In storage technology, data deduplication essentially refers to the elimination of redundant data. In the deduplication process, duplicate data is deleted, leaving only one copy of the data to be stored. However, indexing of all data is still retained should that data ever be required. Deduplication is able to reduce the required storage capacity since only the unique data is stored.
University of East Anglia wished to create a “green” HPC resource, increase compute power and support research across multiple operating systems. Platform HPC increased compute power from 9 to 21.5 teraflops, cut power consumption rates and costs and provided flexible, responsive support.
This book examines data storage and management challenges and explains software-defined storage, an innovative solution for high-performance, cost-effective storage using the IBM General Parallel File System (GPFS).
In any storage system it is essential to ensure that the integrity of the data stored is maintained so data can be recovered exactly as it was written. HP StoreOnce appliances have been designed with the necessary technology that delivers this essential high degree of data protection. HP has unique technology that protects data throughout its lifecycle when stored on the HP StoreOnce appliance. This paper will discuss the methods used at various stages to provide this high degree of data integrity.
With an estimated 1.8 million branch offices in the US, not only is critical data being dispersed across the enterprise, but also applications. Organizations have invested in monitoring tools to help assure network and application performance, but do these tools have the visibility across the network to deliver real-time insights?
A Gigamon Visibility Fabric™ solution can extend visibility wherever critical data may exist. It eliminates the need to facilitate resources for troubleshooting and the need to install monitoring tools at every remote site. By doing so, it simplifies IT operations and centralizes monitoring tools that can reduce OPEX and CAPEX.
Simplifying IT operations by centralizing monitoring tools and connecting them into a Gigamon Visibility Fabric™ can reduce OPEX and CAPEX. These monitoring tools include systems used for application performance management (APM), customer experience management (CEM), data loss prevention (DLP), deep packet inspection (DPI), intrusion detection systems (IDS), intrusion prevention systems (IPS), network performance management (NPM), network analysis, and packet capture devices. This white paper explains how this new approach to monitoring and management of IT infrastructure provides pervasive visibility across campus, branch, virtualized and, ultimately, SDN islands.
With critical data and applications dispersed across the enterprise, IT teams struggle to manage, analyze, and secure their networks. Even within a single location this can be a daunting task. Organizations have invested in monitoring tools to assure network and application performance, as well as security, but do these tools have the visibility across the network to deliver real-time insights?
A Gigamon Visibility Fabric™ solution can extend visibility wherever critical data may exist to address issues like oversubscription, tool proliferation, and TAP/SPAN port contention. By centralizing monitoring and simplifying IT, organizations are better able to manage, analyze, and secure the networks.
For remote office protection, you can reliably get a backup and a DR copy of data at any location without the need for onsite expertise. Read this paper to learn more about the next generation of deduplication.
The early days of the de-duplication target market could be characterized as the Wild West according to 451 Research, with a slew of startups shooting it out in an emerging market with tremendous potential.
Taking a more comprehensive, unified approach to managing data—recovering any data from a single console—can not only reduce your capital and operating costs, but can also provide enhanced application availability for improved IT service levels.