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  • Hadoop Distributed File System options for big data

    Because big data can scale to petabytes of capacity, organizations are looking to manage it in ways that are easier and less expensive than traditional scale-out NAS. Object storage and software-defined storage are frequently mentioned as big data tools. Both can add intelligence required for analyzing data and take advantage of low-cost disk storage.

    An object storage system handles files differently than a traditional file system. Servers use unique identifiers to find objects, which use metadata in a far more detailed way than file systems do. The unique identifiers mean objects can be geographically dispersed because they can be retrieved without the storage system knowing their physical location. That makes objects a good choice for large data stores or data stored in a cloud.

    Software-defined storage has many forms and use cases, but it applies to big data when used to pool and manage data across off-the-shelf commodity hardware. Because the management and analytics happen in software appliances, the hardware can be cheap, deep disk without bells and whistles.

    Perhaps the most well known option available is the Apache Hadoop Distributed File System (HDFS), which is a Java-based file system designed to be used in Hadoop clusters. HDFS currently scales to 200 petabytes and can support single Hadoop clusters of 4,000 nodes. It offers storage performance on a large scale and at a low cost, which is atypical of most enterprise arrays that cannot perform all three tasks simultaneously.

    In this chapter of "Tools to Tackle Big Data Troubles," we look at some core HDFS features, three HDFS commercial distributions and other Hadoop storage-related tools and their related applications.

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  • How hyper-converged infrastructure platforms support VDI

    Converged infrastructure gives IT shops the opportunity to buy their entire hardware stack -- storage, networking, compute and server virtualization -- in one SKU. They can also add a software management layer and tightly integrate those components with hyper-converged infrastructure (HCI). These all-in-one HCI platforms are ideal for virtual desktop infrastructure for several reasons: They take the guesswork out of buying hardware, they’re scalable, and shops know the pieces will work together because they're all from the same vendor. But with that simplicity comes some necessary back-end changes.

    In traditional companies, disparate teams manage the facets that get packaged into HCI. But with the management interface inherent to HCI, the need for bodies in the IT shop is sometimes diminished. It takes fewer people to manage fewer parts. Companies considering deploying VDI on hyper-converged infrastructure must think about the personnel, expertise and management requirements that come with the pod-style platforms. In some cases, HCI will be a boon for businesses looking to deploy or improve desktop virtualization. In other cases, it's not the right tool for the job.

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  • Which Amazon storage options balance performance and cost?

    Amazon Elastic Block Store volumes are offered as magnetic hard disk and solid-state drives. How should we use each storage type to ensure proper workload performance? Continue Reading

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  • Buyer's checklist to hybrid flash arrays

    All-flash arrays are a hot technology, but not everybody needs flash for all of their storage. Hybrid flash arrays can strike a balance between using flash for performance while keeping spinning disk drives to lower the price for less frequently accessed data. Flash storage offers blazing speed but at a high cost per gigabyte.

    At the other end of the spectrum, multi-terabyte hard disk drives (HDDs) are more economical, but they do not supply the raw IOPS per drive that some applications need. Hybrid flash arrays combining HDDs and a thin slice of flash storage can provide a performance boost and reduce latency while keeping costs in check. Although the difference between HDD prices and flash costs has narrowed considerably, many organizations still don't have the budget to deploy hundreds of terabytes of solid-state storage. Despite differences in architectures, the vendors generally agree on some hybrid vs. all-flash guidelines. If sub-millisecond latency or guaranteed quality of service (QoS) is required, then an all-flash array or a hybrid flash array that can deliver near all-flash performance is the way to go. But with variable and unpredictable workloads, hybrid flash arrays can often serve the need at a lower $/GB.

    Candidates for hybrid flash arrays include collaboration, email and any applications where data lifecycle issues mean that not all data requires immediate access.

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  • Flash appears as a viable hospital data storage option

    Healthcare facilities looking to boost their storage performance should be looking into flash, if they haven't invested in it already. Nicole Lewis, a contributor to SearchHealthIT, begins this handbook by describing how one hospital system converted to flash technology and subsequently experienced a noticeable improvement in clinical data processing. That increase in computing speed also helped the hospital system greatly shrink its physical storage setup and reduce the amount of time its employees take to complete financial reports.

    Next, contributor Brien Posey explains how facilities that practice telehealth should use flash for their hospital data storage needs. Telehealth is performed through videoconferencing, something that requires plenty of available network bandwidth. Poor storage performance can interfere with telehealth. That issue can be prevented with flash, Posey reasons.

    Lastly, Posey breaks down the deciding factors for organizations that are considering going entirely with flash or using a tiered approach for their hospital data storage.

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  • Four common AWS cloud migration mistakes

    With more than one million customers, AWS has convinced enterprises of all shapes, sizes and industries that its cloud can improve IT operations. But the move isn't always flawless. Continue Reading

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