{"id":816,"date":"2022-01-25T12:59:28","date_gmt":"2022-01-25T12:59:28","guid":{"rendered":"https:\/\/blog.ngocha.biz\/?p=816"},"modified":"2022-01-25T12:59:28","modified_gmt":"2022-01-25T12:59:28","slug":"kibana-dashboard-tutorial","status":"publish","type":"post","link":"https:\/\/blog.ngocha.biz\/?p=816","title":{"rendered":"Kibana Dashboard Tutorial for Beginners: Comprehensive Guide"},"content":{"rendered":"

In this Kibana dashboard tutorial<\/strong>, we will look at the important Kibana concepts involved in the creation of different Kibana dashboards and visualizations.<\/p>\n

Kibana is an open-source tool that helps in search and data visualization capabilities. We have covered the Kibana basics in our Kubernetes EFK stack tutorial<\/a>. Take a look at the EFK stack guide to understand how Kibana interacts with Elasticsearch. Also, in our DevOps Engineers Guide<\/a>, we have covered the importance of logging in an organization.<\/p>\n

We will also look at some of the examples of Kibana dashboards<\/strong> to better understand all the visualizing concepts.<\/p>\n

Kibana Dashboard Tutorial for Beginners<\/h2>\n

When it comes to troubleshooting, it is essential to have logging dashboards<\/strong> and log search functionalities that help developers and DevOps engineers troubleshoot applications and infrastructure issues in real-time.<\/p>\n

In this guide, we are going to learn the following.<\/p>\n

Importing Kibana Sample Data<\/h2>\n

To get started, we need data in Kibana. The good news is, Kibana comes pre-loaded with some sample data. We are going to use it to learn to create Kibana dashboards.<\/p>\n

Let’s go ahead and import the sample data into Kibana to create visualizations. Follow the steps given below to import the sample data.<\/p>\n

Step 1:<\/strong> To get the sample data, go to the Kibana home. Sample URL: http:\/\/<node-ip>:30000\/app\/kibana#\/home<\/code>. Click the Load a data set option as shown below.<\/p>\n

\"Kibana<\/figure>\n

Step 2:<\/strong> Load the ‘Sample eCommerce orders<\/strong>‘ data by clicking the “Add data” option. This is the data that we are going to use for dashboards.<\/p>\n

\"Add<\/figure>\n

Once the data is added, you should see the installed option as shown below.<\/p>\n

\"Sample<\/figure>\n

Let’s look at the popular visualizations and create some visualizations for our sample data. After this, we will create our dashboards.<\/p>\n

Open the visualization section inside Kibana for this.<\/p>\n

Understaning Kibana Gauge<\/h2>\n

Let’s understand the concept of Gauge in Kibana.<\/p>\n

    \n
  1. What does Kibana gauge signify? <\/strong>It indicates the status of the metric.<\/li>\n
  2. How is it usable?<\/strong> It displays the metric against a ‘range,’ i.e., it depicts a comparison of current value to a predetermined lower and upper limit.<\/li>\n
  3. How will we use it?<\/strong> Let’s use it to signify the volume of business in a given time frame. Next, we will use the ‘range’ settings to signify business state.<\/li>\n<\/ol>\n

    Since each log indicates a transaction<\/strong> – we can assume that a higher no. of such logs means higher business transactions.<\/p>\n

    We will use colors such as Red, Yellow, and Green to indicate poor, average, and good business performance in the time frame.<\/p>\n

    Steps to create Gauge Visualization<\/h3>\n
      \n
    1. Create a gauge visualization.<\/li>\n
    2. Add a metric with aggregation as count.<\/li>\n
    3. Save the visualization.<\/li>\n<\/ol>\n

      Additional features:<\/strong> It has several other settings that help in creating better visualizations like:<\/p>\n

        \n
      1. type:<\/strong> to create a complete circle or a semi-circle.<\/li>\n
      2. alignment:<\/strong> to control horizontal or vertical display styles.<\/li>\n
      3. color-schemes:<\/strong> to control the color for each range, try it by clicking on the color in the legend.<\/li>\n
      4. sub-levels:<\/strong> to control the text being displayed inside the visualization.<\/li>\n<\/ol>\n
        \"\"
        Click to view in HD<\/span><\/figcaption><\/figure>\n

        Undestanding Kibana Metrics<\/h2>\n

        Let’s understand the concept of Metrics in Kibana.<\/p>\n

          \n
        1. What does Kibana metrics signify:<\/strong> It displays a calculation as a single figure.<\/li>\n
        2. How is it usable:<\/strong> It has the capability to display any metric and also perform calculations of it.<\/li>\n
        3. How will we use it:<\/strong> Let’s use it to display the overall total revenue of the business (sum of taxful_total_price<\/code>) and the total revenue from each customer (sum of taxful_total_price<\/code> grouped by customer’s email address)<\/li>\n<\/ol>\n

          This will help the business find out which customer is spending more at their store! <\/p>\n

          We will display the revenue from the top 5 customers at a given time.<\/p>\n

          Steps to create Kibana Metric Visualization<\/h3>\n
            \n
          1. Create a metrics visualization.<\/li>\n
          2. Add a metric. Select aggregation as ‘sum’ and field as ‘taxful_total_price’.<\/li>\n
          3. Save this visualization as ‘metric-01’.<\/li>\n
          4. Add a bucket – ‘split group’. Select aggregation as ‘terms’ and field as ’email’.<\/li>\n
          5. This will now display results split by customer emails.<\/li>\n
          6. Save this visualization as a new visualization.<\/li>\n<\/ol>\n

            Additional Features<\/h3>\n

            It has several other settings that help in creating better visualizations like:<\/p>\n

              \n
            1. buckets:<\/em><\/strong> to group data according to another field (e.g., email)<\/li>\n
            2. label:<\/em><\/strong> to control the text being displayed inside the visualization.<\/li>\n
            3. ranges:<\/em><\/strong> to treat values in a given range as per its significance,<\/li>\n
            4. e.g. total revenue in the range 0-100 is low and total revenue in the range of 100000-1000000 is high – so we can assign colors differently using this feature.<\/li>\n
            5. color-schema:<\/em><\/strong> to control the color displayed in the visualization as per the ranges.<\/li>\n<\/ol>\n

              To split data by customer’s email,<\/p>\n

              Create a new visualization for total revenue and modify it –<\/p>\n

                \n
              1. Add a bucket (split group)<\/li>\n
              2. Add aggregation of ‘terms’. We use terms when we want to use a custom field like email.<\/li>\n
              3. Select ’email’ as the field.<\/li>\n<\/ol>\n
                \"\"
                Click to view in HD<\/span><\/figcaption><\/figure>\n
                \"\"
                Click to view in HD<\/span><\/figcaption><\/figure>\n

                Kibana Controller<\/h2>\n
                  \n
                1. What it signifies? <\/em><\/strong>It creates interactive controls for easy manipulation of the dashboard data.<\/li>\n
                2. How is it usable?<\/em><\/strong> It has the capability to apply filters to the visualizations inside a dashboard.<\/li>\n
                3. How will we use it?<\/em><\/strong> Let’s use it to filter the logs based on important fields like manufacturer, category, and quantity.<\/li>\n<\/ol>\n

                  We will display the logs by creating a saved query and importing it into our dashboard.<\/p>\n

                  Steps to create:<\/h3>\n
                    \n
                  1. Go to the discover tab.<\/li>\n
                  2. Add the required fields from the left-hand side options.<\/li>\n
                  3. You should see only the added field in the logs panel now.<\/li>\n
                  4. Save it by clicking on ‘save.’ (It’s on the top side of the panel.<\/li>\n
                  5. Now let’s try to create a controller. Create a controller visualization.<\/li>\n
                  6. Add an ‘options list’. Select the index pattern & choose a field.<\/li>\n
                  7. Repeat step 6 for all the controller fields that you wish to add.<\/li>\n<\/ol>\n

                    Additional features –<\/em><\/strong>
                    It has several other settings that help in better filtrations like:<\/p>\n

                    parentcontrol:<\/em><\/strong> It’s used to control the values of a field. Let us understand it with the help of an example.<\/p>\n

                    The ‘category’ controller field has ‘manufacturer’ as the parent control, and the current value for the ‘manufacturer’ field is ‘Low Tide Media.’<\/p>\n

                    This implies that the ‘category’ field will have only those values for which ‘manufacturer’ is ‘Low Tide Media.’<\/p>\n

                    In this way, filtering becomes easier.<\/p>\n

                    multiselect:<\/em><\/strong> This enables\/disables the functionality to have multiple selections in the field. This also helps in filtering out.<\/p>\n

                    E.g., let’s say we want to look at logs where ‘manufacturer’ is ‘Low Tide Media’ and ‘Spiritechnologies’. We can add both values if multiselect is enabled.<\/p>\n

                    dynamic options:<\/em><\/strong> dynamically updates the options list according to user inputs. <\/p>\n

                    control label:<\/em><\/strong> It controls the text being displayed inside the visualization.<\/p>\n

                    Controllers are usually added to dashboards along with a saved query (Yes, you can add a saved query from discover into a Kibana dashboard as well!)<\/p>\n

                    \"\"
                    Click to view in HD<\/span><\/figcaption><\/figure>\n
                    \"\"
                    Click to view in HD<\/span><\/figcaption><\/figure>\n

                    Lines<\/h2>\n

                    What it signifies? <\/em><\/strong>
                    It creates a visualization of trends in the data.<\/p>\n

                    How is it usable?
                    It has the capability to plot various fields and apply basic calculations to the field such as sum, min, max.<\/p>\n

                    How will we use it?<\/em><\/strong>
                    Let’s use it to display the total_quantity of products for various dates; let us also group this information according to the product type, such as ‘men’s shoes’ or ‘women’s clothing.<\/p>\n

                    This type of filtering can help us understand the trends easily.<\/p>\n

                    Steps to create:<\/em><\/strong><\/p>\n

                      \n
                    1. Create a line visualization.<\/li>\n
                    2. In the Y-axis, we will plot the sum of quantities. So let’s select aggregation as ‘sum’ and field as ‘total_quantity.’<\/li>\n
                    3. In the X-axis, we will display the trend as a histogram (It shows the distribution of data) with an interval of 1 hour. It means the data points will be taken on a per-hour basis.<\/li>\n
                    4. We wish to understand the trend for each product category separately. So let’s split the data according to the product category.\n

                      To do this, add a ‘split series’ option and add a ‘sub-aggregation’ of ‘terms’ and select ‘category’ in the field.<\/li>\n

                    5. Apply the changes by clicking on the ‘play’ button at the top of the panels.<\/li>\n<\/ol>\n

                      Save it by clicking on ‘save.’ (It’s on the top side of the panel.)<\/p>\n

                      Additional features –<\/em><\/strong>
                      It has several other settings that help in better visualizations like:<\/p>\n

                      grid:<\/em><\/strong> It’s used to control the visibility of x and y-axis grids.
                      positions:<\/em><\/strong> It’s used to control the placement of the x and y-axis.
                      customlabels<\/em><\/strong>: to control the text being displayed inside the visualization.<\/p>\n

                      Apart from this, it has a lot of options for aggregations like average, min, max, etc.<\/p>\n

                      This is the most commonly used visualization type! So I encourage you to explore this deeply.<\/p>\n

                      \"\"
                      Click to view in HD<\/span><\/figcaption><\/figure>\n

                      Region Map<\/h2>\n

                      What it signifies? <\/em><\/strong>
                      It shows metrics on a map.<\/p>\n

                      How is it usable?<\/em><\/strong>
                      It gives a visualization over the world map! You can visualize your metrics on a per-country basis.<\/p>\n

                      How will we use it?<\/em><\/strong>
                      Let’s use it to display the transactions, i.e., the count of logs carried out in each country. <\/p>\n

                      This type of filtering can help us get a 360′ view.<\/p>\n

                      Steps to create:<\/em><\/strong><\/p>\n

                        \n
                      1. Create a region map visualization.<\/li>\n
                      2. In the metrics section, we want to plot the count of logs for the countries, so let us select ‘count’ as the aggregation.<\/li>\n
                      3. We obviously want to see the count for each country separately. So let’s create a bucket.<\/li>\n
                      4. We have a field called ‘country_iso_code’ that tells Kibana about each transaction log’s country. So select ‘terms’ in the bucket’s ‘aggregation’ and field as ‘country_iso_code’.<\/li>\n
                      5. Increase the size to about 50 to see data for more countries.<\/li>\n<\/ol>\n

                        Save it by clicking on ‘save’. (It’s on the top side of the panel.)<\/p>\n

                        Additional features –<\/em><\/strong>
                        It has several other settings that help in better visualizations like:<\/p>\n

                        vectormaps:<\/em><\/strong> It’s used to specify different maps. <\/p>\n

                        By default, the world map is displayed. But what if we want to visualize data related to just India. We can select ‘India state and territories’ in vectormap option.<\/p>\n

                        It will display a detailed map of India with the state boundaries now.<\/p>\n

                        Similarly, there are other options such as ‘USA states’ or ‘Australia states’.<\/p>\n

                        color-schema:<\/em><\/strong> to control the color displayed in the visualization as per the ranges. <\/p>\n

                        border thickness: to control the line size by which Kibana draws the boundaries in the map.<\/p>\n

                        \"\"
                        Click to view in HD<\/span><\/figcaption><\/figure>\n

                        How to Create a Kibana Dashboard?<\/h2>\n

                        A dashboard in Kibana is a collection of various visualizations. Here is an example dashboard.<\/p>\n

                        \"\"
                        Click to view in HD<\/span><\/figcaption><\/figure>\n

                        We will create a similar dashboard from the visualizations in the above section.<\/p>\n

                        Steps to create a dashboard<\/em><\/strong><\/p>\n

                          \n
                        1. Head to the dashboard section of Kibana and create a new dashboard.<\/li>\n
                        2. Start adding the visualization and saved queries here.<\/li>\n<\/ol>\n

                          That’s it! You have created your very own first dashboard now! Save it for future use.<\/p>\n

                          Next steps<\/h2>\n

                          In production environments, teams usually try to keep a backup of these visualizations and dashboards in a JSON file for safekeeping.<\/p>\n

                          Steps to create a backup file:<\/em><\/strong><\/p>\n

                            \n
                          1. Go to Kibana’s management section.<\/li>\n
                          2. Go to the saved objects tab.<\/li>\n
                          3. Select your visualizations and dashboards from the list.<\/li>\n
                          4. Export them. Kibana will create a JSON file for you and download it to your system.<\/li>\n<\/ol>\n

                            Creating a backup is not enough; we also need to understand importing the objects through the file.<\/p>\n

                            Steps to import an object using a backup file:<\/em><\/strong><\/p>\n

                              \n
                            1. Under the saved objects click on the Import button.<\/li>\n
                            2. Next, select your JSON backup file. Kibana will import them into its list now.<\/li>\n<\/ol>\n

                              Besides backups, Kibana also has tons of features like anomaly detection using Machine Learning and functionalities to receive email & slack alerts. So be sure to explore them too!<\/p>\n

                              Conclusion<\/h2>\n

                              EFK is a tool used by 100s of DevOps teams every day. In this EFK tutorial series, you have learned a very useful skill of creating a Kibana dashboard <\/p>\n

                              There are many others; explore different options thoroughly to create the best visualizations!<\/p>\n

                              In the next article, we will learn how to create Kibana dashboards for Kubernetes cluster monitoring.<\/p>\n

                              Also, if you are learning about logging & monitoring, you might like my guide on setting up Prometheus on Kubernetes<\/a>.<\/p>\n

                              \n

                              Ngu\u1ed3n:<\/strong> Kibana Dashboard Tutorial for Beginners: Comprehensive Guide \u2014 DevOpsCube<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

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