Implementing Splunk Data Stream Processor (DSP) 1.2 Course Overview

The Implementing Splunk Data Stream Processor (DSP) 1.2 course is an extensive training program designed to teach learners how to deploy, manage, and utilize the Splunk DSP to its full potential. This course covers a range of topics from the basics of Splunk deployment options and DSP terminologies to advanced concepts such as streaming machine learning (ML) and working with third-party sources like Kafka.

By undertaking this course, learners will gain a thorough understanding of how to set up a DSP cluster, configure data sources and sinks, and build pipelines to process and analyze streaming data effectively. With practical lessons on monitoring the DSP environment, scaling DSP, and utilizing the DSP Plugins SDK, students will be equipped with the knowledge to troubleshoot and optimize their DSP implementations.

This course is ideal for Splunk administrators, data engineers, and IT professionals looking to enhance their skills in real-time data processing with Splunk's DSP. The hands-on experience and expert guidance provided in this course will enable participants to leverage the DSP for improved data operations, offering significant value to their organizations.