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An excellent AIOps tool
The AI engine predicts a very close result of workloads similar to the actual ones. It does help allocate resources to the operations in advance. It shows the degree of how much impact and correlations between main applications and resources, which is a good reference for where to start our optimization.
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Best Resource Management tool with AI-enabled for Kubernetes
What do you like best about the product?
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.
What do you dislike about the product?
If it can support multi-tenant, that would be better for my company and other application teams.
What problems is the product solving and how is that benefiting you?
Most application resource allocation is overprovision, which has wasted much Kubernetes cluster resource and money. Federator.ai provides right-sizing based-on workload prediction results, reduce the waste situation. We could release more resources for other applications.
Recommendations to others considering the product:
It is very helpful to manage Kubernetes resource and right-sizing recommendation, saving money as well. All of the recommendations all based on workload and prediction. It is very nice.
Experience in using Federator.ai
What do you like best about the product?
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
I have Kubernetes clusters running many container applications. Allocating proper resources to ensure my applications won’t become unstable because of insufficient resources and won’t waste too many resources because of unnecessary over-provision has always been one of my primary concerns when administrating my clusters. Federator.ai provides the resource usage monitoring and allocation recommendations that reduce a lot of management efforts for me.
Recommendations to others considering the product:
I suggested to provide online chat services in order to enable the participants to respond quickly.
Auto-Scaling via resource recommendation
What do you like best about the product?
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.
What do you dislike about the product?
I have not found something that I dislike about auto-scaling as of yet.
What problems is the product solving and how is that benefiting you?
It solving main business problems of health and load on our web and applications. Being able to reduce unnecessary spending and increase application service quality.
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