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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Learn SPL Command Types: Efficient Search Execution Order and How to Investigate Them
When performing searches, Splunk uses its own language, SPL (Search Processing Language). In this article, we will explain each type of SPL and show you the efficient order in which to run searches and how to use the Search Job Inspector, an investigative tool.
Great Scott: Exploring the Past, Present, and Future of Generative AI
What’s next for AI in 2025? Discover key predictions on ROI-driven investments, domain-specific models, and how AI will reshape businesses and technology.
Business Intelligence (BI): What It Means for Your Organization
Learn how BI transforms raw data into actionable insights to drive decisions, boost efficiency, and enhance ROI.
Data Science vs. Data Analytics: Key Differences
Don’t be confused! Data science and data analytics are different concepts. Learn all about it here, so you’ll know exactly how they can work together.
Models for Time Series Forecasting
Understand time series forecasting — a way to or predict behaviors based on historical, timestamped data — with anomaly detection to prevent IT problems.
Scaling Anomaly Detection with MLTK 5.5
Who doesn’t love a bit of anomaly detection with Splunk? As someone who has spent far too long talking about cyclical statistical forecasts and anomalies, you’ll be relieved that this is a topic that we don’t get tired of here at Splunk! In this blog post we will be taking you through some of the recent changes to the Machine Learning Toolkit, where we have released a more scalable version of our users most favorite algorithm.