Resoto Notebook is similar to Resoto Shell in the sense that you execute queries, but the results are returned in a pandas
DataFrame structure. This gives you more flexibility in filtering, aggregation, visualization, etc.
Here is an example of a heatmap depicting the number of instances per core, per account:
The y-axis represents the number of cores per instance, while account IDs are listed along x-axis. The color of the heatmap cell indicates the number of instances with the given number of cores; the brighter the color, the greater the number.
There are instances where you may be interested in the relationships between resources. Let's say you want to remove a database, but you are not sure of the impact of the removal on other resources. With Resoto Notebook, you can inspect a resource and its relations to see what's going on.
Let's graph a cloud
do (DigitalOcean) and two levels of successor resources:
As mentioned previously, Resoto Notebook allows you to harness the power of pandas, a popular Python package for data analysis. The pandas
DataFrame structure is a table-like object that allows for easy querying, filtering, and aggregation of data.
Let's try aggregating the number of cores in running instances per account, per region:
With this result, we can quickly identify expensive accounts and act accordingly (e.g., taking cost reduction measures).
I hope this blog post has piqued your interest, and that you will try installing Resoto Notebook. Happy exploring!