Meet The CEO: MemVerge’s Charles Fan
Workloads like artificial intelligence (AI), machine learning (ML), big data analytics, the Internet of Things (IoT) and data warehousing need storage memory-levels of performance. Charles Fan, CEO of...
View ArticleTop Four Data Analytics Challenges – Challenge 2: Technical Expertise
The new era of data analytics has opened up a new opportunity for storage professionals to become strategic partners and advisers to line of business stakeholders. The problem is that completing...
View ArticleFor All-Flash Performance, Hardware vs. Media
In recent years the industry has seen the evolution of flash media from Serial Attached SCSI (SAS) and Serial Advanced Technology Attachment (SATA) based interconnects to Peripheral Component...
View ArticleFlash Memory Summit 2019 – Day 1
Storage Switzerland is at the 2019 edition of the Flash Memory Summit (FMS). Each day of the summit, we will be providing a quick summary of our meetings. Day 1 was a busy day for StorageSwiss as we...
View ArticleFlash Memory Summit 2019 Day 2 – Western Digital
Our second day at Flash Memory Summit (FMS) 2019 was another jam-packed day. Western Digital’s activities before and at the event are so extensive that we’ve broken them out into a full detailed...
View ArticleDeveloping an NVMe over Fibre Channel Strategy
Most All-Flash Arrays (AFA) are setup as block devices connected via a Fibre Channel (FC) Storage Area Network (SAN). The deterministic nature of FC and its inherent low latency are an ideal match for...
View ArticleFlash Second – Getting Data Analytics Ready for Flash Storage
Accelerating a data analytics project is critical for storage vendors that sell storage systems designed for big data analytics, artificial intelligence (AI), and machine learning (ML). These vendors...
View ArticleIs it Time to Rethink NAS for Unstructured Data?
Network Attached Storage (NAS) systems were once the primary storage destination for all unstructured data but with file-counts soaring past one billion and with machines replacing users as the primary...
View ArticleIs Your Storage Architecture Ready for the Coming AI Wave?
Artificial Intelligence (AI) is a broad term that can apply to various computing tasks, including machine learning, deep learning, and big data analytics. Many AI projects are in a proof of concept...
View ArticleDisaster Recovery Workshop: Dealing with New Requirements, Expectations, and...
Disaster Recovery (DR) is changing, and DR plans need to change with it. Legislative bodies want companies to not only prove their ability to recover from a disaster, but they have specific guidelines...
View ArticleUnderstanding the Challenges That AI at Scale Creates
Artificial Intelligence (AI) is in its infancy and the requirements it places on the storage architectures that support these workloads are not widely understood. As a result, an organization starting...
View ArticleVirtual Instruments Briefing Note – Virtana Announcement
The data center, in most cases, is a mixture of legacy and modern applications that exist, both on-premises and in the cloud. To provide organizations with a competitive advantage, IT needs to use and...
View ArticleIs Your Storage Ready for the Data-Driven Economy? – SwiftStack Briefing Note
Organizations need to re-think their storage architectures for the data-driven economy. How an organization captures, stores, and analyzes data, can dictate how successful it might be in this new...
View ArticleLightboard Video: The Art of Big and Fast Data
Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) projects can all have varying types of data associated with them. Some projects consist of a relatively small number of huge...
View ArticleCan Current Storage Infrastructure Meet the AI at Scale Demand?
In our last blog we covered the challenges that AI at scale creates for storage infrastructures. To support the coming wave of AI applications, storage infrastructures need to deliver a tremendous...
View ArticleCan The Storage Infrastructure Keep Pace with Data Center Modernization?
The modern data center is increasingly microservice or container-based. These workloads are dynamic and unpredictable. The datasets within these workloads range from thousands of large files to...
View ArticleAre All-Flash Arrays All Wrong for AI and DL Workloads?
When designing a storage infrastructure for an artificial intelligence (AI) or deep learning (DL) workload, the default assumption is that an all-flash array (AFA) or something even faster must be at...
View ArticleLive Webinar: Designing Storage Infrastructures for AI Workloads
Artificial Intelligence (AI) and Machine Learning (ML) workloads are fundamentally different from any other workload. These workloads deal in data sets measured in dozens of petabytes of capacity, and...
View ArticleStorageSwiss Report 64 – A Decade’s Worth of Predictions
The StorageSwiss Report is a weekly discussion about hot trends and topics going on in the storage, cloud, and data protection markets. We don’t just cut & paste press releases. We provide insight...
View ArticleThe Requirements of AI at Scale Storage Infrastructures
Artificial Intelligence (AI) at scale raises the bar for storage infrastructure in terms of capacity and performance. It is not uncommon for an AI or machine learning (ML) environment to expect growth...
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