Posts Tagged ‘cloud’

Dispelling Common Misperceptions About Cloud-Based Storage Architectures

As the media and entertainment industry moves to 4K resolution and virtual/augmented content formats, the storage and archive requirements for media content has grown exponentially. But while storage requirements continue to skyrocket, industry revenue has not grown accordingly – and M&E organizations are finding themselves challenged to “do more with less.” More organizations are looking to leverage the cost efficiencies, scalability and flexibility that cloud storage can offer, but many remain apprehensive about taking the plunge.

To be clear, in this post when we talk about “the cloud,” we’re talking cloud architectures, versus the public cloud provided by vendors such as Microsoft, AWS and Google, among others. Unlike public clouds, cloud architectures can be used completely within your facility if desired and they are designed with infinite scalability and ease of access in mind.

There are a number of misperceptions about moving data to cloud architectures that are (wait for it) clouding people’s judgment. It’s time we busted some of the bigger myths and misperceptions out there about cloud storage.

Myth #1: I’ll have to learn a whole new interface – false! Dell EMC’s Elastic Cloud Storage (ECS) employs a tiered system, where it sits under a file system – in our case, Isilon. For organizations already deploying Isilon SAN or NAS storage platforms, the workflows stay exactly as they were, as does users’ interface to the file system.

This tiered approach helps companies to “do more with less” by allowing them to free up primary storage and consolidate resources. By tiering down “cold,” inactive data to ECS, you can better optimize your tier-one higher performance storage and drive down costs.

Myth #2: My data won’t be safe in the cloud – false! ECS features a geo-efficient architecture that stores, distributes and protects data both locally and geographically, eliminating any single point of failure and providing a seamless failover from site to site with no impact to business. Further, even though the data within ECS is distributed, it’s still a secure, private environment so users won’t run into scenarios where anyone can access information without the right credentials.

Myth #3: Collaboration and access is going to be negatively impacted – false! If you look at the VFX industry, for example, teams are frequently spread across the world and working across time zones on a 24/7 basis. ECS enables global teams to work on the same piece of data at the same time from one system – it’s true collaboration. ECS’s multi-site, active-active architecture and universal accessibility enables anywhere access to content from any application or device.

Myth #4: Moving to the cloud is an all-or-nothing approach – false! ECS can be deployed when your organization is ready for it – whether that’s in a month, or six months, or a year. We realize a lot of operations personnel like to “see” their data and know first-hand that it’s there. We get that. But as things evolve, it’s likely that organizations will face pressure to take at least some of the data offsite. With ECS, you can still keep your data in the data center and, when the time is right to take your data off-site, Dell EMC can work with your organization to move your infrastructure to a hosted facility or a co-lo where you can continue to access your data just as you did when it was on-premise. ECS is available in a variety of form factors that can be deployed and expanded incrementally, so you can choose the right size for your immediate needs and project growth.

Because it is designed with “limitless scale” in mind, ECS eliminates concerns and worries of running out of storage, it can meet the needs for today’s M&E organizations, as well as those in the future simply by adding additional storage, just as you used to do with tapes.

Hopefully we’ve been able to bust a few of the myths around adopting a cloud-based storage architecture. This video featuring Dell EMC’s Tom Burns and Manuvir Das can offer additional insight into ECS’s tiered approach and how media organizations can begin seeing benefits from day one.

Stay current with Media & Entertainment industry trends here or listen to Broadcast Workflows webcast recording.

Why Healthcare IT Should Abandon Data Storage Islands and Take the Plunge into Data Lakes

One of the most significant technology-related challenges in the modern era is managing data growth. As healthcare organizations leverage new data-generating technology, and as medical record retention requirements evolve, the exponential rise in data (already growing at 48 percent each year according to the Dell EMC Digital Universe Study) could span decades.

Let’s start by first examining the factors contributing to the healthcare data deluge:

  • Longer legal retention times for medical records – in some cases up to the lifetime of the patient.
  • Digitization of healthcare and new digitized diagnostics workflows such as digital pathology, clinical next-generation sequencing, digital breast tomosynthesis, surgical documentation and sleep study videos.
  • With more digital images to store and manage, there is also an increased need for bigger picture archive and communication system (PACS) or vendor-neutral archive (VNA) deployments.
  • Finally, more people are having these digitized medical tests, (especially given the large aging population) resulting in a higher number of yearly studies with increased data sizes.

Healthcare organizations also face frequent and complex storage migrations, rising operational costs, storage inefficiencies, limited scalability, increasing management complexity and storage tiering issues caused by storage silo sprawl.

Another challenge is the growing demand to understand and utilize unstructured clinical data. To mine this data, a storage infrastructure is necessary that supports the in-place analytics required for better patient insights and the evolution of healthcare that enables precision medicine.

Isolated Islands Aren’t Always Idyllic When It Comes to Data

The way that healthcare IT has approached data storage infrastructure historically hasn’t been ideal to begin with, and it certainly doesn’t set up healthcare organizations for success in the future.

Traditionally, when adding new digital diagnostic tools, healthcare organizations provided a dedicated storage infrastructure for each application or diagnostic discipline. For example, to deal with the growing storage requirements of digitized X-rays, an organization will create a new storage system solely for the radiology department. As a result, isolated storage siloes, or data islands, must be individually managed, making processes and infrastructure complicated and expensive to operate and scale.

Isolated siloes further undermine IT goals by increasing the cost of data management and compounding the complexity of performing analytics, which may require multiple copies of large amounts of data copied into another dedicated storage infrastructure that can’t be shared with other workflows. Even the process of creating these silos is involved and expensive because tech refreshes require migrating medical data to new storage. Each migration, typically performed every three to five years, is labor-intensive and complicated. Frequent migrations not only strain resources, but take IT staff away from projects aimed at modernizing the organization, improving patient care and increasing revenue.

Further, silos make it difficult for healthcare providers to search data and analyze information, preventing them from gaining the insights they need for better patient care. Healthcare providers are also looking to tap potentially important medical data from Internet-connected medical devices or personal technologies such as wireless activity trackers. If healthcare organizations are to remain successful in a highly regulated and increasingly competitive, consolidated and patient-centered market, they need a simplified, scalable data management strategy.

Simplify and Consolidate Healthcare Data Management with Data Lakes

The key to modern healthcare data management is to employ a strategy that simplifies storage infrastructure and storage management and supports multiple current and future workflows simultaneously. A Dell EMC healthcare data lake, for example, leverages scale-out storage to house data for clinical and non-clinical workloads across departmental boundaries. Such healthcare data lakes reduce the number of storage silos a hospital uses and eliminate the need for data migrations. This type of storage scales on the fly without downtime, addressing IT scalability and performance issues and providing native file and next-generation access methods.

Healthcare data lake storage can also:

  • Eliminate storage inefficiencies and reduce costs by automatically moving data that can be archived to denser, more cost-effective storage tiers.
  • Allow healthcare IT to expand into private, hybrid or public clouds, enabling IT to leverage cloud economies by creating storage pools for object storage.
  • Offer long-term data retention without the security risks and giving up data sovereignty of the public cloud; the same cloud expansion can be utilized for next-generation use cases such as healthcare IoT.
  • Enable precision medicine and better patient insights by fostering advanced analytics across all unstructured data, such as digitized pathology, radiology, cardiology and genomics data.
  • Reduce data management costs and complexities through automation, and scale capacity and performance on demand without downtime.
  • Eliminate storage migration projects.

 

The greatest technical challenge facing today’s healthcare organizations is the ability to effectively leverage and manage data. However, by employing a healthcare data management strategy that replaces siloed storage with a Dell EMC healthcare data lake, healthcare organizations will be better prepared to meet the requirements of today’s and tomorrow’s next-generation infrastructure and usher in advanced analytics and new storage access methods.

 

Get your fill of news, resources and videos on the Dell EMC Emerging Technologies Healthcare Resource Page

 

 

Using a World Wide Herd (WWH) to Advance Disease Discovery and Treatment

Patricia Florissi

Vice President & Global Chief Technology Officer, Sales at Dell EMC
Patricia Florissi is Vice President and Global Chief Technology Officer (CTO) for Sales. As Global CTO for Sales, Patricia helps define mid and long term technology strategy, representing the needs of the broader EMC ecosystem in EMC strategic initiatives. Patricia is an EMC Distinguished Engineer, holds a Ph. D. in Computer Science from Columbia University in New York, graduated valedictorian with an MBA at the Stern Business School in New York University, and has a Master's and a Bachelor's Degree in Computer Science from the Universidade Federal de Pernambuco, in Brazil. Patricia holds multiple patents, and has published extensively in periodicals including Computer Networks and IEEE Proceedings.

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Analysis of very large genomic datasets has the potential to radically alter the way we keep people healthy. Whether it is quickly identifying the cause of a new infectious outbreak to prevent its spread or personalizing a treatment based on a patient’s genetic variants to knock out a stubborn disease, modern Big Data analytics has a major role to play.

By leveraging cloud, Apache™ Hadoop®, next-generation sequencers, and other technologies, life scientists potentially have a new, very powerful way to conduct innovative global-scale collaborative genomic analysis research that has not been possible before. With the right approach, there are great benefits that can be realized.

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To illustrate the possibilities and benefits of using coordinated worldwide genomic analysis, Dell EMC partnered with researchers at Ben-Gurion University of the Negev (BGU) to develop a global data analytics environment that spans across multiple clouds. This environment lets life sciences organizations analyze data from multiple heterogeneous sources while preserving privacy and security. The work conducted by this collaboration simulated a scenario that might be used by researchers and public health organizations to identify the early onset of outbreaks of infectious diseases. The approach could also help uncover new combinations of virulence factors that may characterize new diseases. Additionally, the methods used have applicability to new drug discovery and translational and personalized medicine.

 

Expanding on past accomplishments

In 2003, SARS (severe acute respiratory syndrome) was the first infectious outbreak where fast global collaborative genomic analysis was used to identify the cause of a disease. The effort was carried out by researchers in the U.S. and Canada who decoded the genome of the coronavirus to prove it was the cause of SARS.

The Dell EMC and BGU simulated disease detection and identification scenario makes use of technological developments (the much lower cost of sequencing, the availability of greater computing power, the use of cloud for data sharing, etc.) to address some of the shortcomings of past efforts and enhance the outcome.

Specifically, some diseases are caused by the combination of virulence factors. They may all be present in one pathogen or across several pathogens in the same biome. There can also be geographical variations. This makes it very hard to identified root causes of a disease when pathogens are analyzed in isolation as has been the case in the past.

Addressing these issues requires sequencing entire micro-biomes from many samples gathered worldwide. The computational requirements for such an approach are enormous. A single facility would need a compute and storage infrastructure on a par with major government research labs or national supercomputing centers.

Dell EMC and BGU simulated a scenario of distributed sequencing centers scattered worldwide, where each center sequences entire micro-biome samples. Each center analyzes the sequence reads generated against a set of known virulence factors. This is done to detect the combination of these factors causing diseases, allowing for near-real time diagnostic analysis and targeted treatment.

To carry out these operations in the different centers, Dell EMC extended the Hadoop framework to orchestrate distributed and parallel computation across clusters scattered worldwide. This pushed computation as close as possible to the source of data, leveraging the principle of data locality at world-wide scale, while preserving data privacy.

Since one Hadoop instance is represented by a single elephant, Dell EMC concluded that a set of Hadoop instances, scattered across the world, but working in tandem formed a World Wide Herd or WWH. This is the name Dell EMC has given to its Hadoop extensions.

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Using WWH, Dell EMC wrote a distributed application where each one of a set of collaborating sequence centers calculates a profile of the virulence factors present in each of the micro-biome it sequenced and sends just these profiles to a center selected to do the global computation.

That center would then use bi-clustering to uncover common patterns of virulence factors among subsets of micro-biomes that could have been originally sampled in any part of the world.

This approach could allow researchers and public health organizations to potentially identify the early onset of outbreaks and also uncover new combinations of virulence factors that may characterize new diseases.

There are several biological advantages to this approach. The approach eliminates the time required to isolate a specific pathogen for analysis and for re-assembling the genomes of the individual microorganisms. Sequencing the entire biome lets researchers identify known and unknown combinations of virulence factors. And collecting samples independently world-wide helps ensure the detection of variants.

On the compute side, the approach uses local processing power to perform the biome sequence analysis. This reduces the need for a large centralized HPC environment. Additionally, the method overcomes the matter of data diversity. It can support all data sources and any data formats.

This investigative approach could be used as a next-generation outbreak surveillance system. It allows collaboration where different geographically dispersed groups simultaneously investigate different variants of a new disease. In addition, the WWH architecture has great applicability to pharmaceutical industry R&D efforts, which increasingly relies on a multi-disciplinary approach where geographically dispersed groups investigate different aspects of a disease or drug target using a wide variety of analysis algorithms on share data.

 

Learn more about modern genomic Big Data analytics

 

 

Solving the Video Vortex at the Secured Cities Conference

Gary Buonacorsi

CTO of State and Local Government at Dell EMC

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I’m in Houston today at the Secured Cities conference, the leading government security and public safety event, to participate on the “Video Vortex Drives Public Safety to the Datacenter” panel. I’ll be joined by Kenneth Baker, director of Infrastructure Support at the Metropolitan Transit Authority of Harris County (METRO), who recently helped implement a citywide video surveillance system for the bus and trolley service. I’m looking forward to hearing more about METRO’s specific architecture, the pain points and challenges the department faced and what problems it hopes to solve with the new system.

For those of you unable to join us in the “Space City” of Houston, here’s a glimpse of what I’ll be covering in the session:

 

What is driving the increase in data for state and local government? 

drroneOne key factor is the emergence of new surveillance technology, such as drones, body cameras, license plate trackers and audio/video recognizance. In particular, drone usage in the public safety arena has seen significant growth for providing situational awareness in tactical events such as bank robberies or hostage situations. In addition to tactical operations, drones are also being used around the country for policing activities. Pilot programs are popping up in cities like Modesto, California, where law enforcement is using drones to assist with search warrants and surveying crime scenes. The sky’s the limit for drone usage in law enforcement, as evidenced by Amazon patenting a voice-activated shoulder-mounted drone earlier this month that officers can use to help assess dangerous situations.

Secondly, resolution requirements are increasing. Grainy pictures are ineffectual when it comes to facial recognition, analytics and post-evaluation, forcing the transition from standard definition to 4K. As new tools and analytics are posed, resolution requirements are much higher.

Perhaps the most common reason for the increase in data for public safety organizations is the growing number of camera counts and longer video retention times. With the rise of citywide surveillance, cities such as London and New York City are moving towards having cameras on practically every street corner. Discovery activities in legal proceedings are extending the retention period and the chain of evidence storage requirements.

 

Given this exponential data growth, how is it impacting organizations and what do they need to focus on?

IT departments at these organizations should look for architectures that are open source, scalable and enterprise-ready to integrate with the system they currently have, in addition to any changes they may make in the future. Simply put, department heads should avoid spot solutions and instead adopt an integrated, strategic approach to help plan for the years ahead. I would counsel them to look for a solution that allows them to start small but grow big, and easily add more cameras and scale without disrupting the current environment.

The next major area to consider is life cycle management. Previously, video footage was kept for a week before it was written over or deleted. Now long term archiving is critical with the potential for courts to mandate digital assets such as video evidence in a capital case to be maintained indefinitely.

Organizations must embrace the shift to an enterprise model. For police departments, having body cameras isn’t enough. They must consider how to integrate them into dashboard cameras, 911 call centers, etc., taking each of these point solutions to form an enterprise approach.

 

Which platform will support retention policies and what are the three different storage architectures? How can organizations escape the video vortex?
cloud2Early video surveillance solutions presented a host of challenges, including restricting departments to certain file and storage protocols, and communication channels. Combine those factors with non IP-based cameras, and modernizing existing systems became extremely difficult. The first step for organizations to solve the video vortex is to select an open platform that not only allows them to migrate and move data from system to system, but that enables them to shift providers easily. Open platforms also present more options in terms of analytics and security, enabling departments to apply more traditional security tools on top of their data storage and data transportation needs.

Compute and data storage is the key element to eliminating the video vortex. Storage is the foundation layer of a sound architecture and must address the needs of an organization, including scaling, enterprise approach and open platform to avoid a lock-in. Currently, three storage architectures exist today: distributed, centralized and cloud. Police forces that are relatively small typically still rely on a distributed architecture, capturing the data from their cars and body cameras and physically transporting it back from a mobile storage device to a centralized repository where it can then be analyzed and managed. Distributed architectures can be folded into centralized architectures, allowing them to be part of the enterprise approach with a centralized location like police headquarters, schools, airports or the METRO. A centralized architecture makes it possible to gather all of these remote data feeds from their video surveillance solutions and bring them back to a centralized repository. In a case like this, the architecture must be efficient, storing only essential data to minimize utilization rates and costs. It must also be capable of supporting thousands of surveillance devices in order to scale to multiple distributed architectures that are coming back to one location.

The third architecture to consider is cloud. Cloud presents a useful solution in that it is elastic, scalable, expands very easily and can ramp up very quickly. However, cloud storage can be very costly in light of the potential retention policy changes, data sets and cloud size – all of a sudden, the portability of those cloud data sets become much more complex. From an architecture perspective, organizations must consider how to bridge that gap and determine the amount of data that can be returned to a more cost-effective on-premise solution without compromising the capabilities that cloud offers.

Finally, distributed, centralized and cloud platforms all underlie the data lake architecture, which is really the foundation for evidence management and helps solve the video vortex public safety organizations are facing.

Embrace Digital Transformation with Elastic Cloud Storage (ECS) 3.0

Sam Grocott

Senior Vice President, Marketing & Product Management at EMC ETD

Digital Transformation is drastically changing the business landscape, and the effects are being felt in every industry, and every region of the world. For some, the goal of this transformation is to use technology to leapfrog the competition by offering innovative products and services. For others, the focus is on avoiding disruption from new market entrants. Whatever your situation might be, it’s clear that you can’t ignore the change. In a recent study by Dell Technologies, 78% of global businesses surveyed believe that digital start-ups will pose a threat to their organization, while almost half (45%) fear they may become obsolete in the next three to five years due to competition from digital-born start-ups. These numbers are a stark indication of the pressure that business leaders are feeling to adapt or fall by the wayside.

But for IT leaders, this raises an uncomfortable question: Where will you find the money to make this transformation? You’re already under constant pressure to lower IT costs. How can you invest in new technologies while still doing this?

Elastic Cloud Storage (ECS), Dell EMC’s object storage platform, was built to help organizations with precisely this challenge. After being in market for just under two years, the latest release, ECS 3.0 is being announced at Dell EMC World today. ECS is a next-generation storage platform that simplifies storage and management of your unstructured data, increases your agility, and most importantly, lowers your costs. Let’s take a look at some of the ways ECS can help modernize your datacenter, clearing the way for you to embrace Digital Transformation.

Simplify and Accelerate Cloud-Native Development

The success of companies like Uber and AirBnB has highlighted the transformative power of “cloud native” mobile and web apps. Enterprises everywhere are taking note – in the previously mentioned Dell Technologies survey, 72% of companies indicated that they are expanding their software development capabilities. Often, these software development efforts are directed towards “cloud-native” applications designed for the web and mobile devices.

ECS is designed for cloud-native applications that utilize the S3 protocol (or other REST-based APIs like OpenStack Swift). ECS natively performs many functions like geo-distribution, ensuring strong data consistency and data protection, freeing up application developers to focus on what moves their business forward. This greatly increases developer productivity, and reduces the time to market for new applications that can unlock greater customer satisfaction, as well as new sources of revenue.

Reduce storage TCO and complexity

Legacy storage systems that sit in most enterprise datacenters are struggling to keep up with the explosion in unstructured data. Primary storage platforms are constantly running out of capacity, and it is expensive to store infrequently accessed data on these platforms. Additionally, as many businesses operate on a global scale, data coming in from different corners of the world ends up forming silos, which increase management complexity and lower agility in responding to business needs.
ECS is compatible with a wide range of cloud-enabled tiering solutions for Dell EMC primary storage resources like VMAX, VNX, Isilon and Data Domain.  Additionally, ECS is certified on many 3rd party tiering solutions, which enable it to act as a low cost, global cloud-tier for 3rd party storage platforms. These solutions drive up primary storage efficiency and drive down cost by accessing a lower cost tier with ECS. Tiering to ECS is friction-free, which means that apps or users accessing primary storage don’t have to change any behavior at all.

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Tape Replacement

The new ECS dense compute rack D-series increases storage density by more than 60%, making it an ideal replacement for tape archives. The D-Series comes as an eight node system that provides the highest density configurations for ECS at 4.5PB (D-4500) and 6.2PB (D-6200) in a single rack.

These new configurations provide the low cost and scalability benefits of traditional tape solutions, but without the lack of agility, poor reliability, and operational difficulties associated with storing data on tape.  Additionally, ECS makes business data available to BUs in an on-demand fashion. This allows organizations to fully embrace Digital Transformation, which relies on insights mined from business data to create more compelling experiences for customers.

Legacy application modernization

ECS can serve as an ideal storage platform for organizations looking to modernize legacy LoB applications that utilize or generate a large amount of unstructured data. Modifying legacy apps to point to ECS using the S3 (or other REST-based APIs like OpenStack Swift) protocol can help reduce costs, simplify maintenance of the application, and allow them to scale to handle massive amounts of data.

Take the Next Step

Learn more about how ECS can enable your transformation , follow @DellEMCECS on Twitter, or try it out – for free!

 

 

IACP: Body Cam Storage Success

Ken Mills

CTO Surveillance & Security

Latest posts by Ken Mills (see all)

Marking the 123rd IACP with Tips to Make Selecting On-Premise Body Cam Storage & Management as Easy as 1, 2, 3

We’re excited to attend the IACP Annual Conference and Exposition in San Diego this week on Oct. 15-18. Each year, thousands of dedicated professionals from federal, state, county, local and tribal agencies attend IACP to learn about the newest intelligence, strategies and tech solutions available to blog1law enforcement.

Among the topics likely to attract attention and spark discussions are body cams and the importance of gathering electronic evidence. With an overwhelming 99 percent of public safety experts agreeing that video surveillance technology will play a significant role in their ability to prevent crime, theft and terrorism over the next five years, it’s more critical than ever to ensure we’re utilizing video data to its potential.

The increase in video data means there is a massive potential for enhanced situational awareness and better intelligence – but only if the data is analyzed.

In honor of the IACP’s 123rd year, we’re sharing tips to help make selecting on-premise body cam storage and management as easy as 1, 2, 3.

1. Beyond Body Cams

While body cams are certainly getting their share of coverage lately, it’s important to remember body cams are just one component of the video data that public safety departments are tasked with managing. Today’s public safety environments also consist of video, surveillance cameras, drones, in-car video, mobile devices and more. Progressive public safety departments must build a data platform that can collect, store and manage these individual pools of data. A common infrastructure provides a more cost-effective storage environment, more control of the data and better security.

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2. Costly Clouds

Last month, the Associated Press reported police departments in Indiana and Kentucky have halted the use of body cams, citing new laws that would require the video to be stored longer and thereby significantly increasing the cost. On average, each body cam requires a minimum of 1TB of storage per year. Competing cloud solutions charge over $1,400/year – per camera. For a police department that has 500 body cameras, that can quickly add up, with the cost of storage for body cams totaling approximately $700,000 annually in perpetuity. Department heads trying to maintain budgets and plan for additional personnel to monitor the data should consider alternative storage solutions that cost considerably less to deploy and provide an overall better total cost of ownership.

3. Open to New Solutions

Open platform enables departments to integrate body cam data with the best available industry applications. To avoid the risk of limiting video to a single company’s platform, departments should bypass a closed solution as it may prevent other key applications gaining access to that data. Because the video world is constantly changing, an open platform will enable departments to implement the best solutions today and tomorrow.

Read more about our storage solutions here or visit us at Booth 820 and Booth 5307 at IACP. We look forward to seeing you there!

 

 

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