Kushagra Sharma's Blog Posts
Kushagra Sharma is a Product Manager at Cisco working on AIOps products that help teams operate complex systems with intelligence and scale. He focuses on translating customer problems into practical, data-driven solutions at the intersection of AI, reliability, and software platforms. Passionate about clear thinking and strong product craft, Kushagra writes to share insights on technology, product strategy, and building systems that actually work in the real world.
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Making Smarter Predictions in ITSI
As we are trying to commoditize machine learning through our MLTK smart workflows, this article outlines another example of an MLTK smart workflow, designed to help improve the usability of the predictive capabilities in ITSI.
Next Level Automation: What’s New with Splunk Phantom
With the release of Splunk Phantom 4.10.1, we now allow you to configure the number of playbook runners using Python 2 and Python 3. Learn more right here.
Visual Link Analysis with Splunk: Part 2 - The Visual Part
Using Splunk for link analysis - part 2 covering visualizations of linked data.
Observability with CI/CD in a Developer World
You need to monitor your apps and deploys equally. The Splunk Observability portfolio is the perfect complement to a CI/CD approach, from a developer laptop to an integration test environment.
Detecting Credit Card Fraud Using SMLE
In this blog post, we’ll explore an ML-powered solution using the Splunk Machine Learning Environment to detect fraudulent credit card transactions in real time. Using out-of-the-box Splunk capabilities, we’ll walk you through how to ingest and transform log data, train a predictive model using open source algorithms, and predict fraud in real-time against transaction events.
Cybersecurity Today: Alice in Wonderland Meets the Matrix & Total Recall
The scale of cyber attacks and the complexity of networks exacerbate the situation. Operators face three significant challenges: an IT security ecosystem that is fragmented and in flux, users that are both human and machine, and multiple threats with varying levels of severity and sophistication.