Monitoring began by using software agents to capture data from infrastructure, operating systems, and applications. These agents would collect metrics and events from these systems to understand the health of the underlying system and the applications. This is what infrastructure monitoring is today.

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.

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.

In a previous blog post I discussed the complexity of securing Kubernetes environments, and some best practices. Unfortunately, even if we follow best practices in setting up and configuring our system, we can never eliminate all the vulnerabilities.

This tutorial will show you how can Coralogix provide analytics and insights for the Fastly logs you ship to Coralogix, both performance, and security.

Since various versions of lockdown around the world kicked in, we’ve all been forced to learn how to live as if we’ve just awoke from a deep stasis into a new reality in which everything on earth works differently. It was nearly that abrupt. And if there was ever evidence of how business adaptability is related to business success, it is now.

We are so excited to announce that LogDNA received the IBM Cloud Embed Excellence Award during the ​IBM Think​ conference on May 5, 2020. IBM Cloud’s Data & AI Excellence Awards recognize the stellar performance of IBM Business Partners who drive extraordinary client experiences and business growth. IBM Log Analysis with LogDNA and IBM Cloud Activity Tracker with LogDNA are built on IKS and are deeply integrated with IBM Cloud.