Understanding Log Analytics at Scale, 2nd Edition

Chapter 2. Log Analytics Use Cases

Technologists have been analyzing machine logs for decades, from the earliest days of tuning or troubleshooting their environments. Over time, the industry has found ways to increasingly automate that analysis, leading to the emergence of log analytics as we know it today. Now more than ever, log analytics can help businesses run more efficiently, reduce risk, and ensure continuity of operations.

The use cases described in this section illustrate some examples of how log analytics has taken on new importance in the past several years, demonstrating how it can deliver unprecedented value to organizations of all types and sizes. Factors that have contributed to that growing importance include the following:

• Machine data provides greater opportunities for log analytics as well as challenges. The scale of data analysis will grow further as we continue to drive intelligence into the world around us. A single self-driving car is estimated to generate multiple terabytes of data each day, while a smart factory might generate a petabyte per day.¹

• Greater variety among types of endpoints has already reached unprecedented levels as the IT environment has become more complex. As the pace of change accelerates and the Internet of Things (IoT) adds billions of new devices online, the insights to be gained by bringing together multiple data sources will continue to increase.

• Technology evolution, making log analytics feasible at greater scale than before. ...