Yes, I could have explored writing a bulky Graphical User Interface, but for something essentially that simple such proof of concept is the way to go! Research and requirements What I wanted to achieve as a user and consumer of the data was to have the data available with ease at any point through just a few simple clicks and more so to have them visually digestible. This is what you need to determine as you start off. You need to think about what performance analysis you want to perform and then determine what data to visualize, what information do you want to correlate, what questions will your team members ask?ĬA Mainframe Application Tuner as a performance monitoring solution offers a nice command-line interface (CLI) that allows you to quickly pull performance information, but maybe that is not enough, or you would like to see it in a different way or present it to your peers more effectively. That led me to research how to display the data available and to best get the value my team might want. “A picture says a thousand words”, they say. To start with, I had the data accessible through RESTful interfaces, but I wanted to visualize it, easily correlate it, and then share it with my peers. You can change the names of the column and the table to fit your data.How can I easily view the results of a mainframe performance run? How can I share these results with my team? This is my experience in solving this challenge. This assumes you have a table called Artist and a column named ArtistId. Select the Edit SQL link and paste the following SQL: SELECT ArtistIdFROM Artist Select your database from the Query drop-down menu and choose to format this query as a table in the format as drop-down. Choose this option, then select Add new panel. You now have the option create your first dashboard. To show a single number, we use the single stat panel. The first panel will show the total number of Artists in our CD database. Each panel can show the same or different data using a visualization that is the easiest for you to process. Panels represent a visual representation of a query. I’m creating a dashboard from one datasource, but you can use different data from different sources in the same dashboard. Now that your database is connected, you are ready to create your first dashboard! I’m going to create a dashboard showing stats about the CD database we connected in the previous section.ĭashboards are made from panels of information organized into rows. If everything is configured correctly, you should see a green box with the message Database Connection OK. It’s safe to leave the rest of the fields as default. I’m using a local MySQL database running on localhost on port 3306 for the database CD and with the user we made previously, grafanaReader. Complete the web form with your connection details. The first option on the display is Create your first datasource. To add a link from your database to Grafana, switch back to the Grafana interface. GRANT SELECT ON CD.Artist TO 'grafanaReader' In your MySQL database, run the following in the database administrator role to add a read-only user named grafanaReader to your database CD for the table Artist: CREATE USER 'grafanaReader' IDENTIFIED BY 'password' Your first step is to add a Grafana user to your database. For my example, I’ve created a database named CD with a table called Artist to simulate a database behind a music library app. Now we’ll walk through configuring Grafana to connect to your MySQL database. Grafana supports pretty much every data source you can think of, from traditional databases like MySQL to log aggregation platforms like AWS Cloudwatch. Your data source could be a database or a collection of logs. Configuring your data source is the first step to setting up your Grafana dashboard.
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