July 31, 2017 / 8:19 PM / 2 minutes ago BRIEF-Red Hat acquires Permabit assets 1 Min Read July 31 (Reuters) – Red Hat Inc * Red Hat acquires Permabit assets, eases barriers to cloud portability with data deduplication technology * Red Hat Inc – transaction is expected to have no material impact to Red Hat’s guidance for its second fiscal quarter ending Aug. 31, 2017 * Red Hat Inc – transaction is expected to have no material impact to Red Hat’s guidance for fiscal year ending Feb. 28, 2018 Source text for Eikon: Further company coverage: 0 : 0
[July 31, 2017] Red Hat Acquires Permabit Assets, Eases Barriers to Cloud Portability with Data Deduplication Technology
Red Hat ( News – Alert ), Inc. (NYSE: RHT), the world’s leading provider of open source solutions, today announced that it has acquired the assets and technology of Permabit Technology Corporation, a provider of software for data deduplication, compression and thin provisioning.
Red Hat, Inc. acquired the assets and technology of Permabit Technology Corporation, a provider of software for deduplication, compression and thin provisioning. With the addition of these capabilities to the world’s leading enterprise Linux platform, Red Hat Enterprise Linux, Red Hat will be able to better enable enterprise digital transformation through more efficient storage options. […]
You probably have already made a commitment to the cloud because it enables you to flexibly deliver IT resources more quickly and at a lower cost. IT buyers are steadily shifting towards cloud-first strategies where they can rapidly adapt to market dynamics as they are no longer bound by legacy IT constraints. Public, private, or hybrid clouds are choices every C-level executive is making today. Each are different — for example, public cloud is shared with other businesses to yield economies of scale in Amazon Web Services (AWS), Google, Microsoft, while private cloud is either on-premises or hosted by a public cloud provider. Hybrid is a mix of both approaches, with different workloads deployed in each based on need. IDC reports that clouds are rapidly evolving to become more trusted, more intelligent, and more specialized for particular industries and workloads.
The cloud’s raison d’être, regardless of the deployment model used, is its ability to deliver IT business agility, deployment flexibility, and elasticity. Cloud priorities today include moving more workloads to the cloud, optimizing existing cloud utilization, leveraging innovation, and enabling multi-cloud deployments.
As businesses deploy cloud infrastructures, they embrace efficiency techniques that have been developed and used by Amazon, Google, and Microsoft to control their public cloud data center costs. These companies deploy efficiency models that increase data density and reduce footprint requirements, while dropping operating costs for power and cooling. As these extremely efficient models are deployed, legacy purpose-built hardware is being replaced with software-defined data centers running on industry-standard servers
Software-defined data centers usher in new opportunities to maximize efficiency in software. One such feature, which is particularly effective and critical in cloud environments, is inline data reduction. In addition to the platforms and software efficiency of cloud, data reduction delivers a substantial impact on your business by reducing the amount of data stored. Data reduction chops the amount of storage consumed, increases data density further, and lowers the costs of data at rest and in flight over your networks. No matter which cloud deployment you use, data reduction delivers economic benefits that make the cloud business case more compelling.
If you are deploying in a public cloud
Every day new workloads are being deployed in public clouds. Worldwide public IT cloud service revenue in 2018 is predicted to be $127B. The economics that public cloud delivers are undeniable. Amazon, Google, and Microsoft growth in the public cloud is testament.
As you deploy a public cloud environment, consider that data reduction technology shrinks public cloud costs. For example, data reduction technology (deduplication and compression) typically cut capacity requirements of block storage in enterprise public cloud deployments by up to 85% (6:1). Take your cloud block storage bill, divide by 6, and that is the business case.
The following Amazon cloud deployment example employing data reduction demonstrates how data reduction delivers substantial savings:
If you provision 300 TB of General Purpose SSD storage for 12 hours per day over a 30-day month in a region that charges $0.10 per GB-month, you would be charged $15,000 for the storage.
With 6:1 data reduction, that monthly cost of $15,000 would be reduced to $2,500. Over a 12 month period you will save $150,000.
Bottom line, data reduction reduces costs of public cloud deployments.
If you are deploying in a private cloud environment
Organizations see similar benefits when they deploy data reduction in private clouds. IDCpredicts$17.2B in infrastructure spending for private cloud in 2017. This demand reflects requirements for cloud’s increased efficiency, flexibility, privacy, performance, and security.
The business case for data reduction in private cloud is based on reducing the cost of both storage hardware and excessive annual software licensing. For example, Software-Defined Storage (SDS) solutions are typically licensed by capacity and their costs are directly proportional to storage device expenses. Data reduction decreases storage costs because it reduces storage consumption, as demonstrated in the following example:
You deploy a private cloud configuration with 1 PB of storage infrastructure and SDS. Assuming a current hardware cost of $500 per TB for commodity server-based storage infrastructure with datacenter-class SSDs and a cost of $56,000 per 512 TB for the SDS component, you would pay $612,000 in the first year. In addition, annual software subscriptions over three years cost $836,000 for 1 PB of storage and $1,060,000 over five years,.
In comparison, the same configuration with 6:1 data reduction over five years will cost $176,667 for hardware and software, resulting in $883,333 savings.
If you are deploying a hybrid cloud
Hybrid cloud is the preferred cloud deployment approach today because it addresses data security concerns while still leveraging cloud efficiency. On-premises resources (private cloud) combined with colocation and multiple public clouds result in a highly redundant data environment. For example, IDC’s FutureScape report finds “Over 80% of enterprise IT organizations will commit to hybrid cloud architectures, encompassing multiple public cloud services, as well as private clouds by the end of 2017.” (IDC 259840)
One consideration is whether to depend on a single cloud storage provider, which can pose a significant risk to Service Level Agreement targets. Consider the widespread AWS S3 storage errors that occurred on February 28th 2017, where data was not available to clients for several hours. Businesses lost millions of dollars of revenue due to loss of data access. This highlighted requirements for a “Cloud of Clouds” approach where data is redundantly distributed across multiple clouds for data safety and near continuous accessibility. IDC forecasts that 85% of cloud deployments will be multi-cloud by 2018. Unfortunately, the Cloud of Clouds approach increases storage capacity cost (by having redundant copies in multiple clouds), and adds the networking cost to move and sync data between cloud deployments.
That’s where data reduction comes in, as demonstrated in the following example:
In hybrid cloud deployments where data is replicated to the participating clouds, data reduction multiplies capacity and cost savings. If three copies of the data are kept in three different clouds, three times as much data is saved and data movement between clouds to sync them can be costly.
Take the private cloud example above where data reduction drove down the costs of a 1 PB deployment to $176,667, resulting in $883,333 in savings over five years. If that PB of data is replicated in three different clouds, the savings would be multiplied by three times for a total savings of $2,649,999.
Data reduction described
One data reduction application that can readily be applied in public, private, and hybrid clouds is Permabit’s Virtual Disk Optimizer (VDO), a pre-packaged software solution that installs and deploys in minutes on Linux operating systems. Because it is deployed directly with Linux, it can be easily deployed in any public or private cloud today.
OS-based data reduction solutions such as Permabit VDO address public cloud, private cloud (including on-premises and hosted private clouds), and the bandwidth challenges faced in hybrid cloud environments. Data reduction can reduce storage requirements and network bandwidth consumption by as much as 85% (6:1 data reduction).
Data reduction solutions generally combine a number of techniques to reduce data footprint. For example, Permabit VDO applies three reduction techniques:
- Zero-block elimination uses pattern matching techniques to eliminate zero data blocks
- Inline Deduplication eliminates duplicate data blocks
- HIOPS Compression™ compresses the remaining data blocks
The graphic below visually demonstrates how simple data reduction really is and its impact on storing data.
Data reduction delivers compelling cost reduction that substantially improves the business case in every cloud deployment model. No matter which cloud approach you choose, the cost savings benefits from data reduction should not be ignored and must be a component of your cloud strategy.
IT professionals are finding that the future of IT infrastructure lies in the cloud. Data reduction technologies enable clouds — public, private, and hybrid — to deliver business agility and elasticity at the lowest possible cost, making cloud the deployment model of choice for IT infrastructure going forward.
A short, live, tutorial on the installation process for Permabit VDO on RHEL. This shows how quickly VDO can be installed on RHEL less than 5 minutes!
All of the buzz about containers is a bit surprising to many people who’ve watched operating system technology evolve over the years. After all, many of the core concepts behind running isolated applications on a shared OS has been around on UNIX for over 20 years. So what’s so exciting? Well, to understand the container revolution you first have to look at Virtual Machines (VMs) and their impact on the…
Data centers are pushing the boundaries of the possible, using new paradigms to operate efficiently in an environment that continually demands more power, more storage, more compute capacity… more everything. Operating efficiently and effectively in the land of “more” without more money requires increased data center optimization at all levels, including hardware and software, and even policies and procedures.
Although cloud computing, virtualization and hosted data centers are popular, most organizations still have at least part of their compute capacity in-house. According to a 451 Research survey of 1,200 IT professionals, 83 percent of North American enterprises maintain their own data centers. Only 17 percent have moved all IT operations to the cloud, and 49 percent use a hybrid model that integrates cloud or colocation hosts into their data center operations.
The same study says most data center budgets have remained stable, although the heavily regulated healthcare and finance sectors are increasing funding throughout data center operations. Among enterprises with growing budgets, most are investing in upgrades or retrofits to enable data center optimization and to support increased density.
As server density increases and the data center footprint shrinks, any gains may be taken up by the additional air handling and power equipment, including uninterruptable power supplies and power generators. In fact, data center energy usage is expected to increase by 81 percent by 2020, according to CIO magazine.
Often, identifying and decommissioning unused servers during a data center optimization project is a challenge, along with right-sizing provisioning.
Virtualization makes it easy to spin up resources as needed, but it also makes tracking those resources harder. The result is that unused servers may be running because no one is certain they’re not being used. A study by the Natural Resources Defense Council and Anthesis reports that up to 30 percent of servers are unused, but still running.
A similar principle extends to storage. While data deduplication (removing duplicate files) is widely used, over-crowded storage remains an issue for small to medium-sized enterprises (SMEs). Deduplication can free much-needed storage space. For example, data deduplication along with compression can shrink data storage consumption by up to 85%. This not only addresses the budget issues mentioned above but also helps with data density much like the server density mentioned earlier. Imagine that you can save money with less storage and increase your data density at the same time . Looks lie a win-win!
If data center optimization is concerned with saving money, managers also should examine their purchasing programs. NaviSite looked for cost efficiencies within volume projects and looked at large commodity items like cabinets, racks, cabling and plug strips eliminated middlemen whenever possible. For big purchases go directly to the manufacturers in China and seek innovative young technology vendors working with them to design specifications that significantly lower the price.
Data center optimization, clearly, extends beyond hardware to become a system-wide activity. It is the key to providing more power, more capacity and more storage without requiring more money.
* This article is quite long you may want to read the source article which can be found by clicking on the link below:
With the increased focus on virtualization and cost of operations; simplicity and convergence; and the cloud, enterprises are moving from traditional enterprise storage system to software-defined storage and cloud storage to provide cost effective real-time storage services. Therefore, it has been observed that traditional Enterprise Storage Systems market has declined over the past few years.
Most of the enterprises are implementing cloud based storage systems due to low cost and greater agility and it also observed that there are companies which follow the hybrid cloud strategy where traditional and cloud storage are used together. This approach fuel the demand for traditional enterprise storage system and cloud storage system where critical workloads can be managed securely.
Enterprises are seeking for more efficient storage systems, as increasing focus on digitization creates huge amount of data which fuel the demand for innovative storage solutions. It has been observed that smaller enterprises drive the cloud storage market and large enterprises drive hybrid approach storage.
A significant tool in containing storage costs in any cloud or hybrid cloud is the application of data reduction technology which can easily deploy in any cloud deployment. Permabit VDO delivers data reduction up to 85% in public, private or hybrid cloud.
Due to the rise in the volume of structured and unstructured data and the need to backup and archive the files at reduced costs also propel the market growth for enterprise storage systems.
By offering a better price and reducing infrastructure and management costs and providing the enhanced security features enterprise storage systems market witness with the growth in future.
Enterprise storage systems market is segmented on the basis of type of storage and regions.
Enterprise IT organizations use cloud architectures to rapidly deploy resources and lower costs. By incorporating data reduction technologies in their architectures, organizations will accelerate deployment and reduce IT expenditures, say experts at Permabit Technology Corporation .
Data reduction is ideal for use by today’s enterprises choosing cloud-based deployments. With data reduction, organizations increase their agility and reduce costs since the technology reduces the footprint of data in transit and at rest. When data reduction is deployed at the operating system level, it is applicable to use in public cloud services or deploy in a company’s own private cloud.
“Organizations are under pressure to deliver digital transformation while reducing IT costs and are looking more and more to cloud as an answer,” said Tom Cook, Permabit CEO. “Our Virtual Data Optimizer (VDO) is the best and easiest way to deploy data reduction in every cloud deployment model.”
Permabit VDO provides the three key data reduction technologies needed to maximize storage savings, including: thin provisioning, data deduplication and compression. Implemented as a driver for the Linux device mapper, VDO operates at the same level in the Linux kernel as core data management services such as virtualization, data protection and encryption. VDO data reduction “just-works” regardless of whether the storage layers above are providing object-, block-, compute- or file-based access.