Java IoT Authors: Liz McMillan, Yeshim Deniz, Sematext Blog, Carmen Gonzalez, TJ Randall

Related Topics: @BigDataExpo, Java IoT, Linux Containers, Agile Computing, @CloudExpo, SDN Journal

@BigDataExpo: Blog Feed Post

Scaling Big Data Fabrics

The size of the network might be the least interesting aspect of scaling Big Data fabrics

When people talk about Big Data, the emphasis is usually on the Big. Certainly, Big Data applications are distributed largely because the size of the data on which computations are executed warrants more than a typical application can handle. But scaling the network that provides connectivity between Big Data nodes is not just about creating massive interconnects.

In fact, the size of the network might be the least interesting aspect of scaling Big Data fabrics.

Just how big is Big Data?

Not that long ago, I asked the question: how large is a typical Big Data deployment? I was expecting, as I suspect many people are, that the Big in the title meant that the deployments would be, in a word, big. But the average Big Data deployment is actually far smaller than most people realize. I grabbed a list from HadoopWizard in an article dating back to last year.

What is remarkable about this list is just how unremarkable the sizes of the deployments are. Sure, the list is dated, and deployments have certainly gotten larger. And yes, companies like Yahoo! are pushing scaling limits. But the average deployment if you take Yahoo! out is a mere 113 nodes. Even if every node is multi-homed to two switches, this means the average deployment could be handled by 4 access switches.

Even if every deployment quadrupled, you would still only be talking about 16-access-switch deployments. When our industry talks about scaling, we usually think well beyond 16 switches.

Is scaling an issue?

So if deployments are small, does that mean scaling is a solved issue? The answer is both yes and no. If the end game is building individual networks for each Big Data application, then yes. While the web scale companies will always need more, the vast majority of customers will be well-served by the scaling limits that are around today.

But the issue with Big Data is that it isn’t really just Big Data. When we talk about Big Data, we usually ought to be using a different moniker. For most people, Big Data is less about Hadoop and more about clustered applications (at least so far as the network is concerned). By expanding the definition to clustered applications, you move past Hadoop and into clustered compute and even clustered storage environments. Anything clustered has a dependency on some kind of interconnect.

The challenge in clustered environments

The challenge of all these types of clustered environments is that their requirements vary. For Hadoop, job completion times are dominated by the compute side of things, so the network is really about providing a congestion-free interconnect that is always available. For clustered compute, latency might be more important. And for multi-tenant environments, it might be most important to isolate traffic. Whatever the application, the point is that the requirements are highly contextual.

Which brings us back to scaling.

The real issue in scaling Big Data fabrics is less about making a small interconnect larger. Networks are not going to scale along the lines of single applications (or at least they shouldn’t). The actual scaling challenge is plotting a course from a single Big Data application to an environment that hosts multiple clustered applications, each with different requirements.

This might seem dead simple, but it isn’t. When people deploy Big Data applications today, the Big part leads people to purpose-build architecture with massive data workloads in mind. In many cases, this includes building out separate networks aimed at specific workloads.

But even in the best cases, Hadoop makes use of things like rack awareness, which help provide application resilience while minimizing traffic across the network. Regardless of whether you view this as for the application or for the network, the result is that proximity and locality are built into the infrastructure. This creates interesting considerations (and potentially limitations) when expanding. If you want to grow a cluster, you can’t just use any available server in the datacenter; there are servers that are more preferable than others based solely on their physical location.

Scalability is more than scaling

Making a scalable interconnect for these types of clustered applications is more than just supporting a large (or as I mentioned previously, not so large) number of nodes. The objective for scalability is to provide a graceful path from start to finish. This means architectures need to consider not just what the ending state is but also how to get from here to there.

With Hadoop, this means that things like locality have to be an explicit consideration in architecting the interconnect. Is the right answer a bunch of cross-connects zigzagging across the datacenter? Maybe. Or it might be a different architectural approach to providing interconnect between clustered servers.

Additionally, it isn’t just about one application. Architecting for bandwidth because you have a Hadoop-y application is great, but what if the next clustered application is latency-sensitive? Or if it brings with it a set of auditing and compliance requirements more typical of HIPAA-style applications?

If the architecture doesn’t explicitly consider how to expand beyond a single application, even if it can grow to thousands of switches, it won’t really matter.

The bottom line

The punch line here is that scaling is not only about growing larger. It also means potentially growing more diverse. And if there is one thing that the Hadoop deployment numbers tell me, it’s that people are still experimenting. If you are still experimenting, how can you predict with certainty what the next 5 or 10 years will mean in terms of applications for your business? You can’t. Which means that the most important architectural objective might go well beyond the number of switches in a deployment. Scalability could be about building flexibility into you datacenter. How do you get a bunch of different purpose-built capabilities into a single, general-purpose network? Answering that might be the real key to determining how to scale Big Data fabrics.

[Today’s fun fact: It is against the law to use the Star Spangled Banner as dance music in Massachusetts. There go my party plans!]

The post Scaling Big Data fabrics appeared first on Plexxi.

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
More and more brands have jumped on the IoT bandwagon. We have an excess of wearables – activity trackers, smartwatches, smart glasses and sneakers, and more that track seemingly endless datapoints. However, most consumers have no idea what “IoT” means. Creating more wearables that track data shouldn't be the aim of brands; delivering meaningful, tangible relevance to their users should be. We're in a period in which the IoT pendulum is still swinging. Initially, it swung toward "smart for smar...
Virgil consists of an open-source encryption library, which implements Cryptographic Message Syntax (CMS) and Elliptic Curve Integrated Encryption Scheme (ECIES) (including RSA schema), a Key Management API, and a cloud-based Key Management Service (Virgil Keys). The Virgil Keys Service consists of a public key service and a private key escrow service. 

The Internet of Things (IoT), in all its myriad manifestations, has great potential. Much of that potential comes from the evolving data management and analytic (DMA) technologies and processes that allow us to gain insight from all of the IoT data that can be generated and gathered. This potential may never be met as those data sets are tied to specific industry verticals and single markets, with no clear way to use IoT data and sensor analytics to fulfill the hype being given the IoT today.
Data is the fuel that drives the machine learning algorithmic engines and ultimately provides the business value. In his session at Cloud Expo, Ed Featherston, a director and 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.
What happens when the different parts of a vehicle become smarter than the vehicle itself? As we move toward the era of smart everything, hundreds of entities in a vehicle that communicate with each other, the vehicle and external systems create a need for identity orchestration so that all entities work as a conglomerate. Much like an orchestra without a conductor, without the ability to secure, control, and connect the link between a vehicle’s head unit, devices, and systems and to manage the ...
The best way to leverage your Cloud Expo presence as a sponsor and exhibitor is to plan your news announcements around our events. The press covering Cloud Expo and @ThingsExpo will have access to these releases and will amplify your news announcements. More than two dozen Cloud companies either set deals at our shows or have announced their mergers and acquisitions at Cloud Expo. Product announcements during our show provide your company with the most reach through our targeted audiences.
Machine Learning helps make complex systems more efficient. By applying advanced Machine Learning techniques such as Cognitive Fingerprinting, wind project operators can utilize these tools to learn from collected data, detect regular patterns, and optimize their own operations. In his session at 18th Cloud Expo, Stuart Gillen, Director of Business Development at SparkCognition, discussed how research has demonstrated the value of Machine Learning in delivering next generation analytics to impr...
@ThingsExpo has been named the Top 5 Most Influential Internet of Things Brand by Onalytica in the ‘The Internet of Things Landscape 2015: Top 100 Individuals and Brands.' Onalytica analyzed Twitter conversations around the #IoT debate to uncover the most influential brands and individuals driving the conversation. Onalytica captured data from 56,224 users. The PageRank based methodology they use to extract influencers on a particular topic (tweets mentioning #InternetofThings or #IoT in this ...
For basic one-to-one voice or video calling solutions, WebRTC has proven to be a very powerful technology. Although WebRTC’s core functionality is to provide secure, real-time p2p media streaming, leveraging native platform features and server-side components brings up new communication capabilities for web and native mobile applications, allowing for advanced multi-user use cases such as video broadcasting, conferencing, and media recording.
Amazon has gradually rolled out parts of its IoT offerings, but these are just the tip of the iceberg. In addition to optimizing their backend AWS offerings, Amazon is laying the ground work to be a major force in IoT - especially in the connected home and office. In his session at @ThingsExpo, Chris Kocher, founder and managing director of Grey Heron, explained how Amazon is extending its reach to become a major force in IoT by building on its dominant cloud IoT platform, its Dash Button strat...
SYS-CON Events announced today that SoftNet Solutions will exhibit at the 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. SoftNet Solutions specializes in Enterprise Solutions for Hadoop and Big Data. It offers customers the most open, robust, and value-conscious portfolio of solutions, services, and tools for the shortest route to success with Big Data. The unique differentiator is the ability to architect and ...
A critical component of any IoT project is what to do with all the data being generated. This data needs to be captured, processed, structured, and stored in a way to facilitate different kinds of queries. Traditional data warehouse and analytical systems are mature technologies that can be used to handle certain kinds of queries, but they are not always well suited to many problems, particularly when there is a need for real-time insights.
DevOps is being widely accepted (if not fully adopted) as essential in enterprise IT. But as Enterprise DevOps gains maturity, expands scope, and increases velocity, the need for data-driven decisions across teams becomes more acute. DevOps teams in any modern business must wrangle the ‘digital exhaust’ from the delivery toolchain, "pervasive" and "cognitive" computing, APIs and services, mobile devices and applications, the Internet of Things, and now even blockchain. In this power panel at @...
One of biggest questions about Big Data is “How do we harness all that information for business use quickly and effectively?” Geographic Information Systems (GIS) or spatial technology is about more than making maps, but adding critical context and meaning to data of all types, coming from all different channels – even sensors. In his session at @ThingsExpo, William (Bill) Meehan, director of utility solutions for Esri, will take a closer look at the current state of spatial technology and ar...
Everyone knows that truly innovative companies learn as they go along, pushing boundaries in response to market changes and demands. What's more of a mystery is how to balance innovation on a fresh platform built from scratch with the legacy tech stack, product suite and customers that continue to serve as the business' foundation. In his General Session at 19th Cloud Expo, Michael Chambliss, Head of Engineering at ReadyTalk, will discuss why and how ReadyTalk diverted from healthy revenue an...
SYS-CON Events announced today that Streamlyzer will exhibit at the 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Streamlyzer is a powerful analytics for video streaming service that enables video streaming providers to monitor and analyze QoE (Quality-of-Experience) from end-user devices in real time.
You have great SaaS business app ideas. You want to turn your idea quickly into a functional and engaging proof of concept. You need to be able to modify it to meet customers' needs, and you need to deliver a complete and secure SaaS application. How could you achieve all the above and yet avoid unforeseen IT requirements that add unnecessary cost and complexity? You also want your app to be responsive in any device at any time. In his session at 19th Cloud Expo, Mark Allen, General Manager of...
SYS-CON Media announced today that @WebRTCSummit Blog, the largest WebRTC resource in the world, has been launched. @WebRTCSummit Blog offers top articles, news stories, and blog posts from the world's well-known experts and guarantees better exposure for its authors than any other publication. @WebRTCSummit Blog can be bookmarked ▸ Here @WebRTCSummit conference site can be bookmarked ▸ Here
In past @ThingsExpo presentations, Joseph di Paolantonio has explored how various Internet of Things (IoT) and data management and analytics (DMA) solution spaces will come together as sensor analytics ecosystems. This year, in his session at @ThingsExpo, Joseph di Paolantonio from DataArchon, will be adding the numerous Transportation areas, from autonomous vehicles to “Uber for containers.” While IoT data in any one area of Transportation will have a huge impact in that area, combining sensor...
Almost everyone sees the potential of Internet of Things but how can businesses truly unlock that potential. The key will be in the ability to discover business insight in the midst of an ocean of Big Data generated from billions of embedded devices via Systems of Discover. Businesses will also need to ensure that they can sustain that insight by leveraging the cloud for global reach, scale and elasticity.