Whether you've recently migrated to the cloud or you've been operating there for a while, you've likely realized how challenging it is to understand where your cloud spending goes and what drives your costs. According to Forbes, 80% of enterprises consider managing cloud spending a challenge, and the average proportion of cloud spending that's wasted is 35%.
Moving to the cloud is supposed to result in cost savings. But without the right tools and know-how to stay in control, costs can actually spiral upward. And if you don't know why your costs are rising and what you can do to optimize, the problem will only get worse as cloud infrastructure continues to grow.
It's inevitable that semiconductor manufacturing will rely more heavily on the cloud. With chip designs becoming smaller and the volume of data produced by them growing, high-performance computing (HPC) capacity in the cloud is becoming pretty much mandatory.
The problem is that these environments can become enormously costly, difficult to size appropriately, and time intensive to manage. Typically, they include thousands of cores and hundreds of petabytes of storage—a figure expanding by double digits every year. In a survey cited by G2, 64% of respondents said that "cost management and containment" is the biggest concern with running the cloud.
The number of resources required to manage these environments continues to build. And not everyone will have the time or ability to analyze their infrastructure efficiency and keep costs optimized.
When stretched, you might end up buying services and resources that don’t match your requirements, creating risk and unnecessary cloud spending. Add a lack of visibility into cloud computing resources into the mix, and you have a recipe for serious cost issues.
To deliver maximum cloud value, semiconductor manufacturers are best served by investing in tools that can automatically adapt to their ongoing needs and dynamically match to the optimal cloud resources. Even with minimal cloud optimization efforts, businesses can potentially save 10% within 2 weeks.
A well-executed and optimized cloud environment lets you scale resource use to the needs of the moment. It also lets you access burst capacity for compute-intensive activities while taking advantage of peak savings when possible. This kind of optimization requires ongoing, proactive management rather than a single, one-time fix.
The move to cloud exposes the variable cost of storing and managing data like never before. Our cost optimization solutions will make unexpected expenditures disappear in an instant.
From clouds to data centers, NetApp provides you with full-stack visibility. Our solutions help you monitor, troubleshoot, and optimize all your resources and applications from one place. Whether it’s on premises or in the cloud, you can track your cloud spending by understanding unused infrastructure and overprovisioned workloads. With our solutions, you can control costs, maintain availability, and protect data.
By using machine learning to combine extensive data about cloud infrastructure pricing, capacity, availability, and real-time analysis of application resource needs, we can identify the ideal mix of spot, reserved, and on-demand compute resources. You can automatically provision, scale, and refresh those resources with minimal disruption, while meeting demands and minimizing costs.
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Gerrit Vandenplas is a global enterprise manager. He joined NetApp six and a half years ago to manage the commercial relationship between NXP—a multinational semiconductor manufacturer—and NetApp Worldwide. Gerrit’s areas of expertise include data management, helping companies unlock the best of cloud, supporting customers on their cloud journeys, and bringing consistency to their data and cloud efforts.
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