For example, log events generated by an influx of traffic can easily overwhelm a log streaming service and exhaust its underlying resources. Sudden spikes in a host’s CPU or network traffic can also create a cascading effect for downstream logging services. This approach, however, can consume a significant amount of your network’s bandwidth and overwhelm the destination server-especially in larger environments. Teams that leverage log management solutions like Datadog to centralize, store, and analyze their logs may start by configuring applications to stream them directly to an endpoint. When operating at this scale, it is critical to have robust processes in place that enable you to efficiently collect logs from all of your system components. Modern environments-including those of many Datadog customers-generate large volumes of log data from multiple sources, such as containers, servers, databases, firewalls, and physical network devices. But first, we’ll further explore the importance of logging to files, and how log rotation solves some of the challenges that often accompany this recommended practice. In this guide, we’ll walk you through how to customize the logrotate utility to fit your logging needs. Logrotate is a Linux utility designed to simplify log management and maintenance within these types of environments through a process known as log rotation. Large-scale production environments emit enormous quantities of logs, which can make them more challenging to manage and introduces the risk of losing important data if underlying resources run out of space. Logs are records of system events and activities that provide valuable information used to support a wide range of administrative tasks-from analyzing application performance and debugging system errors to investigating security and compliance issues.
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