At its .conf23 conference, Splunk today revealed it added a slew of capabilities to its portfolio of operational analytics tools, including an assistant that leverages generative artificial intelligence (AI) capabilities that use large language models (LLMs) the company developed to enable IT teams to use natural language to invoke the Splunk Processing Language (SPL).
In addition, Splunk is also previewing OpenTelemetry Collector, an add-on that uses open source agent software being developed by the Cloud Native Computing Foundation (CNCF) to capture metrics and traces. It is designed to enable IT teams to use OpenTelemetry alongside existing agent software that Splunk uses to capture metrics.
Tom Casey, senior vice president for products and technology at Splunk, said the domain-specific LLMs that the company created enable Splunk Assistant to write or explain customized SPL queries in a way that augments rather than replaces the need for IT professionals. Splunk Assistant is designed to surface recommendations to optimize IT environments to reduce toil rather than automate entire processes, he noted.
Splunk is adding other tools infused with machine learning algorithms to its portfolio. These include the Splunk App for Anomaly Detection and an Outlier Exclusion for Adaptive Thresholding to detect and omit abnormal data points that has been added to version 4.17 of the Splunk IT Service Intelligence platform.
In addition, Splunk is previewing an ML-Assisted Thresholding tool for Splunk IT Service that uses historical data and patterns to create dynamic thresholds with a single click.
The company is making available a 5.4 update to the Splunk Machine Learning Toolkit (MLTK) 5.4 and a Splunk App for Data Science and Deep Learning (DSDL) 5.1 toolkit that provides access to additional data science tools that can extend MLTK to enable organizations to build their own custom LLMs and AI assistants.
Finally, Splunk added Unified Identity to make it simpler to access Splunk Cloud Platform and Splunk Observability Cloud along with an update to Splunk Cloud Platform and Splunk Enterprise that make it simpler to ingest, route, search and export data.
It’s still early days as far as the application of generative AI is concerned, but it’s already clear that the way IT is managed is about to be transformed. Coupled with tools such as OpenTelemetry that make it less expensive to collect massive amounts of data, the opportunity to train LLMs that streamline a wide range of processes is immense. Those capabilities won’t replace the need for humans to manage those processes, but they will most certainly cause staff realignments as many manual tasks become increasingly automated.
In fact, it’s hard to imagine an IT team that would not want to take advantage of AI capabilities to simplify the management of complex IT environments that now function at a level of scale that few IT professionals can successfully manage on their own. One way or another, AI is going to be broadly applied to IT workflows. The only thing left to be seen now is the ultimate impact.
