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  Think Big – Now Think Even Bigger
  Join Us at Internet of Things at Cloud Expo, November 11-13,
at the Javits Center!


The Internet of Things (IoT) is the most profound change in personal and enterprise IT since the creation of the Worldwide Web more than 20 years ago.

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 Internet of Things at Cloud Expo in New York City. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be!

Delegates to Internet of Things at Cloud Expo will be able to attend eight separate, information-packed tracks:

  • Enterprise Cloud
  • Digital Transformation
  • The API Enterprise | Mobility & Security
  • DevOps | Containers & Microservices
  • Cognitive Computing | AI, ML, DL
  • Big Data | Analytics
  • IoT | IIoT | Smart Cities
  • Hot Topics | FinTech | WebRTC

There are 120 breakout sessions in all, with Keynotes, General Sessions, and Power Panels adding to three days of incredibly rich presentations and content.


We'll see you in New York!



Day 3 Keynote at @ThingsExpo | Chris Matthieu, CTO of Octoblu
In his keynote at @ThingsExpo, Chris Matthieu, Director of IoT Engineering at Citrix and co-founder and CTO of Octoblu, focused on building an IoT platform and company. He provided a behind-the-scenes look at Octoblu's platform, business, and pivots along the way (including the Citrix acquisition of Octoblu).
  Themes & Topics to Be Discussed

Consumer IoT
• Wearables
• Smart Appliances
• Smart Cars
• Smartphones 2.0
• Automation
• Smart Travel
• Personal Fitness
• Health Care
• Personalized Marketing
• Customized Shopping
• Personal Finance
• The Digital Divide
• Mobile Cash & Markets
• Games & The IoT
• The Future of Education
• Virtual Reality

Enterprise IoT
• The Business Case for
x IoT
• Smart Grids
• Smart Cities
• Smart Transportation
• The Smart Home
• M2M
• Authentication/Security
• Wiring the IoT
• The Internet of
x Everything
• Digital Transformation
x of Enterprise IT
• Agriculture
• Transportation
• Manufacturing
• Local & State
x Government
• Federal Government

IoT Developers | WebRTC Summit
• Eclipse Foundation
• Cloud Foundry
• Linux Containers
• Node-Red
• Open Source Hardware
• Ajax and the IoT
• Leveraging SOA
• Multi-Cloud IoT
• Evolving Standards
• WebSockets
• Security & Privacy
x Protocols
• GPS & Proximity
x Services
• Bluetooth/RFID/etc
• XMPP
• Nest Labs



The Top Keynotes, the Best Sessions, a Rock Star Faculty and the Most Qualified Delegates of ANY Internet of Things Event!


The future of computing lies in these things. As computing takes a much more active role in our lives it will at the same time become much more invisible. Internet of Things Expo will address the challenges in getting from where we are today to this future.
 
The high-energy event is a must-attend for senior technologists from CEOs on down – including CIOs, CTOs, directors of infrastructure, VPs of technology, IT directors and managers, network and storage managers, network engineers, enterprise architects, and communications and networking specialists.




@ThingsExpo Power Panel | The World's Many IoTs: Which Are the Most Important?
The Internet of Things is clearly many things: data collection and analytics, wearables, Smart Grids and Smart Cities, the Industrial Internet, and more. Cool platforms like Arduino, Raspberry Pi, Intel's Galileo and Edison, and a diverse world of sensors are making the IoT a great toy box for developers in all these areas. In this Power Panel at @ThingsExpo, panelists discussed what things are the most important, which will have the most profound effect on the world, and what should we expect to see over the next couple of years.
Benefits of Attending the Three-Day Technical Program
  LEARNexactly why Internet of Things is relevant today from an economic, business and technology standpoint.
  HEAR first-hand from industry experts the common issues and requirements for creating a platform for the Internet of Things.
  SEE what new tools and approaches the Internet of Things requires.
  DISCOVER how to drive a distributed approach to the Internet of Things, where applications move to the data.
  FIND OUThow the vast volumes of new data produced by the Internet of Things provides a valuable new source of business insight through advanced analytical techniques.
  MASTER how the ongoing development of smart cities, cars, and houses will enhance connectivity infrastructure.
Lunch Power Panel | Microservices & IoT- Moderated by Jason Bloomberg
In this Power Panel at @DevOpsSummit, moderated by Jason Bloomberg, president of Intellyx, panelists Roberto Medrano, Executive Vice President at Akana; Lori MacVittie, Evangelist for F5 Networks; and Troy Topnik, ActiveState's Technical Product Manager; and Otis Gospodnetic, founder of Sematext; peeled away the buzz and discuss the important architectural principles behind implementing IoT solutions for the enterprise. As remote IoT devices and sensors become increasingly intelligent, they become part of our distributed cloud environment, and we must architect and code accordingly. At the very least, you'll have no problem filling in your buzzword bingo cards.


Applying Scalability Patterns to Infrastructure Architecture
Too often software design patterns are overlooked by network and application delivery network architects

Too often software design patterns are overlooked by network and application delivery network architects but these patterns are often equally applicable to addressing a broad range of architectural challenges in the application delivery tier of the data center.

The “High Scalability” blog is fast becoming one of my favorite reads. Last week did not disappoint with a post highlighting a set of scalability design patterns that was, apparently, inspired by yet another High Scalability post on “6 Ways to Kill Your Servers: Learning to Scale the Hard Way.

cheese-curds
Credit:Michael Chow/azcentral.com

This particular post caught my attention primarily because although I’ve touched on many of these patterns in the past, I’ve never thought to call them

what they are: scalability patterns. That’s probably a side-effect of forgetting that building an architecture of any kind is at its core computer science and thus algorithms and design patterns are applicable to both micro- and macro-architectures, such as those used when designing a scalable architecture.

This is actually more common than you’d think, as it’s rarely the case that a network guy and a developer sit down and discuss scalability patterns over beer and deep fried cheese curds (hey, I live in Wisconsin and it’s my blog post so just stop making faces until you’ve tried it). Developers and architects sit over there and think about how to design a scalable application from the perspective of its components – databases, application servers, middleware, etc… Network architects sit over here and think about how to scale an application from the perspective of network components – load balancers, trunks, VLANs, and switches. The thing is that the scalability patterns leveraged by developers and architects can almost universally be abstracted and applied to the application delivery network – the set of components integrated as a means to ensure availability, performance, and security of applications. That’s why devops is so important and why devops has to bring dev into ops as much as its necessary to bring some ops into dev. There needs to be more cross-over, more discussion, between the two groups if not an entirely new group in order to leverage the knowledge and skills that each has in new and innovative ways.

ABSTRACT and APPLY

So the aforementioned post is just a summary of a longer and more detailed post, but for purposes of this post I think the summary will do with the caveat that the original, “Scalability patterns and an interesting story...” by Jesper Söderlund is a great read that should definitely be on your “to read” list in the very near future.

For now, let’s briefly touch on the scalability patterns and sub-patterns Jesper described with some commentary on how they fit into scalability from a network and application delivery network perspective. The original text from the High Scalability blog are in red(dish) text.

  • Load distribution - Spread the system load across multiple processing units

    This is a horizontal scaling strategy that is well-understood. It may take the form of “clustering” or “load balancing” but in both cases it is essentially an aggregation coupled with a distributed processing model. The secret sauce is almost always in the way in which the aggregation point (strategic point of control) determines how best to distribute the load across the “multiple processing units.”  
    • load balancing / load sharing - Spreading the load across many components with equal properties for handling the request
      This is what most people think of when they hear “load balancing”, it’s just that at the application delivery layer we think in terms of directing application requests (usually HTTP but can just about any application protocol) to equal “servers” (physical or virtual) that handle the request. This is a “scaling out” approach that is most typically associated today with cloud computing and auto-scaling: launch additional clones of applications as virtual instances in order to increase the total capacity of an application. The load balancing distributes requests across all instances based on the configured load balancing algorithm.
    • Partitioning - Spreading the load across many components by routing an individual request to a component that owns that data specific
      This is really where the architecture comes in and where efficiency and performance can be dramatically increased in an image application delivery architecture. Rather than each instance of an application being identical to every other one, each instance (or pool of instances) is designated as the “owner”. This allows for devops to tweak configurations of the underlying operating system, web and application server software for the specific type of request being handled. This is, also, where the difference between “application switching” and “load balancing” becomes abundantly clear as “application switching” is used as a means to determine where to route a particular request which is/can be then load balanced across a pool of resources. It’s a subtle distinction but an important one when architecting not only efficient and fast but resilient and reliable delivery networks.
          • Vertical partitioning - Spreading the load across the functional boundaries of a problem space, separate functions being handled by different processing units
            When it comes to routing application requests we really don’t separate by function unless that function is easily associated with a URI. The most common implementation of vertical partitioning at the application switching layer will be by content. Example: creating resource pools based on the Content-Type HTTP header: images in pool “image servers” and content in pool “content servers”. This allows for greater optimization of the web/application server based on the usage pattern and the content type, which can often also be related to a range of sizes. This also, in a distributed environment, allows architects to leverage say cloud-based storage for static content while maintaining dynamic content (and its associated data stores) on-premise. This kind of hybrid cloud strategy has been postulated as one of the most common use cases since the first wispy edges of cloud were seen on the horizon.
          • Horizontal partitioning - Spreading a single type of data element across many instances, according to some partitioning key, e.g. hashing the player id and doing a modulus operation, etc. Quite often referred to as sharding.
            This sub-pattern is inline with the way in which persistence-based load balancing is accomplished, as well as the handling of object caching. This also describes the way in which you might direct requests received from specific users to designated instances that are specifically designed to handle their unique needs or requirements, such as the separation of “gold” users from “free” users based on some partitioning key which in HTTP land is often a cookie containing the relevant data.
    • Queuing and batch - Achieve efficiencies of scale by processing batches of data, usually because the overhead of an operation is amortized across multiple request 
      I admit defeat in applying this sub-pattern to application delivery. I know, you’re surprised, but this really is very specific to middleware and aside from the ability to leverage queuing for Quality of Service (QoS) at the delivery layer this one is just not fitting in well. If you have an idea how this fits, feel free to let me know – I’d love to be able to apply all the scalability patterns and sub-patterns to a broader infrastructure architecture.
      • Relaxing of data constraints - Many different techniques and trade-offs with regards to the immediacy of processing / storing / access to data fall in this strategy
        This one takes us to storage virtualization and tiering and the way in which data storage and access is intelligently handled in varying properties based on usage and prioritization of the content. If one relaxes the constraints around access times for certain types of data, it is possible to achieve a higher efficiency use of storage by subjugating some content to secondary and tertiary tiers which may not have the same performance attributes as your primary storage tier. And make no mistake, storage virtualization is a part of the application delivery network – has been since its inception – and as cloud computing and virtualization have grown so has the importance of a well-defined storage tiering strategy.

        We can bring this back up to the application layer by considering that a relaxation of data constraints with regards to immediacy of access can be applied by architecting a solution that separates data reads from writes. This implies eventual consistency, as data updated/written to one database must necessarily be replicated to the databases from which reads are, well, read, but that’s part of relaxing a data constraint. This is a technique used by many large, social sites such as Facebook and Plenty of Fish in order to scale the system to the millions upon millions of requests it handles in any given hour.
      • Parallelization - Work on the same task in parallel on multiple processing units
        I’m not going to be able to apply this one either, unless it was in conjunction with optimizing something like MapReduce and SPDY. I’ve been thinking hard about this one, and the problem is the implication that “same task” is really the “same task”, and that processing is distributed. That said, if the actual task can be performed by multiple processing units, then an application delivery controller could certainly be configured to recognize that a specific URL should be essentially sent to some other proxy/solution that performs the actual distribution, but the processing model here deviates sharply from the request-reply paradigm under which most applications today operate.

    DEVOPS CAN MAKE THIS HAPPEN

    I hate to sound-off too much on the “devops” trumpet, but one of the primary ways in which devops will be of significant value in the future is exactly in this type of practical implementation. Only by recognizing that many architectural patterns are applicable to not only application but infrastructure architecture can we start to apply a whole lot of “lessons that have already been learned” by developers and architects to emerging infrastructure architectural models. This abstraction and application from well-understood patterns in application design and architecture will be invaluable in designing the new network; the next iteration of network theory and implementation that will allow it to scale along with the applications it is delivering.


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    About 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.

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