Is Your Data Center Cloud-Ready for Big Data?

2016/09/27 • Cloud, Feature • Views: 449

In the information age, data has permeated every industry and commercial enterprise.

Big Data is being mentioned more and more, perhaps trailing only the Internet of Things (IoT) and cloud computing in frequency, as a catchword in the IT sector. Big Data is nothing new to the government, finance, law enforcement, communications, transportation, healthcare, and media fields. It has only gained wide attention in recent years due to recent developments in the IT industry.

What do you need to make your cloud data center ready for Big Data?

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Big Data is a disruptive technology that came onto the scene shortly after cloud computing and the IoT. This new business accelerator is stirring things up, especially in the enterprise Data Center (DC). Conventional DC layouts cannot satisfy the processing or analysis requirements of Big Data, largely due to the sheer volume and complexity of the data being ingested.

These aging layouts are proving ineffective in handling the operational and transactional information in many organizations and the product, logistical, and other associated information needed for enterprises to stay on top in the information superhighway. The volumes of information are simply too much for many existing enterprise IT architectures to bear. This is true even before even mentioning the strain on compute capabilities from escalating requirements for real-time processing. Existing traditional layouts simply cannot keep up.

Enterprise IT builds must consider how to satisfy demands from rapid business growth and how to provide business departments with the IT services they need, when and how they need it. These considerations then warrant taking a close look at how to equip traditional DCs with the cloud resources needed to meet their requirements for the volume, velocity, and variety of information that has come to be known as Big Data.

Is your cloud data center ready to face a flood of data?

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Most enterprises that have their own DC are able to handle the requirements of their routine operations. Yet these same centers will be hard-pressed to keep up with the information processing, unified data and analytics, storage, computing, and data mining requirements of the Big Data era.

Text-based data from computers, mobile terminals, and similar devices typically make up the bulk of content being processed and stored at DCs. That dynamic is changing as data types are becoming much more varied. Video, voice, sensory, and just about any other imaginable avenue through which information is created today are adding to the mushrooming effect. Data, in all its forms, is being drilled down to improve production efficiency, analyze live events, improve production quality, and craft new business models. This means that much greater importance will be placed on how value is actually extracted from data, in contrast to traditional DC models that assigned premiums to storage capacity and archiving capabilities.

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Equally important, Big Data will also place significant requirements on real-time processing and ease of O&M. Enterprises want to make full use of all available data, produce real-time analysis reports, and have a clear picture of their business operations at all times to help them make the right decisions at any moment in time. Even short delays could seriously hinder departments from analyzing data in a timely manner and making correct decisions. Enterprises must consider how to ramp up their infrastructure to process and analyze data more effectively and improve O&M across all centers.

The direction of development for cloud data centers in the future

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The crux of addressing the challenges of the Big Data era in the data center will be on how to allow data to drive service developments. DC integrations must be able to respond to the actual requirements of business departments. Most existing structures simply cannot meet these needs.

The complexity of data requires DCs to be able to quickly respond to ever-changing business requirements. The question then becomes how to go about equipping the centers with the agility, security, reliability, and efficiency required to provide business departments with what they need. Huawei anticipates that the focus at the data center will turn to service models, which is precisely what is reflected in its data integration and cloud DC design concepts.

Fully converged cloud DCs will no longer be restricted to the singular capabilities of physical centers. The new era will combine the physical resources of all the enterprise’s DCs (even if there is only one center) into one overarching resource pool to improve cross-center management, resource scheduling, and disaster recovery. Important technologies in unifying the logic of all physical centers include the cloud operating system FusionSphere, which combines all resources into pools, the O&M management system ManageOne, which unifies resource management and scheduling across the entire DC or multiple DCs, and Layer 2-based SDN ultra-broadband networking and software-defined DCs. These and other technologies form the Virtual Data Center (VDC) layout with the following characteristics taking shape today.

1. Service agility: Unified and converged data resource pools enable different business systems to apply for resources as needed. The platform auto-deploys nodes to suit the various service requirements, achieving a new level in rapid provisioning of services.

2. Processing capabilities throughout the entire data life cycle: The unified data convergence platform provides data ingestion, storage, computing, and application capabilities throughout the entire lifecycle. Users can define the Hadoop Big Data components, relational databases (including Oracle, SQL Server, and MySQL), Extract-Transfer-Load (ETL) in data ingestion, and other elements according to the requirements of the various services systems running on their platform.

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3. Data convergence and smart analytics: Multiple systems, formats, domains, and types of data sources will all be converged onto unified storage, compute, and analysis platforms to allow for the free movement of data to meet service requirements. At-scale data convergence, further improved service availability, and enhanced office productivity with smart analytics able to extract more value from the data will provide the enterprise with the exact information it needs in a timely manner, while delivering full assurances in all areas from security to data management.

4. Live network applications: New data platforms adapt to the database requirements of the existing systems. Unified SQL and search, in addition to distributed Big Data gateways, ensure limited changes to existing systems. Data processing and analysis improves significantly, and service systems can handle much more data.

In the future, core data applications will help enterprises extract more commercial value from their data. Discovering how to apply Big Data and how to extract valuable information from massive amounts of data is of utmost importance. As such, enterprises should focus more on the potential value of their DC layout. With converged data platforms, enterprises can extract full value from their data and continuously optimize business processes at their centers to drive down management costs, make better informed decisions supported by data, and contribute to continued innovation and development at the enterprise.

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Download the White Papers, Case Studies and Free Trial of FusionSphere Foundation to learn more how Huawei Cloud Computing Platform helps Enterprise in Digital Transformation.

FusionSphere Foundation is a free version of Huawei FusionSphere, including FusionCompute and FusionManager, which provide server virtualization and cloud management capabilities. For a system with less than or equal to six physical CPUs, the Foundation Edition allows users to use FusionSphere free of charge permanently without any function restrictions.For a system with more than six physical CPUs, this edition allows users to use FusionSphere free of charge for up to 90 days without any function restrictions. After the trial period (90 days) expires, existing VMs in the system are still available. However, administrators can only query service data, and manage users, roles, and license files.

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