Over the past few weeks, Splunk has created a number of different tools to help bring data to the COVID-19 crisis. These tools, such as a public dashboard, an app on Github, and a Mobile Dashboard can be used to identify locations of outbreaks, find correlations and more.
The Kubernetes framework has become the leading orchestration platform. Originally developed by Google, Kubernetes is a "platform for automating deployment, scaling, and operations of application containers across clusters of hosts" * . The kubernetes platform is used in all Cloud platform provider vendors as a tool that allows orchestration, automation and provision of applications and specific needs computing clusters and services.
Earlier this year Python 2 entered End of Life — and Splunk has already released versions of Splunk Cloud and Splunk Enterprise that provide a Python 3 runtime. As the developer of an app that is published to Splunkbase, if your app contains Python code, you need to update it to work with Python 3 and Splunk Enterprise 8.0 by July 1, 2020 as the Splunk Enterprise and Splunk Cloud releases after that date will no longer support the Python 2 runtime.
Even with tough economic times, e-commerce is up 25% since the beginning of March. But, fraud has increased as well; according to Malwarebytes online credit card skimming has increased by 26% in March alone. In our April “Staff Picks for Splunk Security Reading” blog post, I referenced a story about an e-commerce site getting hacked with a “virtual card skimmer” (thanks Matthew Joseff for sharing this with me).
If you're reading this, you're probably wondering how to get data from various Microsoft Azure services into Splunk. With the growing list of Azure services and various data access methods, it can be a little cloudy (pun intended) on what data is available and how to get all that data into Splunk. In this blog post, I'm going go over how Microsoft makes Azure data available, how to access the data, and out-of-the-box Splunk Add-Ons that can consume this data. So let's dive right in.
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.
