Kaspersky Machine Learning for Anomaly Detection

Scenario: assessing the main metrics of Kaspersky MLAD

Before starting to work with the logging subsystem, it is recommended to read the Grafana User Guide.

When connecting to the logging subsystem for the first time, you must change the default password.

This subsection provides a sequence of actions that must be performed to assess the health and general state of Kaspersky MLAD.

The scenario for assessing the health and general state of Kaspersky MLAD consists of the following steps:

1. Navigating to the logging subsystem

   Go to the logging system by clicking the button. This opens the Grafana interface in which you need to enter the name and password of the Kaspersky MLAD user.

   Available only to the system administrators and users with the Manage application logs permission.

2. Analyzing the main metrics of Kaspersky MLAD

   In the Summary docker metrics section, analyze the graphs of the main Kaspersky MLAD metrics for the selected period.

   The following metrics are displayed for each container of Kaspersky MLAD services:

   • CPU usage – history of central processor workload caused by the container. This is measured as a percentage.
   • RAM usage – history of the container's RAM usage. This is measured in bytes.
   • Disk usage Read/Write – history of the container's load on the disk subsystem (read/write operations). This is measured in bytes.
   • Network usage – history of the container's use of network resources. This is measured in bytes per second.