Welcome!

Apache Authors: Dmitriy Stepanov, Yeshim Deniz, Pat Romanski, Lacey Thoms, Sandi Mappic

Blog Feed Post

Why Contextual Data Locality Matters

Big Data is quickly overtaking SDN as a key phrase in today’s networking lingo. And overused already as it may be, it actually has a lot more meaning and definition compared to SDN. Big Data solutions are designed to work on lots of data as the name suggests. Of course they have been around forever, talk to any large bank, credit card company, airline or logistics company and all of them have had applications running on extremely large databases and data sets forever. But this is the new Big Data, the one inspired by Hadoop, MapReduce and friends. High performance compute clusters specifically created to analyze large amounts of data and reduce it to a form and quantity that human brains can use in decision making.

What makes today’s Big Data solutions different than its more traditional large database based applications, beyond the sheer datasets being analyzed, is the distributed nature of the analysis. Big Data solutions are designed to run across 100s or even 1000s of servers, each with multiple CPU cores to chew on the data. Traditional large database applications tend to be more localized with fewer applications and servers accessing the data, allowing for more tightly custom integrated solutions, the likes of which Oracle and friends are experts at.

Big Data Flashback

In the late 80s I started my career working as a network engineer for a high energy physics research institute. Working closely with the folks at CERN in Geneva, these physicists were (at the time, and probably still) masters of creating very large datasets. Every time an experiment was run, Tbytes of data (probably Pbytes by now) were generated by thousands of sensors along the tunnel or ring particles were passed through to collide.

The Big Data solution at the time was primitive, but not all that much different than today. The large datasets were manually broken into manageable pieces, something that would fit on a tape or disk. These datasets were then hand copied onto a compute server or super computer and the analysis application would churn through it to find specific data, correlate events and simply reduce the data to something smaller and meaningful. This would then create a new dataset, which would be combined, chopped up again, and the process repeated itself until they arrived at data that was consumable for humans to create new theories from, or provide a piece of proof of an existing theory.

During that first job, the IT group spend an enormous amount of time moving data around. A lot of it manual: tapes and disks were constantly being copied onto the appropriate compute server. The data had to be local to have any chance of analyzing the data. Between tapes, local disks and the network, the local disks were the only storage with appropriate speed to have a hope of finalizing the data reductions. And even then it would not be unusual to have a rather powerful (for the time) Apollo workstation run for several weeks on a single data set.

Back to the here and now

Forward the clock to now. The above description is really not that different from how Hadoop MapReduce works. Start with a big data set, chop it into pieces, replicate the data, compute on the data close to physical locality of the data. Then send results to Reducers, combine the results, then perhaps repeat again to get to human interpretable results.

As fast as we believe the network is within 10GbE access ports, it is still commonly the most restrictive component in the compute, distributed storage and network trio. Compute power increments have far outpaced network speed increments and even memory speed increments. We have many more cycles available to compute, but have not been able to get the data into these CPUs with the same increments. As a result, storage solutions are becoming increasingly distributed, closer to the compute power that needs it.

It’s a natural thought to have the data close to where it needs to be processed, close enough that the effort of retrieving it does not impact the overall completion of the task that uses that data. If I am writing a research paper that takes several hours to complete, I do not mind having to wait a second here or there for the right web sites to load. I would mind if I had to get into my car and drive to the library to look something up, drive back home to work on my paper, and keep doing that. The relationship between time and effort to get data has to become negligible compared to the time and effort required to complete the task.

Locality and growth

This type of contextual locality is extremely hard to manage in a dynamic and growing environment. How do you make sure that the right data remains contextually close to where it is needed when servers and VMs may not be physically close? They may not be in the same rack for the same application or customer, they may not even be in the same pod or datacenter. Storage is relatively cheap, but replication for closeness can very quickly lead to a data distribution complexity that is unmanageable in environments where its not a single orchestrated big data solution.

To solve this problem you need help from your network. You need to be able to create locality on the fly. Things that are not physically close need to be made virtually close, but with the characteristics of physical locality. And in network terms these are of course measured in the usual staples of latency and bandwidth. This is when you want to articulate relationships between the data and the applications that need that data and create virtual closeness that resembles the physical. This may mean dedicated paths through multiple switches to avoid congestion that will dramatically impact latency. These same paths can provide direct physical connectivity through dynamically engineered optical paths between application and storage, or simply appropriate prioritization of traffic along these paths. Without having to worry explicitly where the application is or where the storage is.

Physics will always stand in the way of what we really want or need, but that does not mean we use that same physics with a bit of math to create solutions that manage the complexity of creating dynamic locality. Locality is important. More pronounced in Big Data solutions, but even at a smaller scale it is important within the context of the compute effort on that data.

[Today's fun fact: Lake Superior is the world's largest lake. With that kind of naming accuracy we would like to hire the person that named the lake as our VP of Naming and Terminology]

The post Why Contextual Data Locality Matters appeared first on Plexxi.

Read the original blog entry...

More Stories By Michael Bushong

The best marketing efforts leverage deep technology understanding with a highly-approachable means of communicating. Plexxi's Vice President of Marketing Michael Bushong has acquired these skills having spent 12 years at Juniper Networks where he led product management, product strategy and product marketing organizations for Juniper's flagship operating system, Junos. Michael spent the last several years at Juniper leading their SDN efforts across both service provider and enterprise markets. Prior to Juniper, Michael spent time at database supplier Sybase, and ASIC design tool companies Synopsis and Magma Design Automation. Michael's undergraduate work at the University of California Berkeley in advanced fluid mechanics and heat transfer lend new meaning to the marketing phrase "This isn't rocket science."

@ThingsExpo Stories
Software AG helps organizations transform into Digital Enterprises, so they can differentiate from competitors and better engage customers, partners and employees. Using the Software AG Suite, companies can close the gap between business and IT to create digital systems of differentiation that drive front-line agility. We offer four on-ramps to the Digital Enterprise: alignment through collaborative process analysis; transformation through portfolio management; agility through process automation and integration; and visibility through intelligent business operations and big data.
There will be 50 billion Internet connected devices by 2020. Today, every manufacturer has a propriety protocol and an app. How do we securely integrate these "things" into our lives and businesses in a way that we can easily control and manage? Even better, how do we integrate these "things" so that they control and manage each other so our lives become more convenient or our businesses become more profitable and/or safe? We have heard that the best interface is no interface. In his session at Internet of @ThingsExpo, Chris Matthieu, Co-Founder & CTO at Octoblu, Inc., will discuss how these devices generate enough data to learn our behaviors and simplify/improve our lives. What if we could connect everything to everything? I'm not only talking about connecting things to things but also systems, cloud services, and people. Add in a little machine learning and artificial intelligence and now we have something interesting...
Last week, while in San Francisco, I used the Uber app and service four times. All four experiences were great, although one of the drivers stopped for 30 seconds and then left as I was walking up to the car. He must have realized I was a blogger. None the less, the next car was just a minute away and I suffered no pain. In this article, my colleague, Ved Sen, Global Head, Advisory Services Social, Mobile and Sensors at Cognizant shares his experiences and insights.
We are reaching the end of the beginning with WebRTC and real systems using this technology have begun to appear. One challenge that faces every WebRTC deployment (in some form or another) is identity management. For example, if you have an existing service – possibly built on a variety of different PaaS/SaaS offerings – and you want to add real-time communications you are faced with a challenge relating to user management, authentication, authorization, and validation. Service providers will want to use their existing identities, but these will have credentials already that are (hopefully) irreversibly encoded. In his session at Internet of @ThingsExpo, Peter Dunkley, Technical Director at Acision, will look at how this identity problem can be solved and discuss ways to use existing web identities for real-time communication.
Can call centers hang up the phones for good? Intuitive Solutions did. WebRTC enabled this contact center provider to eliminate antiquated telephony and desktop phone infrastructure with a pure web-based solution, allowing them to expand beyond brick-and-mortar confines to a home-based agent model. It also ensured scalability and better service for customers, including MUY! Companies, one of the country's largest franchise restaurant companies with 232 Pizza Hut locations. This is one example of WebRTC adoption today, but the potential is limitless when powered by IoT. Attendees will learn real-world benefits of WebRTC and explore future possibilities, as WebRTC and IoT intersect to improve customer service.
From telemedicine to smart cars, digital homes and industrial monitoring, the explosive growth of IoT has created exciting new business opportunities for real time calls and messaging. In his session at Internet of @ThingsExpo, Ivelin Ivanov, CEO and Co-Founder of Telestax, will share some of the new revenue sources that IoT created for Restcomm – the open source telephony platform from Telestax. Ivelin Ivanov is a technology entrepreneur who founded Mobicents, an Open Source VoIP Platform, to help create, deploy, and manage applications integrating voice, video and data. He is the co-founder of TeleStax, an Open Source Cloud Communications company that helps the shift from legacy IN/SS7 telco networks to IP-based cloud comms. An early investor in multiple start-ups, he still finds time to code for his companies and contribute to open source projects.
The Internet of Things (IoT) promises to create new business models as significant as those that were inspired by the Internet and the smartphone 20 and 10 years ago. What business, social and practical implications will this phenomenon bring? That's the subject of "Monetizing the Internet of Things: Perspectives from the Front Lines," an e-book released today and available free of charge from Aria Systems, the leading innovator in recurring revenue management.
The Internet of Things will put IT to its ultimate test by creating infinite new opportunities to digitize products and services, generate and analyze new data to improve customer satisfaction, and discover new ways to gain a competitive advantage across nearly every industry. In order to help corporate business units to capitalize on the rapidly evolving IoT opportunities, IT must stand up to a new set of challenges.
There’s Big Data, then there’s really Big Data from the Internet of Things. IoT is evolving to include many data possibilities like new types of event, log and network data. The volumes are enormous, generating tens of billions of logs per day, which raise data challenges. Early IoT deployments are relying heavily on both the cloud and managed service providers to navigate these challenges. In her session at 6th Big Data Expo®, Hannah Smalltree, Director at Treasure Data, to discuss how IoT, Big Data and deployments are processing massive data volumes from wearables, utilities and other machines.
All major researchers estimate there will be tens of billions devices – computers, smartphones, tablets, and sensors – connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades. With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend @ThingsExpo in Silicon Valley. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be!
P2P RTC will impact the landscape of communications, shifting from traditional telephony style communications models to OTT (Over-The-Top) cloud assisted & PaaS (Platform as a Service) communication services. The P2P shift will impact many areas of our lives, from mobile communication, human interactive web services, RTC and telephony infrastructure, user federation, security and privacy implications, business costs, and scalability. In his session at Internet of @ThingsExpo, Erik Lagerway, Co-founder of Hookflash, will walk through the shifting landscape of traditional telephone and voice services to the modern P2P RTC era of OTT cloud assisted services.
While great strides have been made relative to the video aspects of remote collaboration, audio technology has basically stagnated. Typically all audio is mixed to a single monaural stream and emanates from a single point, such as a speakerphone or a speaker associated with a video monitor. This leads to confusion and lack of understanding among participants especially regarding who is actually speaking. Spatial teleconferencing introduces the concept of acoustic spatial separation between conference participants in three dimensional space. This has been shown to significantly improve comprehension and conference efficiency.
The Internet of Things is tied together with a thin strand that is known as time. Coincidentally, at the core of nearly all data analytics is a timestamp. When working with time series data there are a few core principles that everyone should consider, especially across datasets where time is the common boundary. In his session at Internet of @ThingsExpo, Jim Scott, Director of Enterprise Strategy & Architecture at MapR Technologies, will discuss single-value, geo-spatial, and log time series data. By focusing on enterprise applications and the data center, he will use OpenTSDB as an example to explain some of these concepts including when to use different storage models.
SYS-CON Events announced today that Gridstore™, the leader in software-defined storage (SDS) purpose-built for Windows Servers and Hyper-V, will exhibit at SYS-CON's 15th International Cloud Expo®, which will take place on November 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA. Gridstore™ is the leader in software-defined storage purpose built for virtualization that is designed to accelerate applications in virtualized environments. Using its patented Server-Side Virtual Controller™ Technology (SVCT) to eliminate the I/O blender effect and accelerate applications Gridstore delivers vmOptimized™ Storage that self-optimizes to each application or VM across both virtual and physical environments. Leveraging a grid architecture, Gridstore delivers the first end-to-end storage QoS to ensure the most important App or VM performance is never compromised. The storage grid, that uses Gridstore’s performance optimized nodes or capacity optimized nodes, starts with as few a...
The Transparent Cloud-computing Consortium (abbreviation: T-Cloud Consortium) will conduct research activities into changes in the computing model as a result of collaboration between "device" and "cloud" and the creation of new value and markets through organic data processing High speed and high quality networks, and dramatic improvements in computer processing capabilities, have greatly changed the nature of applications and made the storing and processing of data on the network commonplace. These technological reforms have not only changed computers and smartphones, but are also changing the data processing model for all information devices. In particular, in the area known as M2M (Machine-To-Machine), there are great expectations that information with a new type of value can be produced using a variety of devices and sensors saving/sharing data via the network and through large-scale cloud-type data processing. This consortium believes that attaching a huge number of devic...
Innodisk is a service-driven provider of industrial embedded flash and DRAM storage products and technologies, with a focus on the enterprise, industrial, aerospace, and defense industries. Innodisk is dedicated to serving their customers and business partners. Quality is vitally important when it comes to industrial embedded flash and DRAM storage products. That’s why Innodisk manufactures all of their products in their own purpose-built memory production facility. In fact, they designed and built their production center to maximize manufacturing efficiency and guarantee the highest quality of our products.
Can call centers hang up the phones for good? Intuitive Solutions did. WebRTC enabled this contact center provider to eliminate antiquated telephony and desktop phone infrastructure with a pure web-based solution, allowing them to expand beyond brick-and-mortar confines to a home-based agent model. Download Slide Deck: ▸ Here
All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades. Over the summer Gartner released its much anticipated annual Hype Cycle report and the big news is that Internet of Things has now replaced Big Data as the most hyped technology. Indeed, we're hearing more and more about this fascinating new technological paradigm. Every other IT news item seems to be about IoT and its implications on the future of digital business.
BSQUARE is a global leader of embedded software solutions. We enable smart connected systems at the device level and beyond that millions use every day and provide actionable data solutions for the growing Internet of Things (IoT) market. We empower our world-class customers with our products, services and solutions to achieve innovation and success. For more information, visit www.bsquare.com.
With the iCloud scandal seemingly in its past, Apple announced new iPhones, updates to iPad and MacBook as well as news on OSX Yosemite. Although consumers will have to wait to get their hands on some of that new stuff, what they can get is the latest release of iOS 8 that Apple made available for most in-market iPhones and iPads. Originally announced at WWDC (Apple’s annual developers conference) in June, iOS 8 seems to spearhead Apple’s newfound focus upon greater integration of their products into everyday tasks, cross-platform mobility and self-monitoring. Before you update your device, here is a look at some of the new features and things you may want to consider from a mobile security perspective.