|By Rupert Tagnipes||
|July 6, 2012 03:30 PM EDT||
For many years, companies collected data from various sources that often found its way into relational databases like Oracle and MySQL. However, the rise of the Internet, Web 2.0, and recently social media began an enormous increase in the amount of data created as well as in the type of data. No longer was data relegated to types that easily fit into standard data fields. Instead, it now came in the form of photos, geographic information, chats, Twitter feeds, and emails. The age of Big Data is upon us.
Big Data Beginnings
A study by IDC titled "The Digital Universe Decade" projects a 45-fold increase in annual data by 2020. In 2010, the amount of digital information was 1.2 zettabytes (1 zettabyte equals 1 trillion gigabytes). To put that in perspective, the equivalent of 1.2 zettabytes is a full-length episode of "24" running continuously for 125 million years, according to IDC. That's a lot of data. More important, this data has to go somewhere, and IDC's report projects that by 2020, more than one-third of all digital information created annually will either live in or pass through the cloud. With all this data being created, the challenge will be how to collect, store, and analyze what it means.
Business intelligence (BI) systems have always had to deal with large data sets. Typically the strategy was to pull in "atomic" data at the lowest level of granularity, then aggregate the information to a consumable format for end users. In fact, it was preferable to have a lot of data because you could also drill-down from the aggregation layer to get at the more detailed information, as needed.
In other words, large data sets have been around a long time. And there have been many attempts at trying to manage, wrangle, and tame the onslaught of data being generated from everywhere. But it wasn't until Jeffrey Dean and Sanjay Ghemawat of Google Labs wrote their influential paper on MapReduce in 2003 that Big Data really started to take shape. Google has had to deal with large amounts of raw data (such as crawled documents and web request logs) that needed to be analyzed in a timely manner. Creating MapReduce was their way of being able to abstract the compute parallelization, distribution of data, fault tolerance, and load balancing from developers so they could focus on expressing the computations necessary to analyze the data. This seminal paper reportedly inspired Doug Cutting to develop an open-source implementation of the MapReduce framework called "Hadoop," which was named after his son's toy elephant. Yahoo famously embraced this implementation after hiring Cutting in 2004. Yahoo continued to build upon this technology and first used Hadoop in production in 2008 for its search "webmap," which was an index of all known webpages and all the metadata needed to search them.
One of the key characteristics of Hadoop was that it could run on commodity hardware and automatically distribute jobs. By its nature, it is designed to be fault tolerant so jobs aren't impacted by the failure of a single node. According to an article in Wired magazine about Yahoo's use of Hadoop, "Hadoop could ‘map' tasks across a cluster of machines, splitting them into tiny sub-tasks, before ‘reducing' the results into one master calculation." Soon after, companies like eBay and Facebook were adopting the technology and implementing it internally. Reportedly, Facebook has the largest Hadoop cluster in the world, currently at 30 petabytes (PB).
Although early adopters of Hadoop and other Big Data technologies tended to form around the Internet, social media, and ad networks, Big Data solutions are intended to be general-purpose tools. With most companies now integrating social media into their offerings, the amount of data created internally combined with those extracted externally will only increase. This is an indication that companies from all industries will need to start investigating how to implement Big Data technologies to make use of all this data they're collecting and creating.
Making Sense of Big Data
The problem with the term Big Data is that it's used in a lot of different ways. One definition is that Big Data is any data set that is too large for on-hand data management tools. According to Martin Wattenberg, a scientist at IBM, "The real yardstick ... is how it [Big Data] compares with a natural human limit, like the sum total of all the words that you'll hear in your lifetime." Essentially, what makes something Big Data is that it:
- Is at a large scale (petabytes, not gigabytes)
- Has high velocity (frequently polled, generated, or collected)
- Is unstructured (not only from a relational database)
Collecting that data is a solvable problem, but making sense of it, (particularly in real time), is the challenge that technology tries to solve. This new type of technology is often listed under the title of NoSQL (or Not Only SQL) and includes distributed databases that are a departure from relational databases like Oracle and MySQL. These systems are specifically designed to be able to parallelize compute, distribute data, and create fault tolerance on a large cluster of servers. Some examples of NoSQL projects and software are Cassandra, Hadoop, Membase, MongoDB, and Riak.
The techniques vary, but there is a definite distinction between SQL relational databases and their NoSQL brethren. Most notably, NoSQL systems share the following characteristics:
- Do not use SQL as their primary query language
- May not require fixed table schemas
- May not give full ACID guarantees (Atomicity, Consistency, Isolation, Durability)
- Scale horizontally
Because of the lack of ACID, NoSQL is used when performance and real-time results are more important than consistency. For example, if a company wants to update its website in real time based on an analysis of the behaviors of a particular user interaction with the site, it will most likely turn to NoSQL technologies to solve this use case.
However, this shortcoming doesn't mean relational databases are going away. In fact, it's likely that in larger implementations, NoSQL and SQL will function together. Just as NoSQL was designed to solve a particular use case, so do relational databases solve theirs. Relational databases excel at organizing structured data and are the standard for serving up ad-hoc analytics and BI reporting. In fact, Apache Hadoop even has a separate project called Sqoop that is designed to link Hadoop with structured data stores. Most likely, those who implement NoSQL will maintain their relational databases for legacy systems and for reporting off their NoSQL clusters.
Big Data Moves to the Cloud
The early adopters of Big Data tended to be companies with capital budgets that could be invested into dedicated data centers. However, with the incredible increase in the amount of data generated, collected, and analyzed, smaller companies can take advantage of the cloud and off-load the hardware management to those vendors. Two traits that many of these NoSQL solutions have in common make them a seemingly natural fit for the cloud: One is that the nodes are distributed, and the second is that they run on commodity hardware. The cloud is designed for horizontal scaling and often built on low-cost, commodity hardware, especially at the infrastructure-as-service (IaaS) layer, where customers simply need infrastructure and have the application expertise to build and configure their own Big Data application (whether it is with Hadoop, Cassandra, or any number of products).
Not all clouds are built the same, however. One of the design elements you should look for is the ability for each virtual server in the Big Data cluster to be deployed on different nodes. Although the servers are all on the same private VLAN, ensuring that each server is on different hardware solves for two problems: (1) all the traffic and processing aren't hitting the same hardware, and (2) the cluster is protected against hardware failure because all the servers are distributed. Whether or not the architecture is assuming a name node and data node construct or a Ring design, this setup ensures performance and reliability. In addition, the option of using local storage on the virtual machine and a high-performance network will reduce latency and improve performance.
Given what most users are trying to achieve with Big Data applications-large-scale data sets, large-scale analysis, often in real time-performance is a key factor. Depending on the problem to be solved, users can also leverage a hybrid implementation that combines both virtual and dedicated servers. This setup offers maximum flexibility that balances the elastic, scalable nature of virtual machines with the single-tenancy of dedicated servers. Big Data projects don't happen in a vacuum: Although a NoSQL database can leverage dedicated servers, the app or web servers that present the results of the analysis to end users or that are used to add additional functionality like log file processing can easily be added to as many virtual machines as needed to meet demand. In addition, using the cloud means that users won't need to invest in expensive equipment, pay for power and connectivity, or hire additional resources to maintain hardware. Users simply pay for the infrastructure they need and can scale it as desired over time. The ability to scale up or down to match demand (and to pay only for the infrastructure you actually use) is one of the values of using the cloud for Big Data.
Conclusion: Succeeding with Big Data
With whatever solution you select, you should also take into account the nature of the application and where you'll want to house the processing and the output. The amount of data you collect, analyze, and present will only increase over time. The advantage will go to companies that can collect and analyze this data quickly and efficiently, allowing them to react instantly to customer sentiment and to changing trends in the ever-quickening pace of business. Make sure to select the right infrastructure vendor who can match your performance criteria and has the capacity to grow with you as your data and application needs increase to match the changing demands of your business.
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,...
Jul. 31, 2015 03:00 PM EDT Reads: 493
Jul. 31, 2015 02:00 PM EDT Reads: 287
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.
Jul. 31, 2015 02:00 PM EDT Reads: 190
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.
Jul. 31, 2015 12:30 PM EDT Reads: 164
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 ...
Jul. 31, 2015 11:45 AM EDT Reads: 192
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...
Jul. 31, 2015 11:00 AM EDT Reads: 117
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 ...
Jul. 31, 2015 07:00 AM EDT Reads: 404
Modern DevOps Tool Kit By @Logentries and @NewRelic | @DevOpsSummit #DevOps #Containers #Microservices
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?
Jul. 30, 2015 08:15 PM EDT Reads: 415
Where the Network Got Invited to the Party By @LMacVittie | @DevOpsSummit #DevOps #Docker #Containers #Microservices
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.
Jul. 30, 2015 08:15 PM EDT Reads: 1,772
Designing the IT Architecture of the Future with Adrian Cockcroft | @DevOpsSummit #DevOps #Docker #Containers #Microservices
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.
Jul. 30, 2015 08:00 PM EDT Reads: 784
[slides] A New Architecture for the Internet of Things By @JKirklan | @ThingsExpo @RedHatNews #IoT #M2M #InternetOfThings
Explosive growth in connected devices. Enormous amounts of data for collection and analysis. Critical use of data for split-second decision making and actionable information. All three are factors in making the Internet of Things a reality. Yet, any one factor would have an IT organization pondering its infrastructure strategy. How should your organization enhance its IT framework to enable an Internet of Things implementation? In his session at @ThingsExpo, James Kirkland, Red Hat's Chief Arch...
Jul. 30, 2015 07:30 PM EDT Reads: 1,401
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...
Jul. 30, 2015 05:45 PM EDT Reads: 380
Take the Long View with Digital Transformation By @IoT2040 | @ThingsExpo #IoT #M2M #API #Microservices #InternetOfThings
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...
Jul. 30, 2015 05:00 PM EDT Reads: 1,091
[slides] Workloads and Public Cloud at @CloudExpo By @utollwi | @ProfitBricksUSA #DevOps #Containers #Microservices
Public Cloud IaaS started its life in the developer and startup communities and has grown rapidly to a $20B+ industry, but it still pales in comparison to how much is spent worldwide on IT: $3.6 trillion. In fact, there are 8.6 million data centers worldwide, the reality is many small and medium sized business have server closets and colocation footprints filled with servers and storage gear. While on-premise environment virtualization may have peaked at 75%, the Public Cloud has lagged in adop...
Jul. 30, 2015 04:00 PM EDT Reads: 2,208
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.
Jul. 30, 2015 03:45 PM EDT Reads: 454
MuleSoft has announced the findings of its 2015 Connectivity Benchmark Report on the adoption and business impact of APIs. The findings suggest traditional businesses are quickly evolving into "composable enterprises" built out of hundreds of connected software services, applications and devices. Most are embracing the Internet of Things (IoT) and microservices technologies like Docker. A majority are integrating wearables, like smart watches, and more than half plan to generate revenue with ...
Jul. 30, 2015 02:30 PM EDT Reads: 105
[session] DevOps State of Mind By @RedHatNews | @DevOpsSummit #DevOps #PaaS #Jenkins #Kubernetes #Docker
Rapid innovation, changing business landscapes, and new IT demands force businesses to make changes quickly. The DevOps approach is a way to increase business agility through collaboration, communication, and integration across different teams in the IT organization. In his session at DevOps Summit, Chris Van Tuin, Chief Technologist for the Western US at Red Hat, will discuss: The acceleration of application delivery for the business with DevOps
Jul. 30, 2015 12:45 PM EDT Reads: 1,118
Growth hacking is common for startups to make unheard-of progress in building their business. Career Hacks can help Geek Girls and those who support them (yes, that's you too, Dad!) to excel in this typically male-dominated world. Get ready to learn the facts: Is there a bias against women in the tech / developer communities? Why are women 50% of the workforce, but hold only 24% of the STEM or IT positions? Some beginnings of what to do about it! In her Opening Keynote at 16th Cloud Expo, S...
Jul. 30, 2015 12:00 PM EDT Reads: 2,060
What’s New in the World of Application Analytics By @MikeAnand | @DevOpsSummit #DevOps #API #APM #Microservices
Software is eating the world. The more it eats, the bigger the mountain of data and wealth of valuable insights to digest and act on. Forward facing customer-centric IT organizations, leaders and professionals are looking to answer questions like how much revenue was lost today from platinum users not converting because they experienced poor mobile app performance. This requires a single, real-time pane of glass for end-to-end analytics covering business, customer, and IT operational data.
Jul. 30, 2015 12:00 PM EDT Reads: 1,312
[video] An Interview with @ProfitBricksUSA CEO @AchimWeiss | @CloudExpo #DevOps #Docker #Containers #Microservices
"ProfitBricks was founded in 2010 and we are the painless cloud - and we are also the Infrastructure as a Service 2.0 company," noted Achim Weiss, Chief Executive Officer and Co-Founder of ProfitBricks, in this SYS-CON.tv interview at 16th Cloud Expo, held June 9-11, 2015, at the Javits Center in New York City.
Jul. 30, 2015 11:15 AM EDT Reads: 1,132