Operations | Monitoring | ITSM | DevOps | Cloud

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.

When I was still writing code, our Splunk license only had enough capacity to monitor our Production environment. So we stood up a self-managed Elastic cluster for our lower environments. This quickly became unmanageable as we started logging more and adding additional environments. As I spend more time in the field, I see this pattern repeated over and over.

As an SRE, have you ever had a situation where you were working on an application that was written with non-standard frameworks, or you wanted to get some interesting business data from an application (number of orders processed for example) but you didn’t have access to the source code?

Observability gets more challenging yearly in the rapidly evolving world of distributed computing and cloud-native applications. Organizations today are tasked with ensuring that their critical business applications, revenue-generating applications, and supporting infrastructure operate with reliability and security. The stakes are high; any lapse can lead to user churn, revenue loss, and decreased productivity.

ELK Stack, also known as the Elastic Stack is a powerful and versatile open-source toolset that has revolutionized the way businesses manage and analyze their data. ELK Stack seamlessly integrates these three robust components to offer a comprehensive solution for searching, analyzing, and visualizing large volumes of data in real-time. So, buckle up, for a comprehensive overview of the ELK stack and its components, which will be a great starting point for beginners.

In the realm of Linux system administration, monitoring log files is essential for maintaining a healthy and secure environment. Linux distributions generate a multitude of log files that capture crucial information about system events, errors, and user activities. These log files act as a silent witness, providing valuable insights into the inner workings of a Linux system.