Over the past few years, to reduce cost and to improve time-to-value, converged infrastructure systems – the integration of compute, networking and storage - have been readily adopted by large enterprise users. The success of these systems results from the deployment of purpose built integrated converged infrastructure optimized for the most common IT workloads like Private Cloud, Big Data, Virtualization, Database and Desktop Virtualization (VDI). Traditionally these converged infrastructure systems have been built using a three-tier architecture; where compute, networking and storage, while integrated together in same rack, still consisted of best-in-breed standalone devices. These systems work well in stable, predictable environments, however, when a virtualization environment is dynamic with unpredictable growth, traditional three-tier architectures often times lack the simplicity, scalability and flexibility needed to operate in such environment.
Enter HyperConvergence, where the three-tier architecture has been collapsed into a single system that is purpose-built for virtualization from the ground up with virtualization, compute and storage, along with advanced features such as deduplication, compression and data protection, are all integrated into an x86 industry-standard building block node. These devices are built upon scale-out architectures with a 100% VM centric management paradigm. The simplicity, scalability and flexibility of this architecture make it a perfect fit for dynamic virtualized environments.
Dell XC Web-scale Converged Appliances powered by Nutanix software are delivered as a series of HyperConverged models that are extremely flexible and scalable. In this solution brief we will examine what constitutes a dynamic virtualized environment and how the Dell XC Web-scale Appliance series fits into such an environment. We can confidently state that by implementing Dell’s XC flexible range of Web-scale appliances, businesses can deploy solutions across a broad spectrum of virtualized workloads where flexibility, scalability and simplicity are critical requirements. Dell is an ideal partner to deliver Nutanix software because of its global reach, streamlined operations and enterprise systems solutions expertise. The company is well positioned to bring HyperConverged platforms to the masses and introduce the technology to a new set of customers previously unreached.
With the advent of server virtualization, many adopters erroneously think that disaster recovery (DR) is a problem of the past. They cite the ability of the hypervisors to replace the two most common yet imperfect DR choices: 1) infrastructure replication to a secondary replica site – fast to restore but very expensive, or 2) economical tape backup with off-site long-term storage – economical but slow to recover from.
The reality is that while server virtualization has certainly helped the industry get closer to simpler and less expensive DR products, DR still remains one of the major challenges for IT. This is especially true for applications that fall somewhere between the most mission critical where RTOs and RPOs of a few seconds is needed (and cost is often no object) and those that find RTOs and RPOs of a day or two to be adequate. Today, DR products available for these “intermediate” applications are few and far between, especially when overall cost of DR is considered.
The missing piece so far has been a cost-effective DR solution with excellent RTO and RPO for the majority of business applications -- without requiring a secondary site. OneCloud steps into the gap by replacing that expensive site with the hyper-scale public cloud. This Profile will discuss how OneCloud works to extend the primary data center onto the cloud, and how this impacts the ease and speed of VM recovery.
Every large IT shop has a long shelf of performance management solutions ranging from big platform bundles bought from legacy vendors, through general purpose log aggregators and event consoles, to a host of device-specific element managers. Despite the invested costs of acquiring, installing, supporting, and learning these often complex tools, only a few of them are in active daily use. Most are used only reactively and many just gather dust for a number of reasons. But, if only because of the ongoing costs of keeping management tools current, it’s only the solutions that get used that are worth having.
When it comes to picking which tool to use day-to-day, it’s not the theory of what it could do, it’s the actual value of what it does for the busy admin trying to focus on the tasks at-hand. And among the myriad of things an admin is responsible for, assuring performance requires the most management solution support. Performance related tasks include checking on the health of resources that the admin is responsible for, improving utilization, finding lurking or trending issues to attend to in order to head off disastrous problems later, working with other IT folks to diagnose and isolate service impacting issues, planning new activities, and communicating relevant insight to others – in IT, the broader business, and even to external stakeholders.
Admins responsible for infrastructure, when faced with these tasks, have huge challenges in large, heterogeneous, complex environments. While vendor-specific device and element managers drill into each piece of equipment, they help mostly with easily identifiable component failure. Both daily operational status and difficult infrastructure challenges involve looking across so-called IT domains (i.e. servers and storage) for thorny performance impacting trends or problems. The issue with larger platform tools is that they require a significant amount of installation, training, ongoing tool support, and data management that all detract from the time an admin can actually spend on primary responsibilities.
There is room for a new style of system management that is agile, insightful and empowering, and we think Galileo presents just such a compelling new approach. In this report we’ll explore some of the IT admin’s common performance challenges and then examine how Galileo Performance Explorer with its cloud-hosted collection and analysis helps conquer them. We’ll look at how Performance Explorer crosses IT domains to increase insight, easily implements and scales, fosters communication, and focuses on and enables the infrastructure admin to achieve daily operational excellence. We’ll also present a couple of real customer interviews in which, despite sunk costs in other solutions, adding Galileo to the data center quickly improved IT utilization, capacity planning, and the service levels delivered back to the business.
Within the past few months IBM announced a new member of its FlashSystem family of all-flash storage platforms – the IBM FlashSystem V840. FlashSystem V840 adds a rich set of storage virtualization features to the baseline FlashSystem 840 model. V840 combines two venerable technology heritages: the hardware hails from the long lineage of Texas Memory Systems flash storage arrays, and the storage services feature set for FlashSystem V840 is inherited from the IBM storage virtualization software that powers the SAN Volume Controller (SVC). One was created to deliver the highest performance out of flash technology and the other was a forerunner of what is being termed software defined storage. Together, these two technology streams represent decades of successful customer deployments in a wide variety of enterprise environments.
It is easy to be impressed with the performance and the tight integration of SVC functionality built into the FlashSystem V840. It is also easy to appreciate the wide variety of storage services built on top of SVC that are now an integral part of FlashSystem V840. But we believe the real impact of FlashSystem V840 is understood when one views how this product affects the cost of flash appliances, and more generally how this new cost profile will undoubtedly affect traditional data center architecture and deployment strategies. This Solution Profile will discuss how IBM FlashSystem V840 combines software-defined storage with the extreme performance of flash, and why the cost profile of this new product – equivalent essentially to current high performance disk storage – will have a major positive impact on data center storage architecture and the businesses that these data centers support.
Two big trends are driving IT today. One, of course, is big data. The growth in big data IT is tremendous, both in terms of data and in number of analytical apps developing in new architectures like Hadoop. The second is the well-documented long-term trend for critical resources like CPU and memory to get cheaper and denser over time. It seems a happy circumstance that these two trends accommodate each other to some extend; as data sets grow, resources are also growing. It's not surprising to see traditional scale-up databases with new in-memory options coming to the broader market for moderately-sized structured databases. What is not so obvious is that today an in-memory scale-out grid can cost-effectively accelerate both larger scale databases as well as those new big data analytical applications.
A robust in-memory distributed grid combines the speed of memory with massive horizontal scale-out and enterprise features previously reserved for disk-orienting systems. By transitioning data processing onto what's really now an in-memory data management platform, performance can be competitively accelerated across the board for all applications and all data types. For example, GridGain's In-Memory Computing Platform can functionally replace both slower disk-based SQL databases and accelerate unstructured big data processing to the point where formerly "batch" Hadoop-based apps can handle both streaming data and interactive analysis.
While IT shops may be generally familiar with traditional in-memory databases - and IT resource economics are shifting rapidly in favor of in-memory options - less known about how an in-memory approach is a game-changing enabler to big data efforts. In this report, we'll first briefly examine Hadoop and it's fundamental building blocks to see why high performance big data projects, those that are more interactive, real-time, streaming, and operationally focused have needed to continue to look for yet newer solutions. Then, much like the best in-memory database solutions, we'll see how GridGain's In-Memory Hadoop Accelerator can simply "plug-and-play" into Hadoop, immediately and transparently accelerating big data analysis by orders of magnitude. We'll finish by evaluating GridGain's enterprise robustness, performance and scalability, and consider how it enables a whole new set of competitive solutions unavailable over native databases and batch-style Hadoop.
All Flash Arrays (AFAs) are plentiful in the market. At one level all AFAs deliver phenomenal performance compared to an HDD array. But comparing AFAs to an HDD-based system is like comparing a Ford Focus to a Lamborghini. The comparison has to be inter-AFAs and when one looks under the hood one finds the AFAs in the market vary in performance, resiliency, consistency of performance, density, scalability and almost every dimension one can think of.
An AFA has to be viewed as a business transformation technology. A well-designed AFA, applied to the right applications will not only speed up application performance but by doing so enable you to make fundamental changes to your business. It may enable you to offer new services to your customers. Or serve your current customers faster and better. Or improve internal procedures in a way that improves employee morale and productivity. To not view an AFA through the business lens would be missing the point.
In this Product Profile we describe all the major criteria that should be used to evaluate AFAs and then look at Violin’s new entry, Concerto 7000 All Flash Array to see how it fares against these measures.