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Monday, June 1st, 2015
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| 12:00p | Top 10 Data Center Stories of the Month: May 2015 Here are some of the most popular stories that ran on Data Center Knowledge in May. Amazon Piloting Tesla Batteries to Power Cloud Data Center – The Tesla energy storage systems are based on the powertrain architecture and components of Tesla electric vehicles. CoreOS Gives Up Control of Non-Docker Linux Container Standard – Becoming a more formalized open source project, the App Container (appc) community now has a governance policy and has added a trio of top software engineers that work on infrastructure at Google, Twitter, and Red Hat as “community maintainers.”  Facebook’s cold storage data center in Prineville, Oregon (Photo: Facebook) How Facebook Cut 75 Percent of Power It Needs to Store Your #tbt Photos – Two Facebook data centers designed and built specifically to store copies of all user photos and videos started serving production traffic. Because they were optimized from the ground up to act as “cold storage” data centers for a very specific function, Facebook was able to substantially reduce its data center energy consumption and use less expensive equipment for storage. Microsoft Investing In Submarine Cables In Support Of Cloud – etter connectivity helps Microsoft compete on cloud costs, as well as improves reliability, performance and resiliency worldwide. The investments also spur jobs and local economies.  Hibernia Express, a high-capacity subsea transatlantic cable, is expected to be ready for service in September 2015 (Image: Hibernia Networks) Google’s Wholesale Move To Cloud and Take On Security Make Cloud Apps Enterprise-Friendly – Google is reportedly moving all of its internal corporate applications to a cloud model. So far, 90 percent of Google’s corporate applications have migrated. With that shift to cloud comes a shift in the way the company approaches and thinks about security. Gone is the idea of the cordoned-off enterprise. QTS Buys Government Cloud Heavyweight Carpathia for $326M – Growing its government cloud business has been a major focus for QTS in recent years. The acquisition will strengthen that part of the strategy and enhance overall geographic footprint and variety of services the Overland Park, Kansas-based company can provide. vXchnge Buys Eight Sungard Facilities in Edge Data Center Markets – vXchnge expands its edge data center footprint while Sungard AS frees up capital to invest into other cities. The data centers largely house colocation customers, according to Sungard AS. HP Lets Loose Horde of New Servers – Many of the management concepts and constructs that were originally developed for blade servers are now being applied to traditional rack servers, which one day may lead to a unification of at least how different server platforms get managed across the data center.  Wearable technology will turn data center workers into walking, talking encyclopedias of data center knowledge, according to Compass CEO Chris Crosby. (Image: Compass Datacenters) Compass Bringing Wearable Technology to the Data Center – The company is outfitting data center workers with a combination of high-tech visors and other key technology that steers them through maintenance and other standard operating procedures. Microsoft Intros Azure Stack for Private Data Centers – Unlike home versions of game shows, Azure Stack is the real thing: customers can run the same technology behind Microsoft’s public cloud offering in their own private data center. Stay current on data center news by subscribing to our daily email updates and RSS feed, or by following us onTwitter,Facebook, LinkedIn and Google+. |
| 3:00p | Catchpoint Adds On-Prem Capabilities to IT Monitoring Software As IT by definition becomes more distributed, it naturally becomes more complex to manage. To enable IT organizations to rise to that challenge, Catchpoint Systems announced an implementation of its IT monitoring software that can now be deployed on-premise. Originally developed to monitor applications and systems deployed in the cloud, Catchpoint CEO Mehdi Daoudi says, the software is now extending its reach out to local data center environments. The thing that differentiates Catchpoint most, he says, is that the company has invested heavily in reducing the number of false alarms that most IT monitoring tools generate. “There’s no way to completely eliminate false positives,” says Daoudi. “But we’ve done a lot more work than everybody else to minimize them.” That effort means internal IT staff don’t wind up ignoring all the alerts generated by the IT monitoring system because they can differentiate between what is potentially a serious situation and noise being generated by the system. IT organizations can define alerts based on the timing, content, code, network health, and availability. Alerts can be based on static thresholds, dynamic historical values, or detection of trend shifts so you can be notified the moment things start to slow down. Issues can be escalated of different members of the team with “warning” and “critical” thresholds. The alerts themselves can be sent via email, SMS or the Catchpoint Alert Push API. Based on a NoSQL database developed by Catchpoint, all the data collected by Catchpoint is stored in tis raw form. The company than applies an analytics engine to help correlate all the data residing in that database. Daoudi says Catchpoint OnPrem Agent enables IT organizations to run multiple tests simultaneously and store up to three years of raw data for historical analysis. The OnPrem Agent runs all synthetic tests now available on Catchpoint’s existing service. That capability is key, says Daoudi, because it enables IT organizations to slice and dice data in multiple ways to better discover the source of a particular problem using a NoSQL database designed to handle the massive amounts of Big Data generated by IT systems. Longer-term, according to him, IT organizations are unlikely to move every application into the cloud. As a result, Daoudi says, IT monitoring tools need to be applied across multiple hybrid cloud computing environments. Via Catchpoint, IT organizations now have the ability to use the same core technology to do both. |
| 3:30p | Hadoop and Big Data Storage: The Challenge of Overcoming the Science Project – Part II Andy Warfield is the CTO and Co-founder of Coho Data. This is Part II of the two-part series. You can read Part I here. Big data is a big opportunity. However, in talking to both large enterprises and big data distribution companies over the past year, I was surprised to learn exactly how nascent these technologies are. Many large enterprise IT organizations are faced with the challenge of tracking a proliferation of small, ad hoc analytics clusters, or of having to plan for a larger central deployment with mixed technology requirements across multiple stakeholders. While many believe there is untapped value to be had through harnessing their unstructured data, the path to a toolset that is as reliable, scalable and integrated as the rest of their enterprise IT environment is far from clear. So how do we get there? This isn’t simply a matter of choosing an appropriate big data distribution. The fluidity of big data software stacks and the hands-on nature of development practices are not going to change any time soon. In the face of this fluidity, what needs to change in order to support big data workflows in production IT environments? How can we help big data projects succeed and continue to succeed in the face of growth, evolution and disruptive events? Big Data’s Infrastructure Problems Need Infrastructure SolutionsIt’s fine that part of the job description of a big data developer or data scientist is the ability to adapt and work with new tools. However, a Wall Street bank or global healthcare firm isn’t in the business of experimenting with new and potentially fragile software tools as part of core IT. An infrastructure solution for big data must allow the diversity of tools that developers need to be deployed. It must also meet the efficiency, reliability and security requirements they have for the rest of their data. In short, it’s time for analytics environments to be brought into the fold, instead of being treated as a totally separate silo. Unfortunately, the incorporation of big data into traditional IT has proven more difficult than anyone anticipated. This is because the compute and IO requirements of big data systems are significantly different than what traditional enterprise systems have been designed to support. The Storage TussleProbably the biggest mismatch between traditional enterprise IT and big data centers on storage. Enterprise storage companies use space-efficient techniques to protect data from device data without wasting space with extra copies. HDFS defaults to keeping three copies of each file, and stores them on local disks within the compute nodes themselves. These copies aren’t just for durability: they provide flexibility in scheduling compute jobs close to data. For years, traditional storage companies have tried to sell in to big data environments only to be defeated by this aspect of architecture: the narrowness of connectivity into a network-attached storage controller goes completely against HDFS’s architecture for scaling out I/O connectivity in conjunction with compute. But there’s a counterpoint to this concern. As much as big data vendors would like to position HDFS as a “big data hub,” the file system falls far short of traditional enterprise storage on many counts. In fact, HDFS is not designed as a traditional file system at all. It doesn’t support the modification of existing files and the file system also struggles to scale beyond a million objects. However, more than all of this, HDFS lacks the rich set of data services that we have become accustomed to with enterprise storage systems, including things like snapshots, replication for disaster recovery and tiering across layers of performance. A really big change is taking place on this front right now. Big data distributions and enterprise storage vendors alike are starting to acknowledge that HDFS is really more of a protocol than a file system. Several traditional enterprise storage vendors have announced support for direct HDFS protocol-based access to data even though that data isn’t stored in HDFS (the file system) at all. Moreover, analytics distributions are acknowledging that data may be stored on external HDFS-interfaced storage. This approach doesn’t solve the issues around scaling IO to actually achieve efficient “big data,” but it does allow customers to gain access to data services and, importantly, to large volumes of incumbent data that are already stored in those legacy systems. At the end of the day, the storage tussle points to the fact that what is really needed for big data is to fully integrate enterprise storage and big data storage into a single, unified storage system. The recent turn toward scale-out storage architectures in enterprises makes a strong promise to deliver on this because they do not have the connectivity and controller bottleneck problems that are endemic to old enterprise storage. In fact, there is a strong possibility that protocol-level integrations for HDFS (both NameNode and DataNode services) may result in systems that far exceed both the performance and functionality of HDFS as it is implemented today, offering the performance of scale-out systems (like HDFS) and the advanced features of enterprise storage systems. Bringing Big Data into the FoldBig data tools and environments have requirements that make them challenging to support with traditional IT infrastructure. However, at the end of the day, big data is still data, and enterprises have come to expect a rich set of capabilities in terms of managing, integrating and protecting that data. Many of these are not yet provided by big data systems that elect to add an entirely new IT silo to the datacenter environment. This property is changing rapidly: as big data deployments continue to move from exploratory projects to business critical systems, IT systems will need to adapt and evolve in order to provide for the needs of large-scale analytics and business intelligence systems, while concurrently providing for the rich set of capabilities that is expected of all data within the enterprise. Industry Perspectives is a content channel at Data Center Knowledge highlighting thought leadership in the data center arena. See our guidelines and submission process for information on participating. View previously published Industry Perspectives in our Knowledge Library. |
| 4:00p | Cavium Links ARM Servers With Storage via 25GbE Links As part of an effort to further disaggregate servers and storage Cavium, a semiconductor vendor focused on ARM servers, has enlisted the aid of QLogic. Under the terms of the alliance between the two vendors, San Jose, California-based Cavium will make QLogic 25Gb Ethernet (25GbE) RDMA-enabled NICs available with servers based on its 48-core ThunderX processors. Manoj Gurjal, vice president of marketing for Ethernet products at Qlogic, says Cavium is making use of QLogic 25GbE RNICs that access a heterogeneous remote direct memory access (RDMA) transport comprised of RDMA over Converged Ethernet and iWARP technologies that serve to offload storage processing requests from the server. Separating compute and storage, says Gurjal, enables IT organization to scale each element of the data center separately. “Storage is growing much faster than compute in the data center,” says Gurjal. “Disaggregation of storage requires access to a low-latency fabric.” In the case of Qlogic, that fabric is provided by 25Gb Ethernet cards that are expected to become a new standard shortly. Gopal Hegde, vice president and general manager for the Data Center Processing Group at Cavium, says the alliance with Qlogic means that the company’s server platform can now be used to support Big Data applications that require access to petabytes of storage that is not attached directly to a server. In general, Cavium has been positioning its ARM servers as an alternative to Intel processors that are designed to provide access to lots of memory in a way that doesn’t consume as much power. The end result is a denser server environment that scales better, says Hegde. While there is a lot of hype surrounding the emergence of converged infrastructure inside the data center, Gurjal says, closely coupling compute and storage is not particularly practical when deploying Big Data applications. An alternative approach, says Gurjal, is to disaggregate compute and storage and then rely on IT management software to holistically manage a set of infrastructure resources that are linked over 25Gb Ethernet connections. The key aspect of that approach from performance perspective is that managing access to storage is offloaded by Qlogic NICs that have their own storage system-on-a-chip (SoC) processor engine , says Gurjal. Historically, IT organizations have preferred to be able to manage compute, storage, and networking in isolation from another. The degree to which IT organizations will not want to converge the management of those three core elements of the data center will vary. But the one thing that is for certain is that the more Big Data applications find their way into the data center, the more challenging it becomes to physically converge compute and storage. |
| 4:32p | Amazon Data Center Deal in Ohio Includes 1,000 Jobs Amazon is building a major hub in Ohio and the jobs are following in tow. In addition to a massive $1.2 billion Amazon data center project across three townships, the company has committed to creating 1,000 jobs. The deal was brokered by Ohio’s privatized job creation entity JobsOhio. The jobs will average about $80,000 yearly. As part of the arrangement, Amazon will also start collecting sales tax on online orders in the state, a standard practice when the giant sets up shop within a given state. The company has received generous tax breaks for the Ohio data center project. Most of the speculation around job creation was a much lower figure, given data centers typically don’t create many permanent jobs within a facility. However, Ohio will act as more than just an Amazon data center hub for servers, but also a hub for its people. The 1,000 figure includes jobs at the company’s fulfillment centers. When looking at data center job creation numbers, the effect on the local economy extends far beyond the data center’s walls. While an actual facility will have a limited number of full-time workers within, the data center helps surrounding businesses and economic activity thrive. Amazon now touts more than one million Amazon Web Services customers and more than 275 million retail customers. It has 50 fulfillment centers with median pay a third higher than traditional retail stores, according to the company. JobsOhio has been criticized in the past for lack of transparency, so the Amazon news is a big win for the state’s economic development arm. Gartner in its recent Infrastructure-as-a-Service Magic Quadrant report estimated that Amazon had 10 times the cloud compute capacity than the next fourteen IaaS providers combined. |
| 6:01p | Rackspace Lures Companies in Highly Regulated Industries with New Dedicated MongoDB Offering
This article originally appeared at The WHIR Rackspace is helping customers in highly regulated industries like healthcare and financial services take advantage of the scalability of MongoDB with a new dedicated option of ObjectRocket for MongoDB databases. Rackspace made the announcement on Monday at MongoDB World, a two-day conference held in New York for developers, sysadmins and DBAs. Rackspace is platinum sponsor of the event. MongoDB database as a service provider ObjectRocket joined Rackspace in 2013, and is now part of the company’s data storage division. Chris Lalonde, co-founder of ObjectRocket, said that the new dedicated MongoDB offering “is our general awesomeness but packaged into cabinets.” “The cabinet has all the components that we offer to customers but in a fully isolated and dedicated infrastructure,” he tells the WHIR in a phone interview. In a statement, Lalonde said that dedicated ObjectRocket lets applications scale to millions of MongoDB operations per second and customers can access MongoDB experts 24×7 for all their support needs. David Swanger, senior director of data services solution marketing said that Rackspace’s new offering brings more security, an important consideration for enterprises that have to meet stringent compliance requirements. “With databases, things like security, encryption and isolation are incredibly important for those types of customers,” he said. “With these big, expensive enterprise databases like Oracle and SQL Server, those vendors have done a good job of building that functionality into those databases, but on the flip side they’re really hard to manage and really expensive, and are somewhat inflexible in terms of what you can actually do with the databases.” “What happened over the last few years is there have been all of these new entrants coming into the field, like MongoDB, and CouchBase and Cassandra. They’re all open source databases and are a lot more flexible in terms of what you can actually do with the database, and they’re also free. They check a lot of those boxes.” “The issue is they are not as robust in terms of the security and isolation type of features and the learning curve that’s needed to be able to get those databases to work in a high security and isolated environment it is really difficult and it takes a lot of special expertise,” Swanger said. Lalonde said that the level of isolation that the dedicated ObjectRocket for MongoDB is “good enough for large enterprises”, and the offering also includes on-disk encryption, which he claims to be a first – “there’s nobody else in the field that offers on-disk encryption for Mongo as far as I’m aware especially in that sort of fully dedicated environment.” However, it appears that there is a least one other database as a service provider offering disk encryption. MongoDirector offers disk encryption that encrypts data at rest, and its MongoDB hosting includes dedicated instances, according to its website. While so far MongoDB has mostly been used by mobile and gaming companies, Swanger said, the database has reached a new level maturity which is opening it up to a wider customer base. “…[Y]ou go back two or three years ago and [MongoDB] was really developer-driven, it was probably more startups using it,” he said. “Now it’s sort of coming into mainstream adoption and big companies are using it for a lot of different things. We’re really excited for the ecosystem as a whole to reach this new level of maturity where enterprises are not just looking at using Oracle or Microsoft but they’re looking at Mongo as a viable alternative for mobile and things like that.” Rackspace will continue to offer fully managed versions of other databases includingRedis, Hadoop, Apache Spark, Oracle Database, Microsoft SQL Server, MySQL, Percona and Maria DB. This first ran at http://www.thewhir.com/web-hosting-news/r |
| 6:30p | Hedvig, Founded by Apache Cassandra Creator, Raises $18M Software defined storage startup Hedvig has closed an $18 million Series B, two months after the company’s official launch and announcement of its Series A funding round. The latest round will fund global expansion. The company has raised $30.5 million in financing to date. The startup was founded by Avinash Lakshman, the engineer who created Apache Cassandra while working at Facebook in 2008. Cassandra is a popular open source distributed database management system originally built for Facebook’s Inbox Search feature. Hedvig combines disparate storage systems into a single virtualized pool controlled from a single platform that manages both public and private cloud infrastructure. It also enables complete protocol consolidation by collapsing several layers of the storage stack into a single software platform, resulting in faster provisioning time, lower costs, and a more flexible storage picture, according to the company. Companies like Hedvig look to help customers avoid the need for constant refreshing by providing a platform that makes commodity storage more future-proof by pooling resources. Another benefit of such pooling systems is providing an avenue to achieving web scale. Hedvig was built by software engineers with expertise in distributed systems. Lakshman, the company’s CEO, is credited with having built some of the most successful distributed systems in the world: Amazon Dynamo and Cassandra. The startup wants to redefine data storage by looking through a distributed-systems lens. Vertex Ventures led the round with participation from existing investors True Ventures and Atlantic Bridge. “Avinash and I worked together at Facebook where he built a reputation for tackling transformational problems,” said Jonathan Heiliger, general partner at Vertex and former vice president of infrastructure and technical operations at Facebook, in a release. “Apache Cassandra, which Avinash invented, has been lauded for its robust design and inimitable scalability—attributes Hedvig brings to modern storage for modern business. Hedvig’s product initially seems like sci-fi, the good kind that leaves you wanting more.” The storage market is fragmented and currently undergoing a “software defined” evolution, with many startups vying to be the transformational platform. Data center modernization is currently considered the second most important IT initiative for enterprises, according to Enterprise Strategy Group, and data is growing at 10 times the rate of storage budgets, according to Forrester. Software defined storage companies continue to see healthy rounds. Last week, converged data management provider Rubrik announced a $41 million round, mere months after a $10 million round. Vertex general partner In Sik Rhee also joins Hedvig’s board of directors. |
| 9:10p | Intel Looks to Future Data Center Market With $16.7B Altera Acquisition Intel is acquiring server FPGA maker Altera for $16.7 billion to expand its data center chip offerings. In an all-cash deal, Intel will pay $54 a share, a 10-percent premium to Altera’s closing price Friday. Altera’s stock has risen over 40 percent since a previous failed offer from Intel a few months ago. The deal extends Intel’s already enormous data center chip play. “Altera provides a nice differentiation to server offerings,” said Gartner analyst Mark Hung. “Intel might not be worried about AMD, but they need to stay ahead of the game.” Hung said Intel’s largest customers have both the resources and the technical know-how to develop their own server CPUs. This is a way for Intel to continue to address needs of their biggest customers. Big web-scale companies like Facebook and Google are already making their own servers, but the fear is that they will start to make their own chips. Altera makes reconfigurable logic with on-chip memory and DSP blocks for a software defined data center. It is a leader in field programmable gate arrays (FPGAs). FPGAs are programmable logic devices, used in many networking and storage systems, but server FPGAs are gradually making inroads in the market as well. Intel plans to combine its chips with Altera’s programmable chips, which can be used for a variety of purposes, such as speeding web searches. Microsoft is working with Altera’s server FPGAs to accelerate Bing, for example. The Redmond, Washington-based giant has designed cloud servers that support CPUs and FPGAs. Intel’s previous offer for Altera was rejected in April. The new price is reportedly unchanged from the previous deal, however. Data centers are where the growth in the chip industry is occurring, as the PC industry is seeing slowing demand. Research numbers from IDC show a downward trend in PC sales, while cloud infrastructure is a major growth area for servers. Cloud infrastructure spending is expected to reach $32 billion this year. Gartner research shows PC shipments have fallen in the last three years, including a drop of over 5 percent in the first quarter of this year. More consumers are relying on tablets and smart phones as main devices. Intel’s own quarterly results illustrate the trends well. Like in all previous quarters in recent years, Intel data center division’s sales were up about 20 percent in the year’s first quarter, outperforming all other business units in terms of growth. Altera will help Intel boost its higher-margin data center chip offerings, so that it can retain an edge in the data center. Another influence on the chip market is the Internet of Things, and Altera’s chips are often used for non-traditional functions such as those needed to power increasing diversity of connected devices. “Intel’s growth strategy is to expand our core assets into profitable, complementary market segments,” said Brian Krzanich, CEO of Intel, in a press release. “With this acquisition, we will harness the power of Moore’s Law to make the next generation of solutions not just better, but able to do more. Whether to enable new growth in the network, large cloud data centers or IoT segments, our customers expect better performance at lower costs. This is the promise of Moore’s Law and it’s the innovation enabled by Intel and Altera joining forces.” Altera will continue to support designs that couple its chips with others designed on ARM Holdings tech. Other recent big chip deals include Avago Technologies’ purchase of Broadcom Corp for $37 billion, the largest deal ever in the $300 billion semiconductor market, and NXP Semiconductors’ acquisition of Freescale Semiconductor for $12 billion. JP Morgan and Rothschild served as financial advisors to Intel, while Goldman Sachs served as Altera’s financial advisor. |
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