Welcome!

Microservices Expo Authors: Pat Romanski, Liz McMillan, Mamoon Yunus, Elizabeth White, Mehdi Daoudi

Related Topics: @BigDataExpo, Java IoT, Microservices Expo, Containers Expo Blog, @CloudExpo, SDN Journal

@BigDataExpo: Article

Archiving the Big Data Old Tail

At any point in time, half of your Big Data are more than two years old

Scenario #1: out of the blue, your boss calls, looking for some long-forgotten entry in a spreadsheet from 1989. Where do you look? Or consider scenario #2: said boss calls again, only this time she wants you to analyze customer purchasing behavior...going back to 1980. Similar problem, only instead of finding a single datum, you must find years of ancient information and prepare it for analysis with a modern business intelligence tool.

The answer, of course, is archiving. Fortunately, you (or your predecessor, or predecessor's predecessor) have been archiving important-or potentially important-corporate data since your organization first started using computers back in the 1960s. So all you have to do to keep your boss happy is find the appropriate archives, recover the necessary data, and you're good to go, right?

Not so fast. There are a number of gotchas to this story, some more obvious than others. Cloud to the rescue? Perhaps, but many archiving challenges remain, and the Cloud actually introduces some new speed bumps as well. Now factor in Big Data. Sure, Big Data are big, so archiving Big Data requires a big archive. Lucky you-vendors have already been knocking on your door peddling Big Data archiving solutions. Now can you finally breathe easy? Maybe, maybe not. Here's why.

Archiving: The Long View
So much of our digital lives have taken place over the last twenty years or so that we forget that digital computing dates back to the 1940s-and furthermore, we forget that this sixty-odd year lifetime of the Information Age is really only the first act of perhaps centuries of computing before humankind either evolves past zeroes and ones altogether or kills itself off in the process. Our technologies for archiving information, however, are woefully shortsighted, for several reasons:

  • Hardware obsolescence (three to five years) - Using a hard drive or tape drive for archiving? It won't be long till the hardware is obsolete. You may get more life out of the gear you own, but one it wears out, you'll be stuck. Anyone who archived to laser disk in the 1980s has been down this road.
  • File format obsolescence (five to ten years) - True, today's Office products can probably read that file originally saved in the Microsoft Excel version 1 file format back in the day, but what about those VisiCalc or Lotus 123 files? Tools that will convert such files to their modern equivalents will eventually grow increasingly scarce, and you always risk the possibility that they won't handle the conversion properly, leading to data corruption. If your data are encrypted, then your encryption format falls into the file format obsolescence bucket as well. And what about the programs themselves? From simple spreadsheet formulas to complex legacy spaghetti code, how do you archive algorithms in an obsolescence-proof format?
  • Media obsolescence (ten to fifteen years) - CD-ROMs and digital backup tapes have an expected lifetime. Keeping them cool and dry can extend their life, but actually using them will shorten it. Do you really want to rely upon a fifteen-year-old backup tape for critical information?
  • Computing paradigm obsolescence (fifty years perhaps; it's anybody's guess) - will quantum computing or biological processors or some other futuristic gear drive binary digital technologies into the Stone Age? Only time will tell. But if you are forward thinking enough to archive information for the 22nd century, there's no telling what you'll need to do to maintain the viability of your archives in a post-binary world.

Cloud to the Rescue?
On the surface, letting your Cloud Service Provider (CSP) archive your data solves many of these issues. Not only are the new archiving services like Amazon Glacier impressively cost-effective, but we can feel reasonably comfortable counting on today's CSPs to migrate our data from one hardware/media platform to the next over time as technology advances. So, can Cloud solve all your archiving issues?

At some point the answer may be yes, but Cloud Computing is still far too immature to jump to such a conclusion. Will your CSP still be in business decades from now? As the CSP market undergoes its inevitable consolidation phase, will the new CSP who bought out your old CSP handle your archive properly? Only time will tell.

But even if the CSPs rise to the archiving challenge, you may still have the file format challenge. Sure, archiving those old Lotus 123 files in the Cloud is a piece of cake, but that doesn't mean that your CSP will return them in Excel version 21.3 format ten years hence-an unfortunate and unintentional example of garbage in the Cloud.

The Big Data Old Tail
You might think that the challenges inherent in archiving Big Data are simply a matter of degree: bigger storage for bigger data sets, right? But thinking of Big Data as little more than extra-large data sets misses the big picture of the importance of Big Data.

The point to Big Data is that the indicated data sets continue to grow in size on an ongoing basis, continually pushing the limits of existing technology. The more capacity available for storage and processing, the larger the data sets we end up with. In other words, Big Data are by definition a moving target.

One familiar estimate states that the quantity of data in the world doubles every two years. Your organization's Big Data may grow somewhat faster or slower than this convenient benchmark, but in any case, the point is that Big Data growth is exponential. So, taking the two-year doubling factor as a rule of thumb, we can safely say that at any point in time, half of your Big Data are less than two years old, while the other half of your Big Data are more than two years old. And of course, this ZapFlash is concerned with the older half.

The Big Data archiving challenge, therefore, is breaking down the more-than-two-years-old Big Data sets. Remember that this two-year window is true at any point in time. Thinking about the problem mathematically, then, you can conclude that a quarter of your Big Data are more than four years old, an eighth are more than six years old, etc.

Combine this math with the lesson of the first part of this ZapFlash, and a critical point emerges: byte for byte, the cost of maintaining usable archives increases the older those archives become. And yet, the relative size of those archives is vanishingly small relative to today's and tomorrow's Big Data. Furthermore, this problem will only get worse over time, because the size of the Old Tail continues to grow exponentially.

We call this Big Data archiving problem the Big Data Old Tail. Similar to the Long Tail argument, which focuses on the value inherent in summing up the Long Tail of customer demand for niche products, the Big Data Old Tail focuses on the costs inherent in maintaining archives of increasingly small, yet increasingly costly data as we struggle to deal with older and older information. True, perhaps the fact that the Old Tail data sets from a particular time period are small will compensate for the fact that they are costly to archive, but remember that the Old Tail continues to grow over time. Unless we deal with the Old Tail, it threatens to overwhelm us.

The ZapThink Take
The obvious question that comes to mind is whether we need to save all those old data sets anyway. After all, who cares about, say, purchasing data from 1982? And of course, you may have a business reason for deleting old information. Since information you preserve may be subject to lawsuits or other unpleasantness, you may wish to delete data once it's legal to do so.

Fair enough. But there are perhaps far more examples of Big Data sets that your organization will wish to preserve indefinitely than data sets you're happy to delete. From scientific data to information on market behavior to social trends, the richness of our Big Data do not simply depend on the information from the last year or two or even ten. After all, if we forget the mistakes of the past then we are doomed to repeat them. Crunching today's Big Data can give us business intelligence, but only by crunching yesterday's Big Data as well can we ever expect to glean wisdom from our information.

More Stories By Jason Bloomberg

Jason Bloomberg is the leading expert on architecting agility for the enterprise. As president of Intellyx, Mr. Bloomberg brings his years of thought leadership in the areas of Cloud Computing, Enterprise Architecture, and Service-Oriented Architecture to a global clientele of business executives, architects, software vendors, and Cloud service providers looking to achieve technology-enabled business agility across their organizations and for their customers. His latest book, The Agile Architecture Revolution (John Wiley & Sons, 2013), sets the stage for Mr. Bloomberg’s groundbreaking Agile Architecture vision.

Mr. Bloomberg is perhaps best known for his twelve years at ZapThink, where he created and delivered the Licensed ZapThink Architect (LZA) SOA course and associated credential, certifying over 1,700 professionals worldwide. He is one of the original Managing Partners of ZapThink LLC, the leading SOA advisory and analysis firm, which was acquired by Dovel Technologies in 2011. He now runs the successor to the LZA program, the Bloomberg Agile Architecture Course, around the world.

Mr. Bloomberg is a frequent conference speaker and prolific writer. He has published over 500 articles, spoken at over 300 conferences, Webinars, and other events, and has been quoted in the press over 1,400 times as the leading expert on agile approaches to architecture in the enterprise.

Mr. Bloomberg’s previous book, Service Orient or Be Doomed! How Service Orientation Will Change Your Business (John Wiley & Sons, 2006, coauthored with Ron Schmelzer), is recognized as the leading business book on Service Orientation. He also co-authored the books XML and Web Services Unleashed (SAMS Publishing, 2002), and Web Page Scripting Techniques (Hayden Books, 1996).

Prior to ZapThink, Mr. Bloomberg built a diverse background in eBusiness technology management and industry analysis, including serving as a senior analyst in IDC’s eBusiness Advisory group, as well as holding eBusiness management positions at USWeb/CKS (later marchFIRST) and WaveBend Solutions (now Hitachi Consulting).

@MicroservicesExpo Stories
In his session at 20th Cloud Expo, Scott Davis, CTO of Embotics, discussed how automation can provide the dynamic management required to cost-effectively deliver microservices and container solutions at scale. He also discussed how flexible automation is the key to effectively bridging and seamlessly coordinating both IT and developer needs for component orchestration across disparate clouds – an increasingly important requirement at today’s multi-cloud enterprise.
IT organizations are moving to the cloud in hopes to approve efficiency, increase agility and save money. Migrating workloads might seem like a simple task, but what many businesses don’t realize is that application migration criteria differs across organizations, making it difficult for architects to arrive at an accurate TCO number. In his session at 21st Cloud Expo, Joe Kinsella, CTO of CloudHealth Technologies, will offer a systematic approach to understanding the TCO of a cloud application...
API Security has finally entered our security zeitgeist. OWASP Top 10 2017 - RC1 recognized API Security as a first class citizen by adding it as number 10, or A-10 on its list of web application vulnerabilities. We believe this is just the start. The attack surface area offered by API is orders or magnitude larger than any other attack surface area. Consider the fact the APIs expose cloud services, internal databases, application and even legacy mainframes over the internet. What could go wrong...
The goal of Continuous Testing is to shift testing left to find defects earlier and release software faster. This can be achieved by integrating a set of open source functional and performance testing tools in the early stages of your software delivery lifecycle. There is one process that binds all application delivery stages together into one well-orchestrated machine: Continuous Testing. Continuous Testing is the conveyer belt between the Software Factory and production stages. Artifacts are m...
In IT, we sometimes coin terms for things before we know exactly what they are and how they’ll be used. The resulting terms may capture a common set of aspirations and goals – as “cloud” did broadly for on-demand, self-service, and flexible computing. But such a term can also lump together diverse and even competing practices, technologies, and priorities to the point where important distinctions are glossed over and lost.
In his session at @DevOpsSummit at 20th Cloud Expo, Kelly Looney, director of DevOps consulting for Skytap, showed how an incremental approach to introducing containers into complex, distributed applications results in modernization with less risk and more reward. He also shared the story of how Skytap used Docker to get out of the business of managing infrastructure, and into the business of delivering innovation and business value. Attendees learned how up-front planning allows for a clean sep...
Most companies are adopting or evaluating container technology - Docker in particular - to speed up application deployment, drive down cost, ease management and make application delivery more flexible overall. As with most new architectures, this dream takes a lot of work to become a reality. Even when you do get your application componentized enough and packaged properly, there are still challenges for DevOps teams to making the shift to continuous delivery and achieving that reduction in cost ...
Enterprise architects are increasingly adopting multi-cloud strategies as they seek to utilize existing data center assets, leverage the advantages of cloud computing and avoid cloud vendor lock-in. This requires a globally aware traffic management strategy that can monitor infrastructure health across data centers and end-user experience globally, while responding to control changes and system specification at the speed of today’s DevOps teams. In his session at 20th Cloud Expo, Josh Gray, Chie...
"At the keynote this morning we spoke about the value proposition of Nutanix, of having a DevOps culture and a mindset, and the business outcomes of achieving agility and scale, which everybody here is trying to accomplish," noted Mark Lavi, DevOps Solution Architect at Nutanix, in this SYS-CON.tv interview at @DevOpsSummit at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
We have already established the importance of APIs in today’s digital world (read about it here). With APIs playing such an important role in keeping us connected, it’s necessary to maintain the API’s performance as well as availability. There are multiple aspects to consider when monitoring APIs, from integration to performance issues, therefore a general monitoring strategy that only accounts for up-time is not ideal.
Web services have taken the development world by storm, especially in recent years as they've become more and more widely adopted. There are naturally many reasons for this, but first, let's understand what exactly a web service is. The World Wide Web Consortium (W3C) defines "web of services" as "message-based design frequently found on the Web and in enterprise software". Basically, a web service is a method of sending a message between two devices through a network. In practical terms, this ...
In his session at 20th Cloud Expo, Mike Johnston, an infrastructure engineer at Supergiant.io, discussed how to use Kubernetes to set up a SaaS infrastructure for your business. Mike Johnston is an infrastructure engineer at Supergiant.io with over 12 years of experience designing, deploying, and maintaining server and workstation infrastructure at all scales. He has experience with brick and mortar data centers as well as cloud providers like Digital Ocean, Amazon Web Services, and Rackspace. H...
All organizations that did not originate this moment have a pre-existing culture as well as legacy technology and processes that can be more or less amenable to DevOps implementation. That organizational culture is influenced by the personalities and management styles of Executive Management, the wider culture in which the organization is situated, and the personalities of key team members at all levels of the organization. This culture and entrenched interests usually throw a wrench in the work...
As many know, the first generation of Cloud Management Platform (CMP) solutions were designed for managing virtual infrastructure (IaaS) and traditional applications. But that’s no longer enough to satisfy evolving and complex business requirements. In his session at 21st Cloud Expo, Scott Davis, Embotics CTO, will explore how next-generation CMPs ensure organizations can manage cloud-native and microservice-based application architectures, while also facilitating agile DevOps methodology. He wi...
When you focus on a journey from up-close, you look at your own technical and cultural history and how you changed it for the benefit of the customer. This was our starting point: too many integration issues, 13 SWP days and very long cycles. It was evident that in this fast-paced industry we could no longer afford this reality. We needed something that would take us beyond reducing the development lifecycles, CI and Agile methodologies. We made a fundamental difference, even changed our culture...
We have Continuous Integration and we have Continuous Deployment, but what’s continuous across all of what we do is people. Even when tasks are automated, someone wrote the automation. So, Jayne Groll evangelizes about Continuous Everyone. Jayne is the CEO of the DevOps Institute and the author of Agile Service Management Guide. She talked about Continuous Everyone at the 2016 All Day DevOps conference. She describes it as "about people, culture, and collaboration mapped into your value streams....
These days, change is the only constant. In order to adapt and thrive in an ever-advancing and sometimes chaotic workforce, companies must leverage intelligent tools to streamline operations. While we're only at the dawn of machine intelligence, using a workflow manager will benefit your company in both the short and long term. Think: reduced errors, improved efficiency and more empowered employees-and that's just the start. Here are five other reasons workflow automation is leading a revolution...
Docker is sweeping across startups and enterprises alike, changing the way we build and ship applications. It's the most prominent and widely known software container platform, and it's particularly useful for eliminating common challenges when collaborating on code (like the "it works on my machine" phenomenon that most devs know all too well). With Docker, you can run and manage apps side-by-side - in isolated containers - resulting in better compute density. It's something that many developer...
While some vendors scramble to create and sell you a fancy solution for monitoring your spanking new Amazon Lambdas, hear how you can do it on the cheap using just built-in Java APIs yourself. By exploiting a little-known fact that Lambdas aren’t exactly single-threaded, you can effectively identify hot spots in your serverless code. In his session at @DevOpsSummit at 21st Cloud Expo, Dave Martin, Product owner at CA Technologies, will give a live demonstration and code walkthrough, showing how ...
Did you know that you can develop for mainframes in Java? Or that the testing and deployment can be automated across mobile to mainframe? In his session and demo at @DevOpsSummit at 21st Cloud Expo, Dana Boudreau, a Senior Director at CA Technologies, will discuss how increasingly teams are developing with agile methodologies, using modern development environments, and automating testing and deployments, mobile to mainframe.