network storage

The media and entertainment industry was valued at $1.81 trillion in 2016, and is expected to reach $2.14 trillion by 2020. Activities within this industry have grown over the last couple of years, and now range from creating content for movies, TV and games, to delivering that content. This is increasingly performed via on-demand data networks rather than traditional over-the-air broadcasting, watched over high resolution displays that enhance the overall viewing experience of the user, and even the latter is being delivered from the same storage repositories. Media production is also now prevalent in areas not traditionally associated with this activity, such as training, museums, and education.

While flash storage can enhance the performance of your applications, there are three potential roadblocks to realizing the full value from a flash investment: • Storage network capacity • Storage architecture • Resiliency Vish Mulchand is Senior Director of Product Management and Marketing for Storage, Hewlett Packard Enterprise.

In an innovation-powered economy, ideas need to travel at the speed of thought. Yet even as our ability to communicate across companies and time zones grows rapidly, people remain frustrated by downtime and unanticipated delays across the increasingly complex grid of cloud-based infrastructure, data networks, storage systems, and servers that power our work.

In a Hyper-Converged Infrastructure, compute, networking, and shared storage are delivered from Dell 13G PowerEdge servers powered by Intel Xeon processors, which enables a pay-as-you-go, aff?ordable model to cost-effectively operate at high performance.

In an innovation-powered economy, ideas need to travel at the speed of thought. Yet even as our ability to communicate across companies and time zones grows rapidly, people remain frustrated by downtime and unanticipated delays across the increasingly complex grid of cloud-based infrastructure, data networks, storage systems, and servers that power our work.

Your online audience expects fast, flawless, secure experiences on any device in any location, every time. But whether you are delivering videos, your website, music, software or games, ensuring engaging online experiences from an increasing variety of devices around the world is a huge challenge. Content delivery networks (CDNs) can significantly improve the user experience of your online audiences. But not all CDNs deliver the same level of service. Dos and Don’ts of Evaluating and Deploying a CDN provides tips on how to determine what is most important to your organization and how to choose a CDN that meets your needs. Download this guide to learn: The four major performance factors that can affect user experience Why speed alone isn't an accurate measure of performance How a content audit can identify performance bottlenecks The role content storage can play in reducing costs and latency How to decide what features are most important to your business

In an innovation-powered economy, ideas need to travel at the speed of thought. Yet even as our ability to communicate across companies and time zones grows rapidly, people remain frustrated by downtime and unanticipated delays across the increasingly complex grid of cloud-based infrastructure, data networks, storage systems, and servers that power our work.

In ESG research conducted shortly after the announced acquisition of EMC by Dell, 65% of the respondents indicated that they expected to benefit from more complete and innovative solutions from the combined company. That’s not surprising, given the complementary strength of their respective portfolios. Perhaps the most potential synergy is in the Converged Platforms and Solutions division, where servers, networking, storage and software come together.

In order for enterprises and IT organizations to truly innovate and offer differentiated value to customers, you need an IT infrastructure based on the latest advancements in computing, networking, and storage. Considering an investment in flash storage or converged infrastructure? Read this brochure to learn more about the Vblock® System 540, the industry’s first all-flash Converged Infrastructure System for high-performance mixed workloads and emerging 3rd platform applications—built on best of breed technology components including EMC XtremIO all-flash storage. All of this with the VCE™ Experience of unmatched management and one-call support.

We invite you to join us for an information-packed, educational opportunity with the Dell Compellent-VMware virtualization team.

The ExtraHop Discovery Edition is a free virtual appliance will help you to discover the performance of your applications across the network, web, VDI, database, and storage tiers. Get yours today!

Cloud applications and web-based services, such photo sharing sites, create some monumental challenges for a storage infrastructure.

Scalability has always been an important characteristic of enterprise storage systems, maybe the most important, since the rationale of consolidating storage assumes that the system can easily grow with aggregate demand.

To meet the growing need for agility and flexibility, the data center components (compute, network and storage) also need to evolve and provide a level of automation and orchestration that can meet present and future demands.

Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly, and legacy storage systems are not keeping up. Advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics.

To find out how to simplify the virtualized network transforming multiple storage silos into a singular solution, watch our Webinar. Learn how network simplification solves data storage issues for optimized application performance.

With increasing demands being made on enterprise IT departments to keep up with the accelerating pace of business, infrastructure has to enable more dynamic, eficient application and IT service delivery. Unfortunately, more ofen than not, IT provisioning can be a bottleneck. Traditional means are ofen ineficient. When developers plan their projects and estimate the server, networking, and storage resources they need, they ofen overestimate and pad their requests to ensure what actually gets provisioned is adequate. The formal request comes via an IT ticket, and then the waiting begins. Days, possibly weeks go by before they get the resources they need, and all the while they’re unable to iterate on and evolve core business oferings.

As agencies continue to modernize data center infrastructure to meet evolving mission needs and technologies, they are turning to agile software and cloud solutions. One such solution is hyper-converged infrastructure (HCI), a melding of virtual compute, storage, and networking capabilities supported by commodity hardware. With data and applications growing exponentially along with the need for more storage capacity and flexibility, HCI helps offset the rising demands placed on government IT infrastructure. HCI also provides a foundation for hybrid cloud, helping agencies permanently move applications and workloads into public cloud and away from the data center.

Hybrid cloud architectures are growing in popularity as a way to cope with today's business needs. This paper outlines a framework and specific solutions for adopting a hybrid cloud architecture to support increased profits and productivity.

Data is growing at amazing rates and will continue this rapid rate of growth. New techniques in data processing and analytics including AI, machine and deep learning allow specially designed applications to not only analyze data but learn from the analysis and make predictions. Computer systems consisting of multi-core CPUs or GPUs using parallel processing and extremely fast networks are required to process the data. However, legacy storage solutions are based on architectures that are decades old, un-scalable and not well suited for the massive concurrency required by machine learning. Legacy storage is becoming a bottleneck in processing big data and a new storage technology is needed to meet data analytics performance needs.

Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Advanced AI applications require a modern all-fl ash storage infrastructure that is built specifically to work with high-powered analytics.

Rapid increases in network traffic volumes, security threats and application complexity all underscore the importance for lossless data capture, analysis and storage to provide crucial raw data for post event analysis and remediation. Viavi commissioned Tolly to evaluate the performance of its Observer GigaStor family of capture, analysis, and storage solutions. Specifically the tests that focuses on bench marking maximum sustained full packet capture/write rates and greatest burst performance with no packet loss while delivered robust encryption of stored network data.

In the new age of big data, applications are leveraging large farms of powerful servers and extremely fast networks to access petabytes of data served for everything from data analytics to scientific discovery to movie rendering. These new applications demand fast and efficient storage, which legacy solutions are no longer capable of providing.

FlashBlade fabric modules implement a unified network that connects all blades to each other and to the data center network. With full connectivity, all blades can serve as client connection endpoints, as authorities that process client requests, and as storage managers that transfer data to and from flash and NVRAM.

Advanced image analysis and computer vision are key components of today’s AI revolution and is becoming critical for a wide range of industry applications, including healthcare, where this technology is being used to detect anomalies and improve patient care. Due to a lack of integrated tools and experience with these cutting-edge technologies, however, deploying complete systems is difficult. Applications that utilize deep learning approaches often require large amounts of highly parallel compute power, storage, and networking capabilities, along with performance optimizations for faster data analysis. The Intel and QNAP/IEI solution combines all these elements in one complete system for scalable data management for hospitals and clinics of all sizes. Read more on Intel’s and QNAP/IEI’s real-world use case on macular degeneration analysis through high-performance computing, vision capabilities, storage, and networking in a single solution.