud platform. The most important updates include improvements for real-time processing of data streams. This mainly affects the monitoring and management of data and the improvement of machine learning processes.

In the update, the provider of big data solutions provides enhancements to its Data-To-Everything platform to improve the complexity of moving large amounts of data from a single data center to multiple data centers in cloud environments.

For this purpose, it introduces version 4.5 of its Splunk IT Service Intelligence tool. The tool provides a centralised environment for monitoring and investigating data. In addition, the tool now offers more capacity for service and event management for large-scale rollouts.

Splunk Data Stream Processor (DSP) v1.1

Splunk also introduces an enhanced version 1.1 of its Splunk Data Stream Processor (DSP) for real-time processing of data streams. In the update, more streaming capacity has been added, and there is an option to collect data at a single unified location. Furthermore, Splunk DSP 1.1 allows companies to hide sensitive or customer data in the data stream. Subsequently, with the necessary compliance guarantees, they can move this data to different locations within their organisation.

Update for machine learning

The cloud-based data specialist also releases updates for machine learning. The Machine Learning Toolkit (MLT) is now equipped with a simplified customisable interface. This is done to make the toolkit more suitable for a wider audience.

In addition, version 5.2 of the toolkit offers improved visualisation capabilities and a new group of Smart Assistants. According to Splunk, the latter should enable step-by-step guided workflows. Customers can use publicly available machine learning algorithms for their data and run models for tasks such as data clustering, predictions or the discovery of opportunities. Customers who put a lot of effort into operational and marketing data and are looking at associations, in particular, can benefit from this.