Click here to close now.

Welcome!

Cloud Expo Authors: Carmen Gonzalez, Michael Jannery, AppDynamics Blog, Harry Trott, Roger Strukhoff

Related Topics: Cloud Expo

Cloud Expo: Blog Post

The Economics of Big Data: Why Faster Software is Cheaper

Faster means better and cheaper - lower latency and lower cost!

In big data computing, and more generally in all commercial highly parallel software systems, speed matters more than just about anything else. The reason is straightforward, and has been known for decades.

Put very simply, when it comes to massively parallel software of the kind need to handle big data, fast is both better AND cheaper. Faster means lower latency AND lower cost.

At first this may seem counterintuitive. A high-end sports car will be much faster than a standard family sedan, but the family sedan may be much cheaper. Cheaper to buy, and cheaper to run. But massively parallel software running on commodity hardware is a quite different type of product from a car. In general, the faster it goes, the cheaper it is to run.

Time Is Money
As has been noted many times in the history of computing, if you are a factor of 50x slower, then you will need 50x more nodes to run at the same speed (even assuming perfect parallelization), or your computation will need 50x more time. In either case, it will also be much more likely that you will experience at least one of your nodes crashing during a computation. This is not to argue that automatic fault tolerance and recovery should be ignored in the pursuit of speed, but rather that these two factors need to be carefully balanced. Good design in massively parallel systems is about achieving maximum speed along with the ability to recover from a given expected level of hardware failure, via checkpointing.

The key phrase here is "a given expected level of hardware failure". In certain types of peer-to-peer services which take advantage of idle PC capacity, it is necessary to assume that all machines are extremely unreliable and may go offline at any time. However, in a commercial big data cluster it may be reasonably asssumed that almost all machines will be available almost all of the time. This means that a much more optimistic point in the design space can be chosen, one which is designed much more for speed than for pathological failure scenarios.

The MapReduce model is an example of a model where speed has been sacrificed in a major way in order to achieve scalability on very unreliable hardware. As we have noted, while this is acceptable in certain types of free peer-to-peer services, it is much less acceptable in commercial big data systems deployed at scale.

Google, the inventors of the model, were the first to recognize the throughput and latency problems with the MapReduce model. To get the realtime performance they required, they recently replaced MapReduce in their Google Instant search engine.

The MapReduce model of Apache Hadoop is slow. In fact, it's very slow compared to, for example, the kinds of MPI or BSP clusters that have been routinely used in supercomputing for more than 15 years. On exactly the same hardware, MapReduce can be several orders of magnitude slower than MPI or BSP. By using MPI rather than MapReduce, HadoopBI gives customers the best possible big data solution, not only in terms of performance - massive throughput and extremely low latency - but also in terms of economics. HadoopBI is not just the fastest Big Data BI solution, it is also the cheapest at scale.

It's Free, But Is It Fast Enough?
Another frequently misunderstood element of big data economics concerns so-called "free" software. It has been argued by some that, since big data software needs to be run on many nodes, it is really important to have software that is free. Again this is an extreme oversimplification that ignores the dominant cost issues in big data economics. At large scale, software costs will in general be much smaller than hardware or cloud costs. And commercial software vendors should ensure that they are, if they want to stay in business.

Consider the following small-scale example. A company needs to process big data continuously in order to maximize competitive advantage. For simplicity, we will assume that the cost of running a single server (in-house or cloud) for one hour is $1, and that the company has a choice between two big data software systems - system A costs $1,000 per server and system B is free, but system A is 8x faster. Choosing system A, the company requires 5 servers, working continuously, to achieve the throughput required. However, if the company chooses system B, it will require 40 servers running continuously.

Simple arithmetic shows that within just six days, the initial cost of system A has been recovered, and from then on system A gives the company massive cost savings. Even if system A is only 2x or 3x faster and more efficient than system B, the initial cost will still be recovered in a matter of a few weeks.

The economic advantages of speed at scale are magnified even more in large-scale big data systems where, with volume licensing discounts, the payback time for super-fast software is even shorter.

The lesson of the above example is simple and very important. In parallel systems, speed at scale is king, as speed equates to efficiency, and efficiency equates to massive cost savings at scale. So, to be relevant for large scale production deployments, free parallel software has to be at least as fast and efficient as the best commercial software, otherwise the economics will be solidly against it. Some examples of free software, such as the Linux operating system, have achieved this goal. It remains to be seen whether this will also be the case with highly parallel big data software. In the meantime, it's important to remember that "free software is cheap, but fast software can be even cheaper".

More Stories By Bill McColl

Bill McColl left Oxford University to found Cloudscale. At Oxford he was Professor of Computer Science, Head of the Parallel Computing Research Center, and Chairman of the Computer Science Faculty. Along with Les Valiant of Harvard, he developed the BSP approach to parallel programming. He has led research, product, and business teams, in a number of areas: massively parallel algorithms and architectures, parallel programming languages and tools, datacenter virtualization, realtime stream processing, big data analytics, and cloud computing. He lives in Palo Alto, CA.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


@CloudExpo Stories
There are many considerations when moving applications from on-premise to cloud. It is critical to understand the benefits and also challenges of this migration. A successful migration will result in lower Total Cost of Ownership, yet offer the same or higher level of robustness. In his session at 15th Cloud Expo, Michael Meiner, an Engineering Director at Oracle, Corporation, will analyze a range of cloud offerings (IaaS, PaaS, SaaS) and discuss the benefits/challenges of migrating to each of...
Platform-as-a-Service (PaaS) is a technology designed to make DevOps easier and allow developers to focus on application development. The PaaS takes care of provisioning, scaling, HA, and other cloud management aspects. Apache Stratos is a PaaS codebase developed in Apache and designed to create a highly productive developer environment while also supporting powerful deployment options. Integration with the Docker platform, CoreOS Linux distribution, and Kubernetes container management system ...
Cloud data governance was previously an avoided function when cloud deployments were relatively small. With the rapid adoption in public cloud – both rogue and sanctioned, it’s not uncommon to find regulated data dumped into public cloud and unprotected. This is why enterprises and cloud providers alike need to embrace a cloud data governance function and map policies, processes and technology controls accordingly. In her session at 15th Cloud Expo, Evelyn de Souza, Data Privacy and Compliance...
VictorOps is making on-call suck less with the only collaborative alert management platform on the market. With easy on-call scheduling management, a real-time incident timeline that gives you contextual relevance around your alerts and powerful reporting features that make post-mortems more effective, VictorOps helps your IT/DevOps team solve problems faster.
Containers and microservices have become topics of intense interest throughout the cloud developer and enterprise IT communities. Accordingly, attendees at the upcoming 16th Cloud Expo at the Javits Center in New York June 9-11 will find fresh new content in a new track called PaaS | Containers & Microservices Containers are not being considered for the first time by the cloud community, but a current era of re-consideration has pushed them to the top of the cloud agenda. With the launch ...
Skeuomorphism usually means retaining existing design cues in something new that doesn’t actually need them. However, the concept of skeuomorphism can be thought of as relating more broadly to applying existing patterns to new technologies that, in fact, cry out for new approaches. In his session at DevOps Summit, Gordon Haff, Senior Cloud Strategy Marketing and Evangelism Manager at Red Hat, will discuss why containers should be paired with new architectural practices such as microservices ra...
Roberto Medrano, Executive Vice President at SOA Software, had reached 30,000 page views on his home page - http://RobertoMedrano.SYS-CON.com/ - on the SYS-CON family of online magazines, which includes Cloud Computing Journal, Internet of Things Journal, Big Data Journal, and SOA World Magazine. He is a recognized executive in the information technology fields of SOA, internet security, governance, and compliance. He has extensive experience with both start-ups and large companies, having been ...
HP and Aruba Networks on Monday announced a definitive agreement for HP to acquire Aruba, a provider of next-generation network access solutions for the mobile enterprise, for $24.67 per share in cash. The equity value of the transaction is approximately $3.0 billion, and net of cash and debt approximately $2.7 billion. Both companies' boards of directors have approved the deal. "Enterprises are facing a mobile-first world and are looking for solutions that help them transition legacy investme...
The industrial software market has treated data with the mentality of “collect everything now, worry about how to use it later.” We now find ourselves buried in data, with the pervasive connectivity of the (Industrial) Internet of Things only piling on more numbers. There’s too much data and not enough information. In his session at @ThingsExpo, Bob Gates, Global Marketing Director, GE’s Intelligent Platforms business, to discuss how realizing the power of IoT, software developers are now focu...
Operational Hadoop and the Lambda Architecture for Streaming Data Apache Hadoop is emerging as a distributed platform for handling large and fast incoming streams of data. Predictive maintenance, supply chain optimization, and Internet-of-Things analysis are examples where Hadoop provides the scalable storage, processing, and analytics platform to gain meaningful insights from granular data that is typically only valuable from a large-scale, aggregate view. One architecture useful for capturing...
SYS-CON Events announced today that Vitria Technology, Inc. will exhibit at SYS-CON’s @ThingsExpo, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. Vitria will showcase the company’s new IoT Analytics Platform through live demonstrations at booth #330. Vitria’s IoT Analytics Platform, fully integrated and powered by an operational intelligence engine, enables customers to rapidly build and operationalize advanced analytics to deliver timely business outcomes ...
DevOps is about increasing efficiency, but nothing is more inefficient than building the same application twice. However, this is a routine occurrence with enterprise applications that need both a rich desktop web interface and strong mobile support. With recent technological advances from Isomorphic Software and others, it is now feasible to create a rich desktop and tuned mobile experience with a single codebase, without compromising performance or usability.
SYS-CON Events announced today Arista Networks will exhibit at SYS-CON's DevOps Summit 2015 New York, which will take place June 9-11, 2015, at the Javits Center in New York City, NY. Arista Networks was founded to deliver software-driven cloud networking solutions for large data center and computing environments. Arista’s award-winning 10/40/100GbE switches redefine scalability, robustness, and price-performance, with over 3,000 customers and more than three million cloud networking ports depl...
The speed of software changes in growing and large scale rapid-paced DevOps environments presents a challenge for continuous testing. Many organizations struggle to get this right. Practices that work for small scale continuous testing may not be sufficient as the requirements grow. In his session at DevOps Summit, Marc Hornbeek, Sr. Solutions Architect of DevOps continuous test solutions at Spirent Communications, will explain the best practices of continuous testing at high scale, which is r...
SYS-CON Events announced today that Open Data Centers (ODC), a carrier-neutral colocation provider, will exhibit at SYS-CON's 16th International Cloud Expo®, which will take place June 9-11, 2015, at the Javits Center in New York City, NY. Open Data Centers is a carrier-neutral data center operator in New Jersey and New York City offering alternative connectivity options for carriers, service providers and enterprise customers.
Thanks to Docker, it becomes very easy to leverage containers to build, ship, and run any Linux application on any kind of infrastructure. Docker is particularly helpful for microservice architectures because their successful implementation relies on a fast, efficient deployment mechanism – which is precisely one of the features of Docker. Microservice architectures are therefore becoming more popular, and are increasingly seen as an interesting option even for smaller projects, instead of bein...
The explosion of connected devices / sensors is creating an ever-expanding set of new and valuable data. In parallel the emerging capability of Big Data technologies to store, access, analyze, and react to this data is producing changes in business models under the umbrella of the Internet of Things (IoT). In particular within the Insurance industry, IoT appears positioned to enable deep changes by altering relationships between insurers, distributors, and the insured. In his session at @Things...
Security can create serious friction for DevOps processes. We've come up with an approach to alleviate the friction and provide security value to DevOps teams. In her session at DevOps Summit, Shannon Lietz, Senior Manager of DevSecOps at Intuit, will discuss how DevSecOps got started and how it has evolved. Shannon Lietz has over two decades of experience pursuing next generation security solutions. She is currently the DevSecOps Leader for Intuit where she is responsible for setting and driv...
Even as cloud and managed services grow increasingly central to business strategy and performance, challenges remain. The biggest sticking point for companies seeking to capitalize on the cloud is data security. Keeping data safe is an issue in any computing environment, and it has been a focus since the earliest days of the cloud revolution. Understandably so: a lot can go wrong when you allow valuable information to live outside the firewall. Recent revelations about government snooping, along...
In his session at DevOps Summit, Tapabrata Pal, Director of Enterprise Architecture at Capital One, will tell a story about how Capital One has embraced Agile and DevOps Security practices across the Enterprise – driven by Enterprise Architecture; bringing in Development, Operations and Information Security organizations together. Capital Ones DevOpsSec practice is based upon three "pillars" – Shift-Left, Automate Everything, Dashboard Everything. Within about three years, from 100% waterfall, C...