Use the following menu options to navigate the SL1 user interface:
- To view a pop-out list of menu options, click the menu icon (
). - To view a page containing all of the menu options, click the Advanced menu icon (
).
Understanding Behavioral Correlation in Business Services
SL1 offers an elevated enterprise visibility experience that allows you to monitor and view the health of your services, from an individual device to a larger Business Service view. SL1 has the ability to show a service's behavior and its interactions; in other words, it enables you to analyze a service's Behavioral Correlation. This Behavioral Correlation analysis enables you to implement changes with the hopes of reducing complexity and noise.
To determine a business service's health, you might first look at the Business Service Overview dashboard, where the health of a Business Services's components is displayed:
Using the color-coded health widgets in SL1, you can determine which areas of your enterprise are considered healthy and which are not.
Analyzing a Service's Behavioral Correlation
You can determine the Behavioral Correlation for a Business Service by further analyzing the health data of specific areas.
To analyze the health of a specific area:
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On the Business Service Overview dashboard, click the widget of the Business Service area that you want to further analyze. The tab of the Service Investigator displays.
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Identify problem areas by reviewing the relevant widgets on the Overview page. The widgets on this page allow you to sift through any problem sources and pinpoint their various severities. See Business Services Investigator for more information on widgets and their functionality.
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By clicking into a widget's source data, you can view the Health, Availability, Risk, Events, Changes, and Anomaly data for a specific area. The machine learning capability of SL1 lets you view and recognize patterns for yourservice's problem source areas.
The majority of service-based issues are displayed in the or tabs of the Service Investigator page. SL1's machine learning capability focuses on the services' raw data, as opposed to outdated or static data systems, to capture anomalous patterns.
You can begin using Behavioral Correlation analysis to identify and diagnose service issues by focusing on two key areas:
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The Anomalies widget's time graph. You can hover over any part of the time graph with your mouse to see the exact historical values for each polling cycle. Also, you can zoom in on a shorter time frame by clicking and dragging your mouse over the part of the interactive chart for a time frame, and you can return to the original time span by clicking the button. The historical values for each cycle can offer major insight into problem areas within your enterprise.
To learn more about how to use the graph to identify detected anomalies, see the Anomalies Widget section.
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The Event Drawer panel. On the widget, you can click on a specific event to open the Event Drawer panel, which contains widgets that allow you to view and perform SL1's recommended actions and remediations.
For events that are aligned to devices, click the down-arrow icon (
) next to the event to open the Event Drawer panel, which displays the following panes:-
Vitals. A widget displaying the event health for the past 24 hours of CPU and its memory usage for the device related to the event.
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Tools. A set of network diagnostic tools or user-initiated actions that you can run on the device associated with the problem event. Click the search bar to search for a tool or action to run, or click one of the default tools or actions that are available based on the device type and your user permissions.
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Logs. You can review a list of the log entries from the device's log file and determine errors recorded by SL1's logging feature.
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To learn more about how to view and perform SL1's recommended actions and remediations, see the Events Widget section.