Each user can have their own dashboard that they want to consume. Instead of having to share one dashboard for multiple users, you can create individual views for each user to view, and that view will contain only their own accounts, which allows for separation of data.
Principal Consultant at a tech consulting company with 501-1,000 employees
Mar 27, 2024
The most crucial feature in reducing my cloud costs has been the rightsizing recommendations, along with the dashboards that track reserved instance spending coverage and utilization. As for Cloudability's integration with our existing cloud infrastructure, it's not integrated directly into our AWS infrastructure but rather reads and pulls data from it, providing valuable insights and analysis for cost management.
One of the standout features of the solution is its groups and views functionality.
The solution is highly-stable.
The solution is highly-scalable.
The customer support is good. They can be easily contacted.
The initial setup is straightforward.
It's an excellent tool, especially when dealing with multiple clouds. It streamlines the process, eliminating the need to check each cloud individually.
Infrastructure Engineer at a computer software company with 11-50 employees
Dec 11, 2018
We have dealt with a few technical support people where we ask for one thing and they might not deliver straightaway. It seems like they are a stretched across multiple customers.
The API is not well-documented. It is not straightforward and difficult to use. This needs to be improved, as it is very difficult for our developers to develop automation around it.
Principal Consultant at a tech consulting company with 501-1,000 employees
Mar 27, 2024
I wish there was a feature to temporarily remove certain recommendations from the list for teams that couldn't implement them immediately. I believe Cloudability could improve its automation functionality and enhance cost allocation modeling.
We would like them to have a linear regression, so we can be predictive for budgets, allocations, and the year's follow ups. We also want to have a longer window of analytics with better certainty that our workload will fit the model, not just in a two week window.
There is always room for improvement in education and training. We are not that mature in terms of our automation. It could help us identify where we could optimize in terms of build.
