By 2020:
“92% of applications will run in cloud-scale data centers”
(Cisco)
By 2030:
“Industrial internet of things to top
$60 trillion”
(GE)
By 2020:
“We will be creating 44 zetabytes of data annually”
(IDC)
By 2022:
“The AI market is expected to be worth
$16.06 billion”
(Research&Markets)
New applications, such as IoT, Big Data Analytics and Artificial Intelligence, have a big impact on storage workloads and require a significant transformation in storage architectures. To meet the requirements of these new application workloads, enterprises and service providers are seeking to optimize their infrastructures in the same way as these tech giants.
Scalability
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Scale linearly to any size, data center-readiness
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Client-side intelligence means data services scale as you add clients
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Locking is 100% distributed across targets and clients and scales as you add nodes
-
No centralized metadata manager means no scalability bottleneck
Flexibility
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Mix different storage media types, server types and deployment models
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Use native NVMesh and/or NVMf transports to future-proof your environment
-
Avoid one-type fits all logical volume simplifications
-
Scale Storage and CPU independently
Efficiency
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Enable high NVMe SSD utilization rates
-
Use standard hardware
-
No CPU Overhead
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No forklift upgrades
-
Low management cost
Ease of Use
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Easy to manage & monitor
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Integration with orchestration layers for provisioning of logical volumes
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Storage access API – block is the common building block
Performance
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Leverage the full performance of your NVMe SSD at scale, over the network
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True convergence to ensure deterministic application performance – no noisy neighbors
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Leverage high IOPS, high bandwidth or mixed
