4.1 Configuring Observability Sources
4.1.1 Observability Sources
4.1.2 Data Pipeline and Parser Configuration
4.1.3 Data Enrichment Techniques
4.2 Configuring RCABot and ML Models
7.2 Authentication and Security
7.3 Data Management and Data Model Handling
7.3.1 Storage
7.3.2 Retention
7.3.3 Export/Import
7.3.4 Working with Data Model
7.4 Control Center
7.4.1 License Entitlements
7.5 Platform Settings
7.5.1 Definitions
7.5.2 Preferences
7.5.3 About
Panels > Heat Map
A heat map (or heatmap) is a data visualization technique that represents data using colors in two dimensions. It uses color variation to display the magnitude of a phenomenon, providing a clear visual representation of how the phenomenon is distributed or changes across an area.
Heatmaps are valuable because they transform complex data into easily comprehensible visuals. They intuitively convey information, with warmer colors indicating a higher concentration of interactions or data points.
To create the Heat Map
(Refer to Dashboard Creation > Query)
On the right side of the default screen, select Visualization as Heatmap to create a Heatmap panel.
There are multiple options to edit the properties of the panel. The first one is Panel Options. Enter a Name and Description for the Panel that you want to create. For instance, if you’re making a Heatmap to track CPU usage, name the panel “Heatmap” and describe it as “CPU Usage.”
The Description is available in the top left corner and can be viewed by hovering over the i button.
The next part of Panel Options is Panel Link where you can point a link to any other website or dashboard of your choice. Enter a title, and URL, and select the ‘Open in a new Tab’ option if you want to open the link in a new tab. Click Save.
The URL can be a link to another dashboard or for getting help or useful info. When you click on a panel, it opens the link either in the same tab or a new tab, depending on your choices. For example, if you want to compare a default dashboard, just click the link to open it.
Defines how the Y axis is displayed.
The Y-Axis options include:
Unit: Unit configuration.
Scale: linear or logarithmic.
Decimals: This setting determines decimal configuration.
Y- Min/Max value: This setting configures the axis range.
Width: The width of the axis.
This setting decides how the X-axis and Y-axis are divided. You can choose a time interval in the Size input. For instance, if you pick 1 hour, each cell on the X-axis will represent a one-hour time span.
Y-axis Bucket: Number of Buckets for Y-axis.
Size: Size of Bucket.
X-axis Bucket: Number of Buckets for Y-axis.
Size: Size of Bucket.
The format of data to be used:
The color spectrum decides how colors are assigned based on the number of values in each bucket. The color on the left side represents the lowest count, and the one on the right side represents the highest count. Note that some color schemes may automatically switch when you use the light theme.
You can also switch to Opacity mode, which keeps the color the same but changes the transparency based on the bucket count.
Mode: Choose between Opacity and Spectrum.
Color: This is the base color for the cells.
Scale: It determines how bucket values are mapped to opacity.
Exponent value: If it’s less than 1, you get a logarithmic scale; if greater than 1, it’s exponential. For 1, it’s a linear scale.
By default, cell colors are calculated using the minimum and maximum bucket values. But you can set your own values using Min and Max. Think of the bucket value like a Z-axis, and Min and Max as Z-Min and Z-Max, respectively.
Choose whether you want to display the heatmap legend on the panel.
You can set the Tooltip options as per your preference.
You have now learned how to configure the Heatmap, change the panel settings, and more. You can save and edit the panel later too.
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