I’ve worked with Log Analytics quite a bit over the years and that’s taken me down the road of the Kusto Query Language – or KQL
So, using Azure Data Explorer Clusters seemed the next logical step on that journey.
Log Analytics is great for storing and querying diagnostic data from Azure (or any other infrastructure) – but I decided that I might want to investigate my own data.
So, with that in mind – I decided to set up my own Azure Data Explorer Cluster and start looking around.
It’s easy enough to find in the Azure Portal – I chose to favorite it as I expect to be using it a fair bit over the next little while
You can also get to it via a shortcut
Next, I select “Create” and then filled in the minimum amount of information needed to get up and running.
Just a few things to focus on here – firstly, the combination of the cluster name and the region is going to form part of a URI – so this has to be unique, and there are certain formats that the name has to meet, but you’ll soon know if you have not met them as the screen will call them out instantly.
Additionally, I’m just creating a Dev cluster here – note that there is no SLA.
Also, the region that I chose has Availability Zones – yours might not, or you might choose not to take advantage of them. I chose to include all three.
You’ll then notice that you can step through all of the remain setup.
I simply accepted the defaults, but it’s great to know you can define additional settings at this stage.
It’ll take a little time to set the cluster up – but you’ll soon be up and running.
And once we are up and running we can see that the URI is made up of the cluster name and region
In order to create a database on the cluster head to the resource, click on “Databases” in the left hand side menu (scrolling may be needed), click “Add database” near the top of the screen and then enter a name for the database in the fly-out pane.
That’s it – we now have our first Azure Data Explorer Cluster created with a new shiny database.
Hope this help somebody.