Workloads such as high-performance transactional databases, high-volume analytics, artificial intelligence (AI) and machine learning (ML) stand to unlock new value for the business, and non-volatile memory express (NVMe) promises to deliver on these levels of performance. However, deploying NVMe at…
Storage Switzerland has previously discussed the problems that legacy storage file systems have when it comes to serving modern workloads such as artificial intelligence (AI) and high-velocity analytics. We have also explored the qualities that a modern file system requires.…
Previously, Storage Switzerland has discussed the value of computational storage, or adding compute power directly to storage media to enable data to be processed in place, in serving modern workloads – as well as its impact on future forward data…
Artificial intelligence (AI) is becoming solidified as an important tool for competitive advantage, used by organizations of all sizes and across industries. Legacy network-attached storage (NAS) systems, however, are not equipped to provide the levels of throughput that these workloads…
Storage Switzerland recently wrote about the need for enterprises to move away from using backup processes for long-term data retention use cases. Backup implementations add value in providing high availability and fast (or instant) recovery of the enterprise’s most critical…
Artificial Intelligence, Machine Learning and High Velocity Analytic workloads are going mainstream. Enterprises of all types and sizes want to seize the opportunity their data presents. As these workloads move from development to production, organizations face a significant challenge with…
Benchmarks are necessary when trying to understand the performance characteristics of a particular storage system in a particular environment. The problem is they are susceptible to manipulation by vendors to get the best marketing results. The Standard Performance Evaluation Corporation…
Migrating to the hybrid cloud stands to allow businesses to balance agility, cost, performance, and security requirements. However, the complexity of implementing a global management structure that accounts for all data and that gets that data where it needs to…
Our previous blog highlighted the challenges of supporting artificial intelligence (AI), machine learning (ML) and deep learning (DL) workloads with legacy file systems. Control node bottlenecks, inferior (or lack of) non-volatile memory express (NVMe) drivers, and inefficient capacity utilization are…
Artificial Intelligence workloads push current IT architectures to their extremes. For the first time both computing horsepower and All-Flash Storage I/O can be overwhelmed by AI demands. GPUs from companies like Nvidia have largely solved the computing problem but the…
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