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              Types of Panels

              This topic introduces you to the types of panels in the New Dashboard.

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              Timechart Panel

              A Timechart is a graph produced by applying statistical aggregation to a label over an interval. The X-axis of a timechart will always be time.

              Timecharts allow you to see the change in metric value over time. The amount of data visualized on a graph is dependent on the time selection selected within the Dashboard. You can aggregate metrics from multiple sources into a single line, or graph a line per combination of segment labels.

              Time aggregation: For example, the average value of cpu.used.percent metric is computed for each entity over 1 hour at 1-minute intervals.

              Group Rollup: For each host.hostName the values from time aggregation are averaged over the scope and the top 10 segments are shown on the chart.

              The only supported panel type now in time series is the Line chart.

              Line Chart

              The Line panel show change over time in a selected window. Time is plotted on the horizontal axis and the change that is measured is plotted on the vertical axis.

              The image below shows the trend of resource consumption of top resource-hogging hosts in the last one hour.

              Configure Line Chart

              For information on configuring a chart, see Create a New Panel.

              Stacked Area

              An area chart is distinguished from a line chart by the addition of shading between lines.

              For information on configuring a chart, see Create a New Panel.

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              Number Panel

              Number panels allow you to view a single value for a given entity, along with optionally comparing the current value to historical values. Use the Number panel when the number is the most important aspect of the metric you’re trying to display, such as unique visitors to a website.

              Do not use this panel to see a trend, rather use it when you need to see the average of a value over the given time range. This is also useful for counting entities, such as the number of nodes in a cluster.

              For information on configuring a panel, see Create a New Panel.

              Major Features

              • The default preset for the Number visualization is 1 hour.

              • The global default values for the threshold are overridable. The new value can be reset back to the global default.

              • A comparison between two threshold values determines color-coding directions.

              • The Compare To functionality can be toggled between enabled and disabled.

              • When the Compare To value is set, the preview is updated accordingly showing the comparison value and an arrow denoting the metric has increased or decreased.

              • The unit displayed for Thresholds is determined by the query.

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              Table Panel

              The Table panel displays metric data in tabular form. In this view, you can review metric values and their associated labels in a single view. Use Table panels for such quantitative analysis where you can see actual values instead of visual representations. Similar to a spreadsheet, you can look at a combination of metric values and their segments. This is useful when you don’t necessarily care about the change in metric over time, or want to run reports to download as CSV/JSON for offline analysis.

              The panel displays the value returned by the metric query specified in the Query tab. The value is determined by the data source and the query. Each datapoint will have an associated raw and an option to add columns for additional metric values.

              Configuring Table Panel

              Major features include but not limited to :

              • Queries

                • The first query you build cannot be removed.

                • With subsequent queries are built, you cannot remove all the queries except the first one.

                • Changing the unit of the query changes the unit in the table as well.

                • Changing the display format on the query reflects on the row values.

              • Segmentation

                • The segmentation label determines the column name.

                • The segmentation in conjunction with metric values determines the values displayed on the rows.

              • Scope

                • The selected scope determines the values displayed on the table.
              • Metric / Labels Columns

                • Adding a new query insert a new column with the name of the metric as the column heading.

                • Metric values in conjunction with segmentation determine the values displayed on the rows.

              • Sorting

                • Column sorting is based on the selected column header and the type of sorting (ascending and descending).

                • When another column is sorted, the table is resorted by that column, resetting the previous sorting.

              • Resizing

                • Grab the header column by the borderline to resize the columns.

                • Browser window resizes shouldn’t reset the resize of the columns if you have resized any columns.

                • When resizing the browser window, table columns are resized to cover the full width. An exception is when you have already resized columns. In such cases, other columns that you have not resized are resized on browser window resize.

                • The last column in the table is not resizable.

              • Export

                • The table by default shows a maximum of 50 rows.

                • Clicking on Export all results… below the table opens the Export Data window.

                • Export data in either JSON or CVS format to a file. The default name of the file is the panel name. Renaming the default filename is permissible.

              For information on configuring a chart, see Create a New Panel.

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              Text

              The example below uses a text panel as a reminder list of the testing steps for a procedure.

              Text Panel Markdown

              Headers

              # H1
              ## H2
              ### H3
              #### H4
              ##### H5
              ###### H6
              
              H1
              ======
              H2
              ------
              

              Emphasis

              *italics* or _italics_
              **bold** or __bold__
              **combined _emphasis_**
              ~~strikethrough~~
              

              Lists

              1. First ordered list item
              2. Second item
                * Unordered sub-list.
                  Sub-paragraph within the list item.
              1. Third item
                8. First ordered sub-list item.
              103. Fourth item
              

              General guidelines:

              • The list item number does not matter. As shown in the example below, the formatting defines the lists.

              • List items can contain properly indented paragraphs, using white space.

              • Unordered list can use: *, -, or +.

              Linebreaks

              This is the first sentence.
              
              This line is separated from the one above by two newlines, so it will be a *separate paragraph*.
              
              This line is also a separate paragraph.
              This line is only separated by a single newline, so it's a separate line in the *same paragraph*.
              

              Trailing spaces can be used for line-breaks without creating a new paragraph. This behavior is contrary to the typical GFM line break behavior, where trailing spaces are not required.

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              Toplist

              A Toplist chart displays the specified number of entities, such as containers, with the most or least of any metric value. This is useful for “ranking” metric values in order, for example, considering hosts that have the highest amount of pods running or the highest consumers of CPU or memory in your infrastructure.

              Major Features

              • Toplist supports executing multiple queries.

              • Segmentation is supported for all queries.

              • Text displayed on the bars in the chart is based on queries and segmentation.

                • If there is a single query without segmentation, the query name is displayed.

                • If there is a single query and multiple segmentations are selected, segmentation texts separated by > sign are displayed.

                • If there are multiple queries, the query name is displayed on the bar.

              Segmentation

              You can use multiple objects to simultaneously segment a single metric. For example, cpu.used.percent segmented by kubernetes.cluster.name, kubernetes.namespace.name, and kubernetes.deployment.name.

              In this example, deployments are sequentially listed in the order of resource consumption. Use Display to toggle between descending (Top) and ascending order (Bottom).

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              Histogram

              Sysdig Monitor handles three types of Histograms:

              • Histogram panel type on the Dashboard: Histogram panels allow you to visualize the distribution of metric values for large data collection. You should select a segmentation, and optionally, the number of buckets.

                Use Histogram for any metric, Sysdig native or custom, counter or gauge, segmented by a dimension/label. The histogram panel helps understand value across different segments. For example, CPU usage percent by pods across your cluster gives you the aggregated value across the selected time.

              • Legacy Prometheus histogram collection: This implementation of legacy Prometheus Histograms is deprecated in SaaS 3.2.6 release.

                To create a Histogram, use the Prometheus integration to collect histogram metrics and use the PromQL panel with the histogram_quantile function.

              • Prometheus histograms (collected as raw metrics): The legacy Prometheus histogram collection is replaced by the new Prometheus histogram. You can natively collect histogram metrics, and for visualization, use timechart:

                For example, run the following query to build a timechart:

                sum(histogram_metrics_bucket{kubernetes_cluster_name="prod"}) by (le)