Data which is provided by an instance of Application Insights connected with your application is in most cases more than enough. As long as you're logging satisfying amount of information, you can easily track all your metrics and diagnose problems with ease. But what if you'd like to get a deeper insight into "what is really going on there"? I guess it'd possible to use AI's REST API and fetch all the data into your custom tool(or any kind of 3rd-party software) to analyze it - but who needs it when you have Application Insights Analytics?
To access Analytics you need only to access this link - https://analytics.applicationinsights.io. When accessed, you'll see a welcome screen, which out-of-the-box allows you to access some common queries.
A welcome screen gives you a rapid start when it comes to analyze common statistics
I strongly recommend you to try out common queries - they allow you to quickly get an overview of the capabilities of this tool.
Querying the data
For sure you'll notice, that charts and other statistics are the result of a query. This is what makes Analytics a really powerful tool - you can query any kind of metric available to you(like dependency duration, custom events, client OS and many many more) and combine them to get a what you're looking for.
An expanded tab of traces of the left - still there're some missing on the screen...
What is more, when creating or editing a query you can take advantage of inbuilt editor, which helps with a syntax and highlights all your errors. It's definitely much more polished than the one from the Function Apps :)
You can easily add metrics from the tabs on the left and then use an intuitive editor to combine them
There's a one cool feature, which makes Analytics really helpful in searching the root cause of a problem - Smart Diagnostics. It allows you to quickly discover what is "strange" in this particular fragment of your log(maybe one dependency fails to respond or responds three times longer than usual).
Those highlighted dots on the chart allow you to run a smart detection on those parts of the data, which doesn't match the rest.
You have to be aware of the fact, that this diagnostics is not perfect and relies on the data you provide(so if you provide not enough data, it will tell you, that something is wrong, but not what it exactly is). Nonetheless is encourage you to gather more and more data, so its proposals are more and more valid and precise.
In the next post we'll try to run more advanced queries and find where limits of this tool are.