Top Rated Federator.ai Alternatives
Automated resources reservation planning based on AI recommendations. This is raising consolidation on our clusters, with an automated process. Review collected by and hosted on G2.com.
Licensing model based on central processing unit (CPU) core. Review collected by and hosted on G2.com.
9 out of 10 Total Reviews for Federator.ai
Its self-evolved machine-learning algorithms can pretty much accurately capture application workloads. It gives me the confidence to follow its timely recommendations to allocate cloud resources. Review collected by and hosted on G2.com.
It’s not a SaaS application, it’s a standalone containerized application running on Kubernetes. Some industries with a strict information security policy, such as banking or telecom, will love it, but I personally prefer SaaS. Review collected by and hosted on G2.com.
It is impressive to provide visibility of the correlations between applications the resources with quantified figures. It provides a solid base for actionable optimization. Review collected by and hosted on G2.com.
Role-based access control to the software is needed so that accounts involved in the project can be managed by different access privileges. It would be better to be multitenant. Review collected by and hosted on G2.com.
The comparison of potential savings in the multi-cloud environment is based on its accurate application workload predictions. It made a meaningful cost comparison and streamlined our decision-making process for workload migration between different cloud service providers. Review collected by and hosted on G2.com.
I really haven't found anything to dislike about Federator.ai. It saves a lot of time for our team on the cloud migration issue. Review collected by and hosted on G2.com.
Cost savings is the most stunning benefit. Federator.ai shows us cost savings opportunities by avoiding the over-provisioning of resources through its machine-learning predictions and comparing the pricing of resources our operations require from different public clouds. Review collected by and hosted on G2.com.
In practice, every siloed business unit has access to the console, which is good for helping unify the business objectives. But we do need multi-tenancy support for avoiding our parameters being touched by other units. Review collected by and hosted on G2.com.
The predictions its machine learning-based engine provides are pretty awesome! Quick, accurate but few resources consumed. Review collected by and hosted on G2.com.
Um… I don’t appreciate its console in a dark black color. Haha..
Actually, I like its features and most of its design in the console to provide information. Review collected by and hosted on G2.com.
Federator.ai’s resource planning feature much helps with resource allocation planning for my applications. The cost allocation feature shows the real and potential usage per namespace provides detailed insights into how cluster resources are used. Review collected by and hosted on G2.com.
Federator.ai neither provides a well formatted (better customizable) report that summarizes the resource usage and planning of applications nor provides the automation feature to apply the resource recommendations automatically. Review collected by and hosted on G2.com.
Continuously collecting workload metrics from infrastructure to application, provide predicted resource allocation recommendation to reduce cluster resource waste, also saving cost regardless of on local or public cloud. It is a high ROI for my team. Review collected by and hosted on G2.com.
If it can support multi-tenant, that would be better for my company and other application teams. Review collected by and hosted on G2.com.
All applications are automatically scaled to meet the predicted resource usage, I do not have to worry about over provisioning for anything or shut down servers as usage goes down. Review collected by and hosted on G2.com.
I have not found something that I dislike about auto-scaling as of yet. Review collected by and hosted on G2.com.
