Pointers at Glance
- A multi-cloud SaaS and managed service provider, Wanclouds, is adding Cost Optimization as a service (COaaS) to its solution offering.
- It will ensure current and prospective customers optimize cloud spending as costs rise.
Wanclouds is spinning its existing cost management tools to meet its demand into an entirely new service offering alongside its Disaster Recovery as a Service (DRaaS) and Migration as a Service (MaaS).
Powered by VPC+ and building on the latest version of its spend visibility and cost optimization feature, Wanclouds COaaS allows enterprise-wide spend visibility and cost tracking for different cloud resources.
Through its proprietary analytics on users’ cost and usage data and Amazon’s Cost Explorer for rightsizing, Wanclouds gives customers a real-time view into the cost of cloud resources, purpose tagging, backups, recommendations on infrastructure changes for optimization and resource pause options.
As per the vendor, Wanclouds enables users to act on these cost savings recommendations with one click. This ability is important for IT leaders as CFOs and FinOps repeatedly ask to curb cloud spending associated with digital transformation initiatives that started during the pandemic.
Wanclouds’ COaaS dashboard provides a central hub with a summary of all AWS cost recommendations regarding idle resources and rightsizing total spending. The insights spotlight the most used resources, along with their purpose.
Wanclouds plans to add COaaS support for those working with Google Cloud, IBM Cloud, and Microsoft Azure to enable multi-cloud organizations to utilize actionable cost savings recommendations across clouds.
Highlighted features of Wanclouds Cost Optimization as a service (COaaS) are:
- NAT Gateways Tagging of cloud resources based on the engineering stage, i.e., development, testing, and production
- Sorting costs by resources like EC2 instances, Elastic IPs, Elastic Load Balancers and Volumes.
- One-click ability to stop and re-start idle resources and rightsizing recommendations for cost savings based on predicted monthly costs.
