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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Introducing Splunk OpenTelemetry Java Lambda Wrapper
Introducing Splunk OpenTelemetry Java Lambda Wrapper. In this blog, we’ll show you how to deploy the wrapper with a Lambda layer for frictionless instrumentation
Advanced Link Analysis: Part 1 - Solving the Challenge of Information Density
Leverage Sigbay's link analysis visualization to solve the challenge of information density.
Threat Hunting With ML: Another Reason to SMLE
This blog is the first in a mini-series of blogs where we aim to explore and share various aspects of our security team’s mindset and learnings. In this post, we will introduce you to how our own security and threat research team develops the latest security detections using ML.
Splunker Stories: Manan Grover
In the latest edition of our "Splunker Stories" series, we meet one of our Sales Engineers, Manan Grover. We sat down with Manan to learn more about her conversion from a Splunktern to a full time employee, her perspectives on what “team” means, and how she is working with our customers to elevate discussions and accelerate progress.
The OpenTelemetry Tracing Specification Reaches 1.0.0!
OpenTelemetry tracing specifications reached 1.0.0; which means tracing APIs and SDKs GA is imminent! Read more about this exciting announcement in this blog.
Creating a Fraud Risk Scoring Model Leveraging Data Pipelines and Machine Learning with Splunk
One of the new necessities we came across several times was that the clients were willing to get a sport bets fraud risk scoring model to be able to quickly detect fraud. For that purpose, I designed a data pipeline to create a sport bets fraud risk scoring model based on anomaly detection algorithms built with Probability Density Function powered by Splunk’s Machine Learning Toolkit.