The Splunk Security Research Team has been working on new improvements and additions to the Splunk Attack Range, a tool that allows security researchers and analysts to quickly deploy environments locally and in the cloud in order to replicate attacks based on attack simulation engines. This deployment attempts to replicate environments at scale, including Windows, workstation/server, domain controller, Kali Linux, Splunk server and Splunk Phantom server.

In sync with the upcoming release of Splunk’s Machine Learning Toolkit 5.2, we have launched a new release of the Deep Learning Toolkit for Splunk (DLTK) along with a brand new “golden” container image. This includes a few new and exciting algorithm examples which I will cover in part 2 of this blog post series.

In part 1 of this release blog series we introduced the latest version of the Deep Learning Toolkit 3.1 which enables you to connect to Kubernetes and OpenShift. On top of that a brand new “golden image” is available on docker hub to support even more interesting algorithms from the world of machine learning and deep learning! Over the past few months, our customers’ data scientists have asked for various new algorithms and use cases they wanted to tackle with DLTK.

You may already be using Splunk to ingest data and generate alerts and dashboards so you can take quick action on problems, but did you know you can quickly start a VictorOps trial and in three easy steps, have great Splunk alerts escalated to the right teams and people with a mobile app notification, SMS message or a live phone call?

Contact or Call... Center or Centre... Call them what you will, but, wow, we’re calling them and we’re counting on them now more than ever! The dramatic shift to remote everything has flooded Contact Centers with more calls, while also requiring providers to adopt remote, distributed architectures.

For those of you with some gray hair working in the manufacturing business, remember when order intake plunged suddenly by more than 40%? Remember when CFO and Controllers ruled the company, driving painful cost-cutting programs to counter double-digit business losses? It was the time of the Economic and Financial Crisis 2007/08, which forced manufacturing organizations to stare in the abyss.

Splunk’s recent "What Is Your Data Really Worth?" report1 highlighted the importance of data and analytics to financial services companies. In our global survey of business and IT decision makers2, 89% of respondents from financial services companies felt that the intelligent use of data and analytics is becoming the only source of differentiation in the industry.

I recently participated in a webinar exploring the question "What is Your Data Really Worth?" in the context of financial services. Enterprise Strategy Group (ESG), in partnership with Splunk, performed a global research survey of 1,350 business and IT decision-makers across leading economies and industries. Over the course of the webinar we discussed their findings with my participation focused on IT Operations.

You don’t need us to tell you that fraud and financial crime is on the rise. A quick google search will give you endless stats to support this claim. Fraud losses are increasing as a percentage of revenue, and that direct impact on the bottom line isan area of laser focus for senior execs.

I recently chatted with Adam DeMattia from leading research and analyst firm ESG in a webinar about data use maturity in financial services. According to the research1, 21% of financial services firms identify as data innovators (compared to 11% of global respondents) — those who make smarter use of data as a matter of strategic importance.