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As organizations become more digitized, customers, employees, and partners want more control over, and access to, digital services. To stay on top of those demands, you need a hybrid multicloud strategy that keeps your on-premises infrastructure agile and high performing, with the ability to leverage the cloud on demand.

One important question to ask: Where is the best place to store my data, on premises or in the cloud? If you want control of your data, then on premises is the right choice. However, the data center isn’t designed to handle the additional infrastructure that’s needed, and you can’t build it at the speed your business requires.

What about the cloud? Public clouds offer attractive elasticity and cost efficiencies, which can speed up innovation throughout your business. However, running workloads in public clouds presents management complexity and risk, such as:

• Data privacy and control. Compliance and sovereignty laws can be complex and difficult to navigate.
• Security and control. Public clouds can leave your data vulnerable, and you need a cybersecurity safeguard.
• Multicloud choice. It’s great to have access to multiple clouds, but inconsistency between clouds can make management and scale challenging.

NetApp Keystone Flex Subscription, powered by Equinix

• Centrally locate data “next to” the leading cloud providers rather than “in” one public cloud, so it remains private. Data is close to public cloud services such as compute, databases, and analytics, with dedicated high-speed connections, resulting in low latency (< 1ms roundtrip lag).
• Avoid oversubscribing and overprovisioning. Instead, you pay for space and other operational expenses as a percentage of your storage bill, which aligns with your storage usage.
• Get the control and governance that your enterprise is used to, along with capacity to grow as your business expands.

Industry-specific solutions

• From vehicle design to manufacturing, today's auto sector runs on data. Developing and deploying Advanced Driver Assistance and Autonomous Vehicle Systems (ADAS) requires the ability to collect, store, and manage massive amounts of data, high-performance computing capacity, and advanced deep learning frameworks. It also requires the capability to do real-time processing of local rules and events in the vehicle.
• Electronic design automation (EDA). EDA workflow requirements vary widely. On the front end are massively parallel register-transfer level simulations with up to a million metadata-heavy small files. On the back end are the processing demands of large physical and manufacturing files. EDA infrastructures need the flexibility to support the performance requirements (latency, IOPs, and throughput) of highly parallel and often bursty EDA workflows.
• Healthcare and life sciences. Despite the regulatory hurdles, healthcare and life sciences providers are adopting public clouds for scalability and flexibility. Without the proper foundation and planning, adopting multiple public clouds can mean management overhead and security headaches for your IT department. Cloud-based solutions can accelerate time to insight for a range of applications, including clinical genomic sequencing, drug design, and cancer research.
• Media and entertainment. Video and animation can create giant file sizes that are hard to move around among the numerous studios, editors, and rendering processes that create the final product. With a centralized repository between the clouds, these giant media files can remain stationary, while studios leverage the appropriate tools from their hyperscaler of choice to collaborate on media that is cloud connected.
• Financial services. As traditional banks face increasing competition and evolving customer expectations, they are fast-tracking their digital transformations. The public cloud has helped accelerate the transition to digital. It offers scalability and elasticity that cannot be matched in a traditional IT procurement model. However, for financial services institutions there are significant barriers to public cloud adoption, including regulatory requirements, data privacy, data security, and data egress costs.

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