Click here to close now.




















Welcome!

Microservices Expo Authors: Pat Romanski, Elizabeth White, Mike Kavis, Ian Khan, Lori MacVittie

Related Topics: @CloudExpo, Java IoT, Microservices Expo, Microsoft Cloud, Containers Expo Blog, Apache

@CloudExpo: Blog Feed Post

Little Data, Big Data and Very Big Data (VBD) or Big BS?

I routinely hear from different people or groups trying to define what is or is not big data

This is an industry trends and perspective piece about big data and little data, industry adoption and customer deployment.

If you are in any way associated with information technology (IT), business, scientific, media and entertainment computing or related areas, you may have heard big data mentioned. Big data has been a popular buzzword bingo topic and term for a couple of years now. Big data is being used to describe new and emerging along with existing types of applications and information processing tools and techniques.

I routinely hear from different people or groups trying to define what is or is not big data and all too often those are based on a particular product, technology, service or application focus. Thus it should be no surprise that those trying to police what is or is not big data will often do so based on what their interest, sphere of influence, knowledge or experience and jobs depend on.

Traveling and big data images

Not long ago while out traveling I ran into a person who told me that big data is new data that did not exist just a few years ago. Turns out this person was involved in geology so I was surprised that somebody in that field was not aware of or working with geophysical, mapping, seismic and other legacy or traditional big data. Turns out this person was basing his statements on what he knew, heard, was told about or on sphere of influence around a particular technology, tool or approach.

Fwiw, if you have not figured out already, like cloud, virtualization and other technology enabling tools and techniques, I tend to take a pragmatic approach vs. becoming latched on to a particular bandwagon (for or against) per say.

Not surprisingly there is confusion and debate about what is or is not big data including if it only applies to new vs. existing and old data. As with any new technology, technique or buzzword bingo topic theme, various parties will try to place what is or is not under the definition to align with their needs, goals and preferences. This is the case with big data where you can routinely find proponents of Hadoop and Map reduce position big data as aligning with the capabilities and usage scenarios of those related technologies for business and other forms of analytics.

SAS software for big data

Not surprisingly the granddaddy of all business analytics, data science and statistic analysis number crunching is the Statistical Analysis Software (SAS) from the SAS Institute. If these types of technology solutions and their peers define what is big data then SAS (not to be confused with Serial Attached SCSI which can be found on the back-end of big data storage solutions) can be considered first generation big data analytics or Big Data 1.0 (BD1 ;) ). That means Hadoop Map Reduce is Big Data 2.0 (BD2 ;) ;) ) if you like, or dislike for that matter.

Funny thing about some fans and proponents or surrogates of BD2 is that they may have heard of BD1 like SAS with a limited understanding of what it is or how it is or can be used. When I worked in IT as a performance and capacity planning analyst focused on servers, storage, network hardware, software and applications I used SAS to crunch various data streams of event, activity and other data from diverse sources. This involved correlating data, running various analytic algorithms on the data to determine response times, availability, usage and other things in support of modeling, forecasting, tuning and trouble shooting. Hmm, sound like first generation big data analytics or Data Center Infrastructure Management (DCIM) and IT Service Management (ITSM) to anybody?

Now to be fair, comparing SAS, SPSS or any number of other BD1 generation tools to Hadoop and Map Reduce or BD2 second generation tools is like comparing apples to oranges, or apples to pears. Lets move on as there is much more to what is big data than simply focus around SAS or Hadoop.

StorageIO industry trends cloud, virtualization and big data

Another type of big data are the information generated, processed, stored and used by applications that result in large files, data sets or objects. Large file, objects or data sets include low resolution and high-definition photos, videos, audio, security and surveillance, geophysical mapping and seismic exploration among others. Then there are data warehouses where transactional data from databases gets moved to for analysis in systems such as those from Oracle, Teradata, Vertica or FX among others. Some of those other tools even play (or work) in both traditional e.g. BD1 and new or emerging BD2 worlds.

This is where some interesting discussions, debates or disagreements can occur between those who latch onto or want to keep big data associated with being something new and usually focused around their preferred tool or technology. What results from these types of debates or disagreements is a missed opportunity for organizations to realize that they might already be doing or using a form of big data and thus have a familiarity and comfort zone with it.

By having a familiarity or comfort zone vs. seeing big data as something new, different, hype or full of FUD (or BS), an organization can be comfortable with the term big data. Often after taking a step back and looking at big data beyond the hype or fud, the reaction is along the lines of, oh yeah, now we get it, sure, we are already doing something like that so lets take a look at some of the new tools and techniques to see how we can extend what we are doing.

Likewise many organizations are doing big bandwidth already and may not realize it thinking that is only what media and entertainment, government, technical or scientific computing, high performance computing or high productivity computing (HPC) does. I'm assuming that some of the big data and big bandwidth pundits will disagree, however if in your environment you are doing many large backups, archives, content distribution, or copying large amounts of data for different purposes that consume big bandwidth and need big bandwidth solutions.

Yes I know, that's apples to oranges and perhaps stretching the limits of what is or can be called big bandwidth based on somebody's definition, taxonomy or preference. Hopefully you get the point that there is diversity across various environments as well as types of data and applications, technologies, tools and techniques.

StorageIO industry trends cloud, virtualization and big data

What about little data then?

I often say that if big data is getting all the marketing dollars to generate industry adoption, then little data is generating all the revenue (and profit or margin) dollars by customer deployment. While tools and technologies related to Hadoop (or Haydoop if you are from HDS) are getting industry adoption attention (e.g. marketing dollars being spent) revenues from customer deployment are growing.

Where big data revenues are strongest for most vendors today are centered around solutions for hosting, storing, managing and protecting big files, big objects. These include scale out NAS solutions for large unstructured data like those from Amplidata, Cray, Dell, Data Direct Networks (DDN), EMC (e.g. Isilon), HP X9000 (IBRIX), IBM SONAS, NetApp, Oracle and Xyratex among others. Then there flexible converged compute storage platforms optimized for analytics and running different software tools such as those from EMC (Greenplum), IBM (Netezza), NetApp (via partnerships) or Oracle among others that can be used for different purposes in addition to supporting Hadoop and Map reduce.

If little data is databases and things not generally lumped into the big data bucket, and if you think or perceive big data only to be Hadoop map reduce based data, then does that mean all the large unstructured non little data is then very big data or VBD?

StorageIO industry trends cloud, virtualization and big data

Of course the virtualization folks might want to if they have not already corner the V for Virtual Big Data. In that case, then instead of Very Big Data, how about very very Big Data (vvBD). How about Ultra-Large Big Data (ULBD), or High-Revenue Big Data (HRBD), granted the HR might cause some to think its unique for Health Records, or Human Resources, both btw leverage different forms of big data regardless of what you see or think big data is.

Does that then mean we should really be calling videos, audio, PACs, seismic, security surveillance video and related data to be VBD? Would this further confuse the market, or the industry or help elevate it to a grander status in terms of size (data file or object capacity, bandwidth, market size and application usage, market revenue and so forth)?

Do we need various industry consortiums, lobbyists or trade groups to go off and create models, taxonomies, standards and dictionaries based on their constituents needs and would they align with those of the customers, after all, there are big dollars flowing around big data industry adoption (marketing).

StorageIO industry trends cloud, virtualization and big data

What does this all mean?

Is Big Data BS?

First let me be clear, big data is not BS, however there is a lot of BS marketing BS by some along with hype and fud adding to the confusion and chaos, perhaps even missed opportunities. Keep in mind that in chaos and confusion there can be opportunity for some.

IMHO big data is real.

There are different variations, use cases and types of products, technologies and services that fall under the big data umbrella. That does not mean everything can or should fall under the big data umbrella as there is also little data.

What this all means is that there are different types of applications for various industries that have big and little data, virtual and very big data from videos, photos, images, audio, documents and more.

Big data is a big buzzword bingo term these days with vendor marketing big dollars being applied so no surprise the buzz, hype, fud and more.

Ok, nuff said, for now...

Cheers Gs

Greg Schulz - Author Cloud and Virtual Data Storage Networking (CRC Press, 2011), The Green and Virtual Data Center (CRC Press, 2009), and Resilient Storage Networks (Elsevier, 2004)

twitter @storageio

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2012 StorageIO All Rights Reserved

Read the original blog entry...

More Stories By Greg Schulz

Greg Schulz is founder of the Server and StorageIO (StorageIO) Group, an IT industry analyst and consultancy firm. Greg has worked with various server operating systems along with storage and networking software tools, hardware and services. Greg has worked as a programmer, systems administrator, disaster recovery consultant, and storage and capacity planner for various IT organizations. He has worked for various vendors before joining an industry analyst firm and later forming StorageIO.

In addition to his analyst and consulting research duties, Schulz has published over a thousand articles, tips, reports and white papers and is a sought after popular speaker at events around the world. Greg is also author of the books Resilient Storage Network (Elsevier) and The Green and Virtual Data Center (CRC). His blog is at www.storageioblog.com and he can also be found on twitter @storageio.

@MicroservicesExpo Stories
SYS-CON Events announced today that the "Second Containers & Microservices Expo" will take place November 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. Containers and microservices have become topics of intense interest throughout the cloud developer and enterprise IT communities.
The Software Defined Data Center (SDDC), which enables organizations to seamlessly run in a hybrid cloud model (public + private cloud), is here to stay. IDC estimates that the software-defined networking market will be valued at $3.7 billion by 2016. Security is a key component and benefit of the SDDC, and offers an opportunity to build security 'from the ground up' and weave it into the environment from day one. In his session at 16th Cloud Expo, Reuven Harrison, CTO and Co-Founder of Tufin,...
Container technology is sending shock waves through the world of cloud computing. Heralded as the 'next big thing,' containers provide software owners a consistent way to package their software and dependencies while infrastructure operators benefit from a standard way to deploy and run them. Containers present new challenges for tracking usage due to their dynamic nature. They can also be deployed to bare metal, virtual machines and various cloud platforms. How do software owners track the usag...
Our guest on the podcast this week is JP Morgenthal, Global Solutions Executive at CSC. We discuss the architecture of microservices and how to overcome the challenge of making different tools work together. We learn about the importance of hiring engineers who can compose services into an integrated system.
Alibaba, the world’s largest ecommerce provider, has pumped over a $1 billion into its subsidiary, Aliya, a cloud services provider. This is perhaps one of the biggest moments in the global Cloud Wars that signals the entry of China into the main arena. Here is why this matters. The cloud industry worldwide is being propelled into fast growth by tremendous demand for cloud computing services. Cloud, which is highly scalable and offers low investment and high computational capabilities to end us...
You often hear the two titles of "DevOps" and "Immutable Infrastructure" used independently. In his session at DevOps Summit, John Willis, Technical Evangelist for Docker, covered the union between the two topics and why this is important. He provided an overview of Immutable Infrastructure then showed how an Immutable Continuous Delivery pipeline can be applied as a best practice for "DevOps." He ended the session with some interesting case study examples.
One of the ways to increase scalability of services – and applications – is to go “stateless.” The reasons for this are many, but in general by eliminating the mapping between a single client and a single app or service instance you eliminate the need for resources to manage state in the app (overhead) and improve the distributability (I can make up words if I want) of requests across a pool of instances. The latter occurs because sessions don’t need to hang out and consume resources that could ...
Microservices has the potential of significantly impacting the way in which developers create applications. It's possible to create applications using microservices faster and more efficiently than other technologies that are currently available. The problem is that many people are suspicious of microservices because of all the technology claims to do. In addition, anytime you start moving things around in an organization, it means changing the status quo and people dislike change. Even so, micr...
"We've just seen a huge influx of new partners coming into our ecosystem, and partners building unique offerings on top of our API set," explained Seth Bostock, Chief Executive Officer at IndependenceIT, in this SYS-CON.tv interview at 16th Cloud Expo, held June 9-11, 2015, at the Javits Center in New York City.
SYS-CON Events announced today that HPM Networks will exhibit 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. For 20 years, HPM Networks has been integrating technology solutions that solve complex business challenges. HPM Networks has designed solutions for both SMB and enterprise customers throughout the San Francisco Bay Area.
Digital Transformation is the ultimate goal of cloud computing and related initiatives. The phrase is certainly not a precise one, and as subject to hand-waving and distortion as any high-falutin' terminology in the world of information technology. Yet it is an excellent choice of words to describe what enterprise IT—and by extension, organizations in general—should be working to achieve. Digital Transformation means: handling all the data types being found and created in the organizat...
JavaScript is primarily a client-based dynamic scripting language most commonly used within web browsers as client-side scripts to interact with the user, browser, and communicate asynchronously to servers. If you have been part of any web-based development, odds are you have worked with JavaScript in one form or another. In this article, I'll focus on the aspects of JavaScript that are relevant within the Node.js environment.
Approved this February by the Internet Engineering Task Force (IETF), HTTP/2 is the first major update to HTTP since 1999, when HTTP/1.1 was standardized. Designed with performance in mind, one of the biggest goals of HTTP/2 implementation is to decrease latency while maintaining a high-level compatibility with HTTP/1.1. Though not all testing activities will be impacted by the new protocol, it's important for testers to be aware of any changes moving forward.
This week, I joined SOASTA as Senior Vice President of Performance Analytics. Given my background in cloud computing and distributed systems operations — you may have read my blogs on CNET or GigaOm — this may surprise you, but I want to explain why this is the perfect time to take on this opportunity with this team. In fact, that’s probably the best way to break this down. To explain why I’d leave the world of infrastructure and code for the world of data and analytics, let’s explore the timing...
Learn how to solve the problem of keeping files in sync between multiple Docker containers. In his session at 16th Cloud Expo, Aaron Brongersma, Senior Infrastructure Engineer at Modulus, discussed using rsync, GlusterFS, EBS and Bit Torrent Sync. He broke down the tools that are needed to help create a seamless user experience. In the end, can we have an environment where we can easily move Docker containers, servers, and volumes without impacting our applications? He shared his results so yo...
Auto-scaling environments, micro-service architectures and globally-distributed teams are just three common examples of why organizations today need automation and interoperability more than ever. But is interoperability something we simply start doing, or does it require a reexamination of our processes? And can we really improve our processes without first making interoperability a requirement for how we choose our tools?
Cloud Migration Management (CMM) refers to the best practices for planning and managing migration of IT systems from a legacy platform to a Cloud Provider through a combination professional services consulting and software tools. A Cloud migration project can be a relatively simple exercise, where applications are migrated ‘as is’, to gain benefits such as elastic capacity and utility pricing, but without making any changes to the application architecture, software development methods or busine...
The Internet of Things. Cloud. Big Data. Real-Time Analytics. To those who do not quite understand what these phrases mean (and let’s be honest, that’s likely to be a large portion of the world), words like “IoT” and “Big Data” are just buzzwords. The truth is, the Internet of Things encompasses much more than jargon and predictions of connected devices. According to Parker Trewin, Senior Director of Content and Communications of Aria Systems, “IoT is big news because it ups the ante: Reach out ...
At DevOps Summit NY there’s been a whole lot of talk about not just DevOps, but containers, IoT, and microservices. Sessions focused not just on the cultural shift needed to grow at scale with a DevOps approach, but also made sure to include the network ”plumbing” needed to ensure success as applications decompose into the microservice architectures enabling rapid growth and support for the Internet of (Every)Things.
Our guest on the podcast this week is Adrian Cockcroft, Technology Fellow at Battery Ventures. We discuss what makes Docker and Netflix highly successful, especially through their use of well-designed IT architecture and DevOps.