Digital transformation initiatives have accelerated and remain the top business priority, especially in today’s environment, and the public clouds offer the speed and flexibility needed to navigate this new normal as companies find new ways to work, interact and do business. However, unoptimized clouds can be costly and slow down the business transformation. To address this challenge, an application-driven infrastructure translates the application’s workload patterns and drives the best possible level of performance and cost for storage and compute. Together, NetApp and Spot’s application-driven infrastructure for continuous optimization will help customers save up to 90 percent of their compute and storage cloud expenses and will help accelerate public cloud adoption.
“In today’s public clouds, speed is the new scale. However, waste in the public clouds driven by idle resources and overprovisioned resources is a significant and a growing customer problem slowing down more public cloud adoption,” said Anthony Lye, senior vice president and general manager, Public Cloud Services, NetApp. “The combination of NetApp’s shared storage platform for block, file and object and Spot’s compute platform will deliver a solution for the continuous optimization of cost for all workloads, both cloud native and legacy.”
Spot and NetApp aiming for continuous optimization
Spot provides a combination of tools for visibility and automation, that drive continuous optimization of workloads in a single platform while maintaining both SLA and SLO. This relieves DevOps, CloudOps, and FinOps teams from the burden and complexity of managing, scaling, tuning and optimizing cloud resources so that they can focus on business innovation under acceptable budget controls.
Together, NetApp and Spot will establish an Application Driven Infrastructure to enable customers to deploy more applications to public clouds faster with Spot’s “as-a-service” platform for the continuous optimization of both compute and storage for both traditional IT buyers with enterprise applications, cloud-native workloads and data lakes.