|By Clive Cook||
|December 10, 2009 04:00 PM EST||
CIOs and IT managers agree that memory is emerging as a critical resource constraint in the data center for both economic and operational reasons. Regardless of density, memory is not a shareable resource across the data center. In fact, new servers are often purchased to increase memory capacity, rather than to add compute power. While storage capacity and CPU performance have advanced geometrically over time, memory density and storage performance have not kept pace. Data center architects refresh servers every few years, over-provision memory and storage, and are forced to bear the costs of the associated space, power and management overhead. The result of this inefficiency has been high data center costs with marginal performance improvement.
Memory: Where Are We?
Business-critical applications demand high performance from all network resources to derive value out of the ever-increasing volume of data. Memory is one of the three key computing resources, along with CPU and storage, which determine overall data center performance. However, memory has lagged far behind the advances of both processors and storage in capacity, price, and performance ratios. While processor vendors assert that data centers are processor-bound and storage vendors imply that data centers are storage-bound, in many cases the true performance barrier is memory. To that end, both a major network vendor and a dominant server vendor have recently made announcements about dramatic increases in the memory footprint of servers to better support data center virtualization.
The major network vendor built their first-ever blade server with custom developed hardware to support a larger memory footprint (up to 384 GB) for one dual-processor blade. This is significantly larger than the 144 GB maximum that is typical in high-end systems. The dominant server vendor enables individual VMs to use more of the local system memory.
Memory constraints continue to impact application performance for a number of industries. For example, data for seismic processing of oil and gas extraction, flight and reservation information, or business analytics quickly add up to terabytes, much too large to fit in even large-scale (and expensive) local RAM. These growing data sets create huge performance slowdowns in applications where latency and throughput matter. Multi-core processors are underutilized, waiting for data they can't get fast enough. And, currently available solutions are inefficient and don't entirely solve the problem.
Latency, or the delay in delivering the initial piece of data, is critical to application performance in areas such as manufacturing, pharmaceuticals, energy, and capital markets. As an example, algorithmic traders can execute hundreds of thousands of trades per day. Twenty-five percent of securities trades are now algorithmic trades - trades initiated by computers in response to market conditions or trading in patterns and sequences that generate profits. These trades leverage trade execution speed to make money, and it's a race to performance. The fastest trading desks will profit most.
Alongside the significant impact of peak performance is the need for certified messaging. Trading data streams must be certified - reliably stored for record keeping and rollback. Current solutions to the trading message problem are difficult to integrate, expensive, and cannot meet the performance requirements of the algorithmic trading desk.
A leading vendor's message bus solution has transaction latencies in the millisecond range, and reaches maximum throughput at close to 5,000 transactions per second. This performance hampers algorithmic trading, and throughput is not enough to meet the peak trading volumes at the opening bell, closing bell, or during market-moving events.
Memory Virtualization - Breaking the Memory Barrier
The introduction of memory virtualization shatters a long-standing and tolerated assumption in data processing - that servers are restricted to the memory that is physically installed. Until now, the data center has been primarily focused on server virtualization and storage virtualization.
Memory virtualization is the key to overcoming physical memory limitations, a common bottleneck in information technology performance. This technology allows servers in the data center to share a common, aggregated pool of memory that lives between the application and operating system. Memory virtualization is logically decoupled from local physical machines and made available to any connected computer as a global network resource.
This technology dramatically changes the price and performance model of the data center by bringing the performance benefits of resource virtualization, while reducing infrastructure costs.
In addition, it eliminates the need for changes to applications in order to take advantage of the pool. This creates a very large memory resource that is much faster than local or networked storage.
Memory virtualization scales across commodity hardware, takes advantage of existing data center equipment, and is implemented without application changes to deliver unmatched transactional throughput. High-performance computing now exists in the enterprise data center on commodity equipment, reducing capital and operational costs.
Memory Virtualization in Action - Large Working Data Set Applications
Memory virtualization reduces hundreds to thousands of reads from storage or databases to one, by making frequently read data available in a cache of virtualized memory with microsecond access speeds. This decreases reliance on expensive load balancers and allows servers to perform optimally even with simple, inexpensive round-robin load balancing by linking into common file system calls or application-level API integration. Any server may contribute RAM into the cache by using a command-line interface or a configuration and management dashboard that sets up and controls the virtualized memory pool through a web-based user interface. Memory virtualization then uses native high-speed fabric integration to move data rapidly between servers.
For applications with large working data sets, larger than will fit in physical memory, such as those found in high-volume Internet, predictive analytics, HPC and oil and gas, memory virtualization brings faster results and improves end-user experiences. In capital markets, memory virtualization delivers the lowest trade execution latencies, includes certified messaging, and integrates simply as demanded in this competitive market.
The associated performance gains relative to traditional storage are huge. NWChem is a computational chemistry application typically deployed in an HPC environment. In a 4 node cluster with a 4 GB / node running NWChem, memory virtualization cut the test run time from 17 minutes down to 6 minutes 15 seconds with no additional hardware, simply by creating an 8 GB cache with 2 GB contributed from each node.
Alternatives Fall Short
Attempts to address these challenges include scaling out (adding servers), over-provisioning (adding more storage or memory than is needed), scaling up (adding memory to existing or larger servers), or even designing software around the current constraints.
Larger data centers draw more power and require more IT staff and maintenance. For example, a 16-server data center with 32 GB RAM/server costs $190,000 in capital and operational expense over two years. Scaling out that data center to 32 servers would double the cost to $375,000 (see Figure 1). Scaling up the servers to 64GB RAM/server would raise the cost to $279,000 (data center costs based on the cost of scaling up a 16-node cluster from 32GB to 64GB per server, and scaling out a 16-node cluster to 32-nodes, two years operational expense).
What does this investment buy you? You get more servers to work on the problem - but performance has not improved significantly because they aren't working together; each server is still working only with its own local memory. By trying to divide and conquer your data set, you've fragmented it. Like fragmented drives, fragmented data sets restrict the flow of data and force data to be replicated across the network. The overhead of drawing data into each server consumes resources that should be focused on one thing - application performance.
By sharing memory, data centers require less memory per server because they have access to a much larger pool of virtualized memory. Memory virtualization also enables fewer servers to accomplish the same level of application performance, meaning less rack space, power consumption, and management staff (see Figure 2).
Additional cache capacity can be added dynamically with no downtime, and application servers can easily connect to virtualized network memory to share and consume data at any time without re-provisioning.
High Availability features eliminate data loss when servers or networks go down by keeping multiple copies of data in the cache and employing persistent writes to comply with certified messaging standards.
In the storage area, SAN and NAS have decoupled storage from computing, but storage is not the place for the active working data set. Storage acceleration can only marginally improve application performance because it connects too far down the stack and is not application-aware (understands state). The millisecond latencies of storage requests are unacceptable bottlenecks for business and mission-critical applications.
In some cases, data center architects have turned to data grids in the search for performance. Data grids impose a high management overhead and performance load and tend to replicate the working data set, rather than truly share it. These solutions are difficult to integrate, debug, and optimize, and remain tightly coupled to your application, reducing flexibility. Architects who have implemented these solutions complain of the "black box" software to which they have tied their applications' performance and disappointing acceleration results.
Memory virtualization has solved the key barrier to increasing the efficiency of existing network resources in order to improve the performance of business-critical applications. This capability decouples the memory from its physical environment, making it a shared resource across the data center or cluster. Addressing today's IT performance challenges, virtualized memory enables new business computing scenarios by eliminating application bottlenecks associated with memory and data sharing. Currently available, memory virtualization is delivering optimized data center utilization, performance and reliability with minimum risk and immediate business results.
"ReadyTalk is an audio and web video conferencing provider. We've really come to embrace WebRTC as the platform for our future of technology," explained Dan Cunningham, CTO of ReadyTalk, in this SYS-CON.tv interview at WebRTC Summit at 19th Cloud Expo, held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA.
Dec. 5, 2016 08:15 AM EST Reads: 437
We are always online. We access our data, our finances, work, and various services on the Internet. But we live in a congested world of information in which the roads were built two decades ago. The quest for better, faster Internet routing has been around for a decade, but nobody solved this problem. We’ve seen band-aid approaches like CDNs that attack a niche's slice of static content part of the Internet, but that’s it. It does not address the dynamic services-based Internet of today. It does...
Dec. 5, 2016 07:30 AM EST Reads: 970
In his keynote at 18th Cloud Expo, Andrew Keys, Co-Founder of ConsenSys Enterprise, provided an overview of the evolution of the Internet and the Database and the future of their combination – the Blockchain. Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life sett...
Dec. 5, 2016 07:30 AM EST Reads: 7,038
The WebRTC Summit New York, to be held June 6-8, 2017, at the Javits Center in New York City, NY, announces that its Call for Papers is now open. Topics include all aspects of improving IT delivery by eliminating waste through automated business models leveraging cloud technologies. WebRTC Summit is co-located with 20th International Cloud Expo and @ThingsExpo. WebRTC is the future of browser-to-browser communications, and continues to make inroads into the traditional, difficult, plug-in web ...
Dec. 5, 2016 07:15 AM EST Reads: 1,252
20th Cloud Expo, taking place June 6-8, 2017, at the Javits Center in New York City, NY, will feature technical sessions from a rock star conference faculty and the leading industry players in the world. Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud strategy.
Dec. 5, 2016 06:45 AM EST Reads: 1,793
WebRTC is the future of browser-to-browser communications, and continues to make inroads into the traditional, difficult, plug-in web communications world. The 6th WebRTC Summit continues our tradition of delivering the latest and greatest presentations within the world of WebRTC. Topics include voice calling, video chat, P2P file sharing, and use cases that have already leveraged the power and convenience of WebRTC.
Dec. 5, 2016 06:45 AM EST Reads: 1,594
"We're a cybersecurity firm that specializes in engineering security solutions both at the software and hardware level. Security cannot be an after-the-fact afterthought, which is what it's become," stated Richard Blech, Chief Executive Officer at Secure Channels, in this SYS-CON.tv interview at @ThingsExpo, held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA.
Dec. 5, 2016 06:30 AM EST Reads: 719
The Internet of Things (IoT) promises to simplify and streamline our lives by automating routine tasks that distract us from our goals. This promise is based on the ubiquitous deployment of smart, connected devices that link everything from industrial control systems to automobiles to refrigerators. Unfortunately, comparatively few of the devices currently deployed have been developed with an eye toward security, and as the DDoS attacks of late October 2016 have demonstrated, this oversight can ...
Dec. 5, 2016 06:15 AM EST Reads: 884
Fact is, enterprises have significant legacy voice infrastructure that’s costly to replace with pure IP solutions. How can we bring this analog infrastructure into our shiny new cloud applications? There are proven methods to bind both legacy voice applications and traditional PSTN audio into cloud-based applications and services at a carrier scale. Some of the most successful implementations leverage WebRTC, WebSockets, SIP and other open source technologies. In his session at @ThingsExpo, Da...
Dec. 5, 2016 06:00 AM EST Reads: 1,678
Internet-of-Things discussions can end up either going down the consumer gadget rabbit hole or focused on the sort of data logging that industrial manufacturers have been doing forever. However, in fact, companies today are already using IoT data both to optimize their operational technology and to improve the experience of customer interactions in novel ways. In his session at @ThingsExpo, Gordon Haff, Red Hat Technology Evangelist, will share examples from a wide range of industries – includin...
Dec. 5, 2016 04:15 AM EST Reads: 1,617
We're entering the post-smartphone era, where wearable gadgets from watches and fitness bands to glasses and health aids will power the next technological revolution. With mass adoption of wearable devices comes a new data ecosystem that must be protected. Wearables open new pathways that facilitate the tracking, sharing and storing of consumers’ personal health, location and daily activity data. Consumers have some idea of the data these devices capture, but most don’t realize how revealing and...
Dec. 5, 2016 04:00 AM EST Reads: 5,122
Unless your company can spend a lot of money on new technology, re-engineering your environment and hiring a comprehensive cybersecurity team, you will most likely move to the cloud or seek external service partnerships. In his session at 18th Cloud Expo, Darren Guccione, CEO of Keeper Security, revealed what you need to know when it comes to encryption in the cloud.
Dec. 5, 2016 04:00 AM EST Reads: 4,705
"We build IoT infrastructure products - when you have to integrate different devices, different systems and cloud you have to build an application to do that but we eliminate the need to build an application. Our products can integrate any device, any system, any cloud regardless of protocol," explained Peter Jung, Chief Product Officer at Pulzze Systems, in this SYS-CON.tv interview at @ThingsExpo, held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA.
Dec. 5, 2016 03:30 AM EST Reads: 944
In his general session at 19th Cloud Expo, Manish Dixit, VP of Product and Engineering at Dice, discussed how Dice leverages data insights and tools to help both tech professionals and recruiters better understand how skills relate to each other and which skills are in high demand using interactive visualizations and salary indicator tools to maximize earning potential. Manish Dixit is VP of Product and Engineering at Dice. As the leader of the Product, Engineering and Data Sciences team at D...
Dec. 5, 2016 01:30 AM EST Reads: 771
Data is the fuel that drives the machine learning algorithmic engines and ultimately provides the business value. In his session at 20th Cloud Expo, Ed Featherston, director/senior enterprise architect at Collaborative Consulting, will discuss the key considerations around quality, volume, timeliness, and pedigree that must be dealt with in order to properly fuel that engine.
Dec. 5, 2016 12:45 AM EST Reads: 1,576
In addition to all the benefits, IoT is also bringing new kind of customer experience challenges - cars that unlock themselves, thermostats turning houses into saunas and baby video monitors broadcasting over the internet. This list can only increase because while IoT services should be intuitive and simple to use, the delivery ecosystem is a myriad of potential problems as IoT explodes complexity. So finding a performance issue is like finding the proverbial needle in the haystack.
Dec. 5, 2016 12:30 AM EST Reads: 6,099
According to Forrester Research, every business will become either a digital predator or digital prey by 2020. To avoid demise, organizations must rapidly create new sources of value in their end-to-end customer experiences. True digital predators also must break down information and process silos and extend digital transformation initiatives to empower employees with the digital resources needed to win, serve, and retain customers.
Dec. 5, 2016 12:15 AM EST Reads: 1,168
"Once customers get a year into their IoT deployments, they start to realize that they may have been shortsighted in the ways they built out their deployment and the key thing I see a lot of people looking at is - how can I take equipment data, pull it back in an IoT solution and show it in a dashboard," stated Dave McCarthy, Director of Products at Bsquare Corporation, in this SYS-CON.tv interview at @ThingsExpo, held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA.
Dec. 4, 2016 10:45 PM EST Reads: 1,011
@GonzalezCarmen has been ranked the Number One Influencer and @ThingsExpo has been named the Number One Brand in the “M2M 2016: Top 100 Influencers and Brands” by Onalytica. Onalytica analyzed tweets over the last 6 months mentioning the keywords M2M OR “Machine to Machine.” They then identified the top 100 most influential brands and individuals leading the discussion on Twitter.
Dec. 4, 2016 06:30 PM EST Reads: 2,042
Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more business becomes digital the more stakeholders are interested in this data including how it relates to business. Some of these people have never used a monitoring tool before. They have a question on their mind like “How is my application doing” but no id...
Dec. 4, 2016 06:30 PM EST Reads: 2,187