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In this tutorial we'll explain how to get the GitLab Extractor integrated with your Meltano project to pull your GitLab data and load it into a Postgres analytics database.
For this tutorial, you can use a new or existing Meltano project.
If this is your first time using GitLab with Meltano, you will need to enable access to GitLab's API and get your GitLab Private Token by following the instructions found in the GitLab Extractor documentation.
Add the Postgres loader to your Meltano project through the command line:
meltano add loader target-postgres
Then setup your Postgres database by following this tutorial.
Open your Meltano instance and click "Pipelines" in the top navigation bar. You should now see the Extractors page, which contains various options for connecting your data sources.
tap-gitlab by clicking on the
Install button inside its card.
On the configuration modal we want to enter the Private Token that GitLab extractor will use to connect to GitLab, the Groups and Projects we are going to extract from and the Start Date we want the extracted data set to start from.
For this tutorial, we will scope our data sample to only include the Meltano project to make things faster.
Projectwith the Meltano project:
Start Dateto the beginning of last month, for example:
Once you click Save, your pipeline will kick off! And once that is complete, you can click on the Analyze button to choose the model you want to analyze!
The Analyze page contains an interactive user interface to allow you to dynamically build queries and visualize your data.
Now, let's explore and analyze our GitLab Issues data by selecting the following attributes in the left column:
And with that, the big moment is upon us, it's time to click
Run to run our query!
You should now see a bar chart visualization and a table below to see the data in detail!
Let's order the data by Year and Quarter ascending:
We can also filter the results to only include bugs. Select the
Filters dropdown menu at the top of the Query pane and add a filter to only keep issues with the
Labels (for filtering) -->
We add the percentages around the
bug cause issues may have multiple labels and the
bug label can be anywhere in that field.
And, finally, switch the graph to an area chart:
When we find an analysis that we want to reference in the future, we can easily do this by creating a report. This can be accomplished by clicking on the
Save Report dropdown in the Analyze toolbar. This will open a dropdown with a default report name that is dynamically populated, but can be easily changed.
Once we click
Save, we should see the upper left "Untitled Report" change to our new report name.
And with that, our analysis has been saved!
As you acquire more reports, you will probably want to organize them via dashboards. This can be done by clicking on the new
Add to Dashboard dropdown in the toolbar.
Since we have never created a dashboard, click on
New Dashboard, which will trigger a modal that contains a dynamically generated dashboard name that can be customized as desired.
Once we click
Create, we can now verify that the our report has been added to the Dashboard by clicking on the
Add to Dashboard menu. We can also visit the Dashboard directly by clicking on the
Dashboard navigation item in the header, which shows our newly created Dashboard and the associated Report.
And with that, you have now setup a complete end-to-end data solution for extracting and analyzing GitLab data with Meltano! 🎉
You can now check the rest of the pre-bundled Models for Projects, Merge Requests, Users and more.
Don't forget to save the reports that you find useful and add reports to your dashboards.