Announcing the General Availability of Splunk Real User Monitoring (RUM)
Splunk Real User Monitoring (RUM), now generally available, leverages open source and OpenTelemetry standardization to help SREs and on-call engineers troubleshoot customer-facing issues faster, and optimize end-user experience.
Conquer Complexity at Any Scale With the New Splunk Observability Cloud
Announcing the new Splunk Observability Cloud, bringing together the world’s best-in-class solutions for infrastructure monitoring, application performance management, digital experience monitoring, synthetic monitoring, log investigation and incident response.
Observability: It’s Not What You Think
Observability is not just metrics, traces, and logs. It is a mindset that lets you answer any question about your business through collection and analysis of data.
Cybersecurity’s Moneyball Transformation
What do baseball and cybersecurity have in common? Nothing, at first glance. But, take a deeper look and you can see the glaring similarities. That's because cybersecurity is going through its Moneyball transformation right now. Read this blog post to learn more.
TruSTAR Intel Workflows Series: Shifting from App-Centric to Data-Centric Security Operations
TruSTAR recently introduced API 2.O featuring TruSTAR Intel Workflows. This blog series will explain our motivations for building this feature, how it works, and how users can better inform security operations.
Clop Ransomware Detection: Threat Research Release, April 2021
Discover how the Splunk Threat Research Team focused their research efforts on Clop Ransomware detections to help organizations detect abnormal behavior faster before it becomes detrimental.
Meet the Splunktern: Matthew Follegot
In this installment of our 'Meet the Splunktern' series, we’re introducing Matthew Follegot, our Back-End Software Engineer Co-Op on the Security Analytics (UEBA Cloud) team. Read on to learn more about Matthew's virtual Splunktern experience!
Deep Learning Toolkit 3.5 - Part 2: Change Point Detection, Matrix Profiles and LSTM-based Predictions
In the first part of this 2-part-series we talked about recent additions to version 3.5 of the Deep Learning Toolkit for Splunk (DLTK). Here in part 2 we want to explain a few new algorithmic approaches available for time series analysis. These can be especially interesting for anomaly detection and time series prediction.
Using Maths to Fight Financial Crime
Financial crime has become a red-hot topic over the last 12 months, as fraudsters have sought to exploit the monitoring gaps between people, process and technology across an ever-widening attack surface – driven by the growth in usage of remote (digital) channels. But if you could fight financial crime with maths? Splunker Charles dives deeper into the methodology.
