Many of our customers frequently ask us how they can calculate the ROI of their observability platforms. It’s a tough question, and one that comes up because company decision-makers often feel like they may be overpaying for observability when things are running smoothly – especially when it comes to their applications.

Every action, transaction, and interaction in an application generates some sort of data. ThisAnd this data holds a wealth of information that, when collected and analyzed over a period of time, provides a comprehensive view of application behavior and performance. Logging is the most widely used technique for collecting data on application states, transactions, errors, and code flow tracking.

Almost everyone acknowledges that log monitoring is essential for maintaining the reliability, security, and performance of modern applications. However, the complexities increase as organizations adopt diverse architectures to effectively manage the various log data challenges they encounter. In our previous blog post, we discussed the significance of log monitoring alongside a few popular log monitoring tools available in the market today.

In its simplest terms, log monitoring is the process of systematically collecting, storing, analyzing, and alerting on log data generated by various systems, applications, and devices within a DevOps environment. Logs are essentially records of events, transactions, and activities that occur within these systems. They can contain valuable information about system errors, performance metrics, user activities, and security events.