Operations | Monitoring | ITSM | DevOps | Cloud

Data pipelines are the foundational support to any business analytics project. They are growing more critical than ever as companies are leaning on their insights to drive their business: 54% of enterprises said it was vital to their future business strategies. Data pipelines play a crucial role as they perform calculations and transformations used by analysts, data scientists, and business intelligence teams.

At.conf23, we announced the preview release of Splunk AI Assistant - Splunk's first offering powered by generative AI. This app offers an intuitive and easy-to-use chat experience to help you translate a natural language prompt into SPL query that you can execute or build on, all within a familiar Splunk interface. Splunk AI Assistant also explains what a given SPL query is doing in plain English with a summary as well as a detailed breakdown of the query.

Adaptive thresholding is a term used in computer science and — more specifically — across IT Service Intelligence (ITSI), for analyzing historical data to determine key performance indicators (KPIs) in your IT environment. Among other things, it’s used to govern KPI outliers in an effort to foster more meaningful and trusted performance monitoring alerts.

On the heels of an exciting GA in March and the April announcement of its regional expansion, we are excited to share the latest updates to Splunk Edge Processor that will make it even easier for customers to have more flexibility and control over just the data you want, nothing more nothing less.

Anomaly detection in metrics or time series data is the most used machine learning use case among Splunk Security and Observability customers. Customers are looking for easy-to-use ML-powered high-fidelity anomaly detection, so that they can be alerted at the first sign of a failure point or security incident.

Data has become an essential asset for businesses, driving innovation, improving decision-making, and shaping the future. But how does one effectively manage this valuable resource? This is where Data Lifecycle Management (DLM) comes in — a comprehensive approach to managing data throughout its lifecycle. This blog post will guide you through the ins and outs of DLM, its key stages, benefits, and the tools and technologies that enable successful implementation. Let's dive in!