Not all workloads are well-suited for deployment in the cloud; some are best left on-premises. Figuring out what should run where and how to optimize workload deployment is a challenge that Quest Software's newly rebranded Foglight Evolve platform aims to help solve.
The platform, previously known as Foglight for Virtualization, was originally focused on providing monitoring and optimization for virtualization technologies. The new Foglight Evolve platform goes beyond traditional virtualization to also include container and multicloud deployment options.
The hybrid cloud management platform includes three editions. The primary cloud edition integrates monitoring and migration capabilities for Microsoft Azure and Amazon Web Services (AWS). The Foglight Evolve Operate offering integrates optimization capabilities, while Foglight Evolve Monitor adds monitoring and analytics.
Mike Condy, senior product manager of the Quest Data Protection business, told ITPro Today that Foglight for Virtualization did not have specific optimization for containers and, more specifically, for Kubernetes container orchestration system deployments, but that capability has been added to Foglight Evolve. He noted that organizations today are looking at multiple options, and it's often not obvious what the best one is for deployment.
Choosing Where to Deploy
Among the most valuable capabilities in the Foglight Evolve platform is the ability to help administrators understand where best to deploy a workload. The platform provides insights about both performance and cost for different types of deployments, including container, cloud and on-premises, Condy said.
Users can set a budget they want to work within and set a target for what the cost will be for a given workload deployment. If a cost is exceeded or hits a certain threshold, an alarm is triggered and sent to the administrator.
Not only can administrators use the Foglight Evolve hybrid cloud management platform to find the ideal place for a deployment, but they can also use it to help with migration to AWS and Microsoft Azure public cloud services, when appropriate, according to Condy.
While it makes sense to deploy many types of workloads to the cloud, databases are still often better suited to on-premises deployments, at least from a cost perspective. Condy noted that while performance of a cloud database can sometimes exceed on-premises counterparts, for large databases the operational costs are typically less if run on-premises.
Regarding optimization, Condy said that whether the workload is on-premises or in the cloud, the issues generally are related to configuration. He noted that one of the things that Foglight Evolve can help administrators with is to optimize cost and performance via proper configuration for a given workload deployment.
Looking forward, Condy said that future iterations of Foglight Evolve will help DevOps decisions about where and how to build software on-premises and in the cloud.