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SSDs are failing your applications!

Solid State Drives (SSDs) can deliver some impressive performance numbers. However, SSDs are increasingly struggling to keep pace with modern datacenter evolution and growth. Real-world, high-performance workloads (such as transactional databases, trading applications, artificial intelligence and machine learning (AI/ML), data mining/analytics, etc.) require higher capacities, improved application performance, extended endurance, and better economics.

SSDs are failing your applications. If not right now, then likely soon.

A recent 451 Research Voice of the Enterprise survey reports that data is growing 28% annually, but the budget for on-premises storage is only growing at 16%. 

SSD capacities are a fixed size, but applications and edge devices are generating more data. SSDs lacks the flexibility to evolve as workloads change and grow. This means each server needs more SSDs, or more servers are needed to hold more SSDs.

  • Modern applications need to drive more compute against the data, but the intelligence to do so is constrained to the burdened server CPU. Application latency is critical to a positive user experience, but insufficient application performance may impact Service Level Agreements (SLAs) and successful business outcomes.
  • SSD flash is consumable and has a finite number of writes. High write workloads accelerate flash consumption, resulting in SSDs wearing faster than their associated server refresh cycles.
  • Data center space and power are at a premium. Every incremental SSD and server requires additional power and cooling, which is already limited. Assuming, of course, that you are able to purchase the required equipment in time to address project timelines and ongoing data growth. Scaling out is an unsustainable plan without moving to a larger data center.

We are asking too much of our server CPUs, instead of migrating workloads to where they are better addressed. The successful shift to domain-specific processing is evident with Graphics Processing Units (GPUs) for AI/ML, and on Smart Network Interface Cards (SmartNICs) for making data center networking efficient and flexible. The next domain to benefit from this shift is SSD flash storage.

Enter ScaleFlux Computational Storage

ScaleFlux Computational Storage incorporates processing capability directly on the SSD to transparently address insufficient capacity, poor SSD endurance, slowing application performance, and datacenter infrastructure sprawl.

  • Flash storage optimized processing transparently compresses the data as it is written, and seamlessly uncompresses the data as it is read, all while offloading precious CPU cycles. Because of this transparent, in-line compression, ScaleFlux intelligent SSDs can be configured to store up to 4x their physical capacity.
  • When you write less data to flash storage, the flash storage lives longer. ScaleFlux intelligent SSDs leverage variable length mapping and write aggregation to further extend endurance without adversely impacting performance or capacity.
  • Flash storage can be written to, and read from, very quickly. But not at the same time. Writing less data to the flash storage, and writing it less often, provides for more read opportunities. In real-world mixed-use workloads, this results in higher overall IOPS, increased application performance, exceeded application SLAs, and happier users.
  • With a 75% reduction in server SSDs, and higher server CPU performance, the datacenter can do exponentially more with less components to efficiently address critical business needs. A smaller footprint means less power consumption, less cooling, and a higher work unit per watt.

No more compromises!

The data on the SSD is now the source of datacenter optimization, with zero application changes. The high-performance ScaleFlux intelligent NVMe SSDs result in increased capacity and endurance, higher application performance, and a lower overall cost per gigabyte (GB) of storage.

Are your applications impacted by explosive data growth? Are you experiencing SSD performance or capacity challenges? If so, please share your experience in the comments.

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