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Solving the Storage Problem

Solving the Data Storage Problem | @CloudExpo #IoT #Cloud #BigData #Storage |

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  • In his session at 20th Cloud Expo, Tom Eck, Industry Platforms CTO at IBM Cloud, will discuss how these tools simplify the time-consuming tasks of selection, mapping and data integration, allowing developers to use IBM services or combine them with their own data.
  • In his session at 20th Cloud Expo, Tom Eck, Industry Platforms CTO at IBM Cloud, will discuss how these tools simplify the time-consuming tasks of selection, mapping and data integration, allowing developers to use IBM services or combine them with their own data.
  • By mixing Cloud Foundry and the rich set of Watson services, IBM’s Bluemix is the best cloud operating system for enterprises today, providing rapid development and deployment of applications that can take advantage of the rich catalog of Watson services to help drive insights from the vast trove of private and public data available to enterprises.
  • By mixing Cloud Foundry and the rich set of Watson services, IBM’s Bluemix is the best cloud operating system for enterprises today, providing rapid development and deployment of applications that can take advantage of the rich catalog of Watson services to help drive insights from the vast trove of private and public data available to enterprises.

Cloud Computing

@DBaker007: Solving the Data Storage Problem | @CloudExpo #IoT #Cloud #BigData #Storage |

Web-scale IT is a pattern of global-class computing that delivers the capabilities of large cloud service providers within an enterprise IT setting by reimagining positions across several dimensions. The unprecedented explosion of Big Data and cloud services is driving the development of new storage architectures to store the information produced by this web-scale trend. It is becoming increasingly clear that even a linear growth trajectory for storage is insufficient to deliver the quantity of storage needed for data produced by the Internet of Things. Current architectures have bottlenecks that, while merely inconvenient for legacy data, are simply unacceptable for the scale of storage needed today.

In order to accommodate this unparalleled growth, enterprises are deploying web-scale architectures that enable virtualization, compute and storage functionality on a tremendous scale.

Overcoming Performance Issues

A bottleneck that functions as a single point of entry can become a single point of failure, especially with the demands of cloud computing on Big Data storage. A key element in web-scale storage design is its insistence on removing all bottlenecks from storage architecture. Adding redundant, expensive, high-performance components to alleviate the bottleneck, as most service providers presently do, adds cost and complexity to a system very quickly. On the other hand, a horizontally scalable web-scale system designed to distribute data among all nodes makes it possible to choose cheaper, lower-energy hardware.

Data bottlenecks and other performance issues are a significant challenge for cloud providers, which must manage far more users and greater performance demands than do enterprises. While the average user of an enterprise system demands high performance, these systems typically have fewer users, and those users can access their files directly through the local network. Furthermore, enterprise system users are typically accessing, sending and saving relatively low-volume files like document files and spreadsheets, using less storage capacity and alleviating performance load.

It’s another matter entirely for a cloud user outside the enterprise. The system is being accessed simultaneously over the Internet by an order of magnitude more users, which itself becomes a performance bottleneck. The cloud provider’s storage system not only has to scale to each additional user, but must also maintain performance across the aggregate of all users. Significantly, the average cloud user is accessing and storing far larger files – music, photo and video files – than does the average enterprise user. Web-scale architectures are designed to prevent the bottlenecks that this volume of usage causes in traditional legacy storage setups.

Built to Scale

Since hardware inevitably fails (at a number of points within the machine), traditional appliances – storage hardware that has proprietary software built in – typically include multiple copies of expensive components to anticipate and prevent failure. These extra layers of identical hardware extract higher costs in energy usage, and add layers of complication to a single appliance. It’s important, then, that web-scale architecture be built on software exclusively, with no reliance on hardware. Because the actual cost per appliance is quite high compared with commodity servers, cost estimates often skyrocket when companies begin examining how to scale out their data centers. One way to avoid this is by using software-defined vNAS or vSAN in a hypervisor environment, both of which offer a way to build out servers at a web-scale rate.

Distributed Resilience

Although centralization is the direction data centers have been moving in, distributed storage presents the best way to build at web-scale levels. This is because there are now ways to improve performance at the software level that neutralize the performance advantage of a centralized data storage approach.

The nature of cloud-based services is that they are accessible from anywhere in the world, so service providers must be able to offer data centers located across the globe to minimize load time. With global availability, however, come a number of challenges. Load is active in the data center in a company’s region. This creates a problem, since all data stored in all locations must be in sync. From an architecture point of view, it’s important to solve these problems at the storage layer instead of up at the application layer, where it becomes more difficult and complicated to solve.

If a local data center or server goes down, global data centers must reroute data quickly to available servers to minimize downtime. Global data centers must be resilient to localized disaster – such as a power outage – that puts a local server farm offline. While there are certainly solutions today that solve these problems, they do so at the application layer.  Attempting to solve these issues that high up in the hierarchy of data center infrastructure – instead of solving them at the storage level – presents significant cost and complexity disadvantages. Solving these issues directly at the storage level through web-scale architectures delivers significant benefits in efficiency, time and cost savings.

Equipped for the Future

The need for more storage is ever-increasing, and if companies continue to rely on expensive, inflexible appliances in their data centers, they will be forced to lay out significant funds to develop the storage capacity they need to meet customer needs.

Having an expansive, rigid network environment locked into configurations determined by an outside vendor severely curtails the ability of the organization to react nimbly to market demands, much less anticipate them in a proactive manner. Web-scale storage philosophies enable major enterprises to “future proof” their data centers. Since the hardware and the software are separate investments, either may be switched out to a better, more appropriate option as the market dictates, at minimal cost.

Web-Scale is the Future

There’s no question that organizations need new storage solutions to manage the deluge of data that modern technology generates; traditional architectures create bottlenecks that reduce performance, and the only remedy is to spend more and more money on additional components. However, new approaches like software-defined storage and hyper-converged infrastructures are enabling Internet service providers, major enterprises and global organizations to scale to huge compute environments with integrated virtualization components. The future of storage demands web-scale architecture.

Solving the Storage Problem

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