The importance of the security of the Department of Defense’s (DoD’s) networks is no secret (well, of course a lot of it is secret!). This is evidenced by the Department’s IT/cybersecurity budget request that annually tops $40 billion dollars. Last year’s IT and Cyberspace Activities Budget Overview perhaps said it best.
Maybe you have used the previous blog post about generating smarter episodes in ITSI using graph analytics and want to know what else you can apply ML to. Maybe you’re still swamped in alerts even after using the awesome content pack for monitoring and alerting. Maybe your boss has told you to go read up on AIOps…. Whatever the reason for finding yourself here this blog is intended to help you identify the “unknown unknowns” in your alert storms.
Like champagne and party hats, Splunk and Microsoft just go together. Here at Splunk, one of our New Year’s resolutions is to continue to empower our customers with data — in this case, Microsoft data. From cloud, to security, to troubleshooting, we’re back with the latest round of new integrations designed to help you do more with Splunk and Microsoft.
In my previous Link Analysis blogs, "Visual Link Analysis with Splunk: Part 1 - Data Reduction" and "Visual Link Analysis with Splunk: Part 2 - The Visual Part," I used techniques that work well when we have a controlled data set. However, as we know, real data can be messy. When analyzing links in fraud data, the data can be very noisy. Let’s say we want to use IP addresses for link analysis in the Splunk platform. It is not unusual for two people to share an IP address.
In this blog I’m exploring the issues that will guide senior leaders in Government this year as they continue their transformative journey towards digitalisation, remote work, cloud migration and a data-driven approach to public services.
Root cause analysis can be a difficult challenge when you are troubleshooting complex IT systems. In this blog, we are going to take you through how you can perform root cause analysis on your IT Service Intelligence (ITSI) episodes using machine learning, or more specifically causal inference. The approach shown here is included in the Smart ITSI Insights app for Splunk, with this blog largely detailing how to use the ITSI Episode Analysis dashboard.
Enhancing the customer experience and boosting revenue with the power of analytics are key concepts for telecom operators in today’s ultra-competitive business environment. Many telecoms are going through transformation of their system architectures and stacks to change how they operate and manage their day to day operations as well as their strategies and planning for what comes next.
In this blog we are going to describe how you can create a notable event policy in IT Service Intelligence (ITSI) that is able to group your events using labels generated by unsupervised machine learning in the Smart ITSI Insights App for Splunk – and don’t worry you don’t have to be a data scientist to read this blog!
Some of you may have seen recently that we are trying to commoditize machine learning through our MLTK smart workflows. Here I’d like to outline another example of an MLTK smart workflow, designed to help improve the usability of the predictive capabilities in ITSI.
Back in October, we announced the Splunk OpenTelemetry Collector Distribution, which offered the industry’s first production-ready support for OpenTelemetry. This distribution is the recommended way that customers of Splunk’s award-winning observability products capture metrics and traces.
