Click here to close now.


@ThingsExpo Authors: Ian Khan, Liz McMillan, Elizabeth White, Yeshim Deniz, Carmen Gonzalez

Related Topics: @ThingsExpo, Containers Expo Blog, @CloudExpo, @BigDataExpo, SDN Journal, @DevOpsSummit

@ThingsExpo: Blog Post

The 'Internet of Things' and Big Data | @ThingsExpo [#IoT]

The Internet of Things is only going to make that even more challenging as businesses turn to new business models and services

Cloud and Things and Big Operational Data

Software-defined architectures are critical for achieving the right mix of efficiency and scale needed to meet the challenges that will come with the Internet of Things

If you've been living under a rock (or rack in the data center) you might not have noticed the explosive growth of technologies and architectures designed to address emerging challenges with scaling data centers. Whether considering the operational aspects (devops) or technical components (SDN, SDDC, Cloud), software-defined architectures are the future enabler of business, fueled by the increasing demand for applications.

The Internet of Things is only going to make that even more challenging as businesses turn to new business models and services fueled by a converging digital-physical world. Applications, whether focused on licensing, provisioning, managing or storing data for these "things" will increase the already significant burden on IT as a whole. The inability to scale from an operational perspective is really what software-defined architectures are attempting to solve by operationalizing the network to shift the burden of provisioning and management from people to technology.

But it's more than just API-enabling switches, routers, ADCs and other infrastructure components. While this is a necessary capability to ensure the operational scalability of modern data centers, what's really necessary to achieve the next "level" is collaboration.

That means infrastructure integration.

it is one thing to be able to automatically provision the network, compute and storage resources necessary to scale to meet the availability and performance expectations of users and businesses alike. But that's the last step in the process. Actually performing the provisioning is the action that's taken after it's determined not only that it's necessary, but where it's necessary.

Workloads (and I hate that term but it's at least somewhat universally understood so I'll acquiesce to using it for now) have varying characteristics with respect to the compute, network and storage they require to perform optimally. That's means provisioning a "workload" in a VM with characteristics that do not match the requirements is necessarily going to impact its performance or load capability. If one is making assumptions regarding the number of users a given application can support, and it's provisioned with a resource profile that impacts that support, it can lead to degrading performance or availability.

What that means is the systems responsible for provisioning "workloads" must be able to match resource requirements with the workload, as well as understand current (and predicted) demand in terms of users, connections and network consumption rates.

Data, is the key. Measurements of performance, rates of queries, number of users, and the resulting impact on the workload must be captured. But more than that, it must be shared with the systems responsible for provisioning and scaling the workloads.

Location Matters

This is not a new concept, that we should be able to share data across systems and services to ensure the best fit for provisioning and seamless scale demanded of modern architectures. A 2007 SIGMOD paper, "Automated and On-Demand Provisioning of Virtual Machines for Database Applications" as well as a 2010 IEEE paper, "Dynamic Provisioning Modeling for Virtualized Multi-tier Applications in Cloud Data Center" discuss the need for such provisioning models and the resulting architectures rely heavily on the collaboration of the data center components responsible for measuring, managing and provisioning workloads in cloud computing environments through integration.

The location of a workload, you see, matters. Not location as in "on-premise" or "off-premise", though that certainly has an impact, but the location within the data center matters to the overall performance and scale of the applications composed from those workloads. The location of a specific workload comparative to other components impacts availability and traffic patterns that can result in higher incidents of north-south or east-west congestion in the network. Location of application workloads can cause hairpinning (or tromboning if you prefer) of traffic that may degrade performance or introduce variable latency that degrades the quality of video or audio content.

Location matters a great deal, and yet the very premise of cloud is to abstract topology (location) from the equation and remove it from consideration as part of the provisioning process.

Early in the life of public cloud there was concern over not knowing "who your neighbor tenant" might be on a given physical server, because there was little transparency into the decision making process that governs provisioning of instances in public cloud environments. The depth of such decisions appeared to - and still appear to - be made based on your preference for the "size" of an instance. Obviously, Amazon or Azure or Google is not going to provision a "large" instance where only a "small" will fit.

But the question of where, topologically, that "large" instance might end up residing is still unanswered. It might be two hops away or one virtual hop away. You can't know if your entire application - all its components - have been launched on the same physical server or not. And that can have dire consequences in a model that's "built to fail" because if all your eggs are in one basket and the basket breaks... well, minutes of downtime is still downtime.

The next evolutionary step in cloud (besides the emergence of much needed value added services) is more intelligent provisioning driven by better feedback loops regarding the relationship between the combination of compute, network and storage resources and the application. Big (Operational) Data is going to be as important to IT as Big (Customer) Data is to the business as more and more applications and services become critical to the business.

More Stories By Lori MacVittie

Lori MacVittie is responsible for education and evangelism of application services available across F5’s entire product suite. Her role includes authorship of technical materials and participation in a number of community-based forums and industry standards organizations, among other efforts. MacVittie has extensive programming experience as an application architect, as well as network and systems development and administration expertise. Prior to joining F5, MacVittie was an award-winning Senior Technology Editor at Network Computing Magazine, where she conducted product research and evaluation focused on integration with application and network architectures, and authored articles on a variety of topics aimed at IT professionals. Her most recent area of focus included SOA-related products and architectures. She holds a B.S. in Information and Computing Science from the University of Wisconsin at Green Bay, and an M.S. in Computer Science from Nova Southeastern University.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.

@ThingsExpo Stories
The buzz continues for cloud, data analytics and the Internet of Things (IoT) and their collective impact across all industries. But a new conversation is emerging - how do companies use industry disruption and technology enablers to lead in markets undergoing change, uncertainty and ambiguity? Organizations of all sizes need to evolve and transform, often under massive pressure, as industry lines blur and merge and traditional business models are assaulted and turned upside down. In this new data-driven world, marketplaces reign supreme while interoperability, APIs and applications deliver un...
The Internet of Things (IoT) is growing rapidly by extending current technologies, products and networks. By 2020, Cisco estimates there will be 50 billion connected devices. Gartner has forecast revenues of over $300 billion, just to IoT suppliers. Now is the time to figure out how you’ll make money – not just create innovative products. With hundreds of new products and companies jumping into the IoT fray every month, there’s no shortage of innovation. Despite this, McKinsey/VisionMobile data shows "less than 10 percent of IoT developers are making enough to support a reasonably sized team....
Electric power utilities face relentless pressure on their financial performance, and reducing distribution grid losses is one of the last untapped opportunities to meet their business goals. Combining IoT-enabled sensors and cloud-based data analytics, utilities now are able to find, quantify and reduce losses faster – and with a smaller IT footprint. Solutions exist using Internet-enabled sensors deployed temporarily at strategic locations within the distribution grid to measure actual line loads.
You have your devices and your data, but what about the rest of your Internet of Things story? Two popular classes of technologies that nicely handle the Big Data analytics for Internet of Things are Apache Hadoop and NoSQL. Hadoop is designed for parallelizing analytical work across many servers and is ideal for the massive data volumes you create with IoT devices. NoSQL databases such as Apache HBase are ideal for storing and retrieving IoT data as “time series data.”
Too often with compelling new technologies market participants become overly enamored with that attractiveness of the technology and neglect underlying business drivers. This tendency, what some call the “newest shiny object syndrome,” is understandable given that virtually all of us are heavily engaged in technology. But it is also mistaken. Without concrete business cases driving its deployment, IoT, like many other technologies before it, will fade into obscurity.
Today air travel is a minefield of delays, hassles and customer disappointment. Airlines struggle to revitalize the experience. GE and M2Mi will demonstrate practical examples of how IoT solutions are helping airlines bring back personalization, reduce trip time and improve reliability. In their session at @ThingsExpo, Shyam Varan Nath, Principal Architect with GE, and Dr. Sarah Cooper, M2Mi's VP Business Development and Engineering, will explore the IoT cloud-based platform technologies driving this change including privacy controls, data transparency and integration of real time context w...
The Internet of Everything is re-shaping technology trends–moving away from “request/response” architecture to an “always-on” Streaming Web where data is in constant motion and secure, reliable communication is an absolute necessity. As more and more THINGS go online, the challenges that developers will need to address will only increase exponentially. In his session at @ThingsExpo, Todd Greene, Founder & CEO of PubNub, will explore the current state of IoT connectivity and review key trends and technology requirements that will drive the Internet of Things from hype to reality.
The IoT market is on track to hit $7.1 trillion in 2020. The reality is that only a handful of companies are ready for this massive demand. There are a lot of barriers, paint points, traps, and hidden roadblocks. How can we deal with these issues and challenges? The paradigm has changed. Old-style ad-hoc trial-and-error ways will certainly lead you to the dead end. What is mandatory is an overarching and adaptive approach to effectively handle the rapid changes and exponential growth.
Today’s connected world is moving from devices towards things, what this means is that by using increasingly low cost sensors embedded in devices we can create many new use cases. These span across use cases in cities, vehicles, home, offices, factories, retail environments, worksites, health, logistics, and health. These use cases rely on ubiquitous connectivity and generate massive amounts of data at scale. These technologies enable new business opportunities, ways to optimize and automate, along with new ways to engage with users.
The IoT is upon us, but today’s databases, built on 30-year-old math, require multiple platforms to create a single solution. Data demands of the IoT require Big Data systems that can handle ingest, transactions and analytics concurrently adapting to varied situations as they occur, with speed at scale. In his session at @ThingsExpo, Chad Jones, chief strategy officer at Deep Information Sciences, will look differently at IoT data so enterprises can fully leverage their IoT potential. He’ll share tips on how to speed up business initiatives, harness Big Data and remain one step ahead by apply...
There will be 20 billion IoT devices connected to the Internet soon. What if we could control these devices with our voice, mind, or gestures? What if we could teach these devices how to talk to each other? What if these devices could learn how to interact with us (and each other) to make our lives better? What if Jarvis was real? How can I gain these super powers? In his session at 17th Cloud Expo, Chris Matthieu, co-founder and CTO of Octoblu, will show you!
SYS-CON Events announced today that ProfitBricks, the provider of painless cloud infrastructure, will exhibit at SYS-CON's 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. ProfitBricks is the IaaS provider that offers a painless cloud experience for all IT users, with no learning curve. ProfitBricks boasts flexible cloud servers and networking, an integrated Data Center Designer tool for visual control over the cloud and the best price/performance value available. ProfitBricks was named one of the coolest Clo...
As a company adopts a DevOps approach to software development, what are key things that both the Dev and Ops side of the business must keep in mind to ensure effective continuous delivery? In his session at DevOps Summit, Mark Hydar, Head of DevOps, Ericsson TV Platforms, will share best practices and provide helpful tips for Ops teams to adopt an open line of communication with the development side of the house to ensure success between the two sides.
SYS-CON Events announced today that IBM Cloud Data Services has been named “Bronze Sponsor” of SYS-CON's 17th Cloud Expo, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. IBM Cloud Data Services offers a portfolio of integrated, best-of-breed cloud data services for developers focused on mobile computing and analytics use cases.
SYS-CON Events announced today that Sandy Carter, IBM General Manager Cloud Ecosystem and Developers, and a Social Business Evangelist, will keynote at the 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA.
Developing software for the Internet of Things (IoT) comes with its own set of challenges. Security, privacy, and unified standards are a few key issues. In addition, each IoT product is comprised of at least three separate application components: the software embedded in the device, the backend big-data service, and the mobile application for the end user's controls. Each component is developed by a different team, using different technologies and practices, and deployed to a different stack/target - this makes the integration of these separate pipelines and the coordination of software upd...
Mobile messaging has been a popular communication channel for more than 20 years. Finnish engineer Matti Makkonen invented the idea for SMS (Short Message Service) in 1984, making his vision a reality on December 3, 1992 by sending the first message ("Happy Christmas") from a PC to a cell phone. Since then, the technology has evolved immensely, from both a technology standpoint, and in our everyday uses for it. Originally used for person-to-person (P2P) communication, i.e., Sally sends a text message to Betty – mobile messaging now offers tremendous value to businesses for customer and empl...
"Matrix is an ambitious open standard and implementation that's set up to break down the fragmentation problems that exist in IP messaging and VoIP communication," explained John Woolf, Technical Evangelist at Matrix, in this interview at @ThingsExpo, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
WebRTC converts the entire network into a ubiquitous communications cloud thereby connecting anytime, anywhere through any point. In his session at WebRTC Summit,, Mark Castleman, EIR at Bell Labs and Head of Future X Labs, will discuss how the transformational nature of communications is achieved through the democratizing force of WebRTC. WebRTC is doing for voice what HTML did for web content.
The broad selection of hardware, the rapid evolution of operating systems and the time-to-market for mobile apps has been so rapid that new challenges for developers and engineers arise every day. Security, testing, hosting, and other metrics have to be considered through the process. In his session at Big Data Expo, Walter Maguire, Chief Field Technologist, HP Big Data Group, at Hewlett-Packard, will discuss the challenges faced by developers and a composite Big Data applications builder, focusing on how to help solve the problems that developers are continuously battling.