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All for the Want of a Global Load Balancer
Thoughts on the AWS / Netflix Christmas Eve Elastic Load Balancer Event

Christmas Eve and the AWS/Netflix outage to me aren't so much about whether or not the Cloud is viable or scary or dangerous. Rather, the event resonated with users across the United States because the Cloud delivers so much utility to each of us. And regardless of who was at fault -- Netflix or Amazon Web Services, the event made it clear that there's no going back and that the Cloud has quickly become a part of our culture and our everyday lives. This is significant because while the Internet itself is a technology consumers have grown to love, Cloud is a way of delivering service that makes a service like Netflix streaming possible, and at a measly $8 bucks a month. The Netflix business model of delivering outsize utility for a low price point makes the business of streaming video all the more difficult. HBO, Cinemax, and the networks for me are unusable. I sense something beyond just making money remains in play at Netflix. Somewhere in that organization seems to beat a heart that quickens for humanity.


While much is made of the sparsity of the Netflix streaming catalog, keep in mind that streaming is the disruptor's second act. The Wicked Witch, aka Blockbuster is dead, I think in part because each of us desired a little bit of payback for all the times we returned videos late and were charged outrageous fees. Rather than punish Netflix Streaming for innovating, and for challenging the iron grip of the legacy media houses, I praise Netflix and personally admire the generous open source contributions Netflix has made to the Cloud Community.

I once tweeted that the value of the code and tools Netflix has shared on GitHub may well be larger than the value of the streaming business as a whole. That may be true for about five minutes. We're at a tipping point in streaming video media similar to that of the music business just before the iPod. Yet each evolution carries forward a little bit of spin from the last disruption. In this iteration all the players know the iPod playbook and so they are trying very very hard to fight the gravity of disruption. Having lost Blockbuster and effective control over the distribution of their content, the old guard hold onto to their catalog stubbornly hoping Netflix will disappear. But we all know how this movie ends. I see a much larger Netflix catalog of content on the horizon and substantial value for consumers. Once the old guard have been disintermediated and a more open, consumer friendly market for content prevails every Christmas will be a little brighter (that's kind of a stretch?). In my opinion what's in play today with respect to old media firms is not so different from the agency model that kept eBook prices artificially high for many consumers.

So what about the Global Load Balancer Already?
Most Cloud Architect and Solution Architects of high availability systems are familiar with Load Balancers. AWS designed a mostly well-intended and useful service around this technology and it's often referred to as the (infamous) ELB (Elastic Load Balancer). Functionally a "classic" load balancer distributes service requests across hosts grouped into a pool of largely identical servers. Spreading requests across multiple servers is a key capability required for the horizontal scale-out favored by Cloud and to a lesser degree Enterprise Architecture.

A Global Load Balancer operates one or more levels above the Local Load Balancer. Similar to a classic DNS server, the Global Load Balancer returns an ip address. Often the IP address is the address of a Local Load Balancer but could be configured to return a public or private ip address. The IP address or VIP returned is determined by the specific solution requirements. Because Global Load Balancer technology stands on the shoulders of a fundamental and ubiquitous technology like DNS, the service can be very resilient if configured that way. If LLB (Local Load Balancer) high-availability solution is designed correctly the Load Balancer monitors the health and responsiveness of a pool of servers and directs requests to nodes of an application. A Global Load Balancer performs a similar function, except at a data center level. A Global Load Balancer can detect when a Local Load Balancer is no longer available, and when this happens can return the ip address of a load balancer or endpoint in another data center anywhere in the world. As it is based on DNS technology the Global Load Balancer is not coupled to a specific network. Moreover, the top-level domain is likely not hosted in any Cloud, and so provides a degree of separation. Further, Global Load Balancers can determine the nearest endpoint for a specific user request, and can return an endpoint closest to a user. Global Load Balancers can be configured to monitor the latency of response times across a pool of endpoints. In times of network failure, the endpoint that is normally "closest" or "lowest latency" frequently becomes a very high latency endpoint. So the ability to monitor latency and to adapt how it responds to requests based on latency, enables a very fine grained capability to direct users around system and network anomalies such as those that continue to plague US-EAST-1.

My observation is simply this: why don't Cloud or Web firms take a lesson from classic availability architecture and use a load balancer to enable endpoints to fail across data centers. For enterprise, why make Cloud an either/or question. And why gamble with the availability of important systems when it's not so difficult (especially if you've figured out the persistence layer) to balance systems across multiple Clouds. Using such an architecture to enable rapid switching of endpoints to other data centers could enable an enterprise to run an application both in the Cloud and in the data center and to balance traffic across them not in the sense of the much hyped "Cloud Bursting" which seems to focus mostly on "bursty capacity" but rather as a strategy for mitigating risk and reducing the correlated risk of running Load Balancers and applications within a single specific Cloud, even in multiple availability zones (as in the case of AWS). Hurricane Sandy in New York City would have been far more disruptive if not for systems built using Global Load Balancers for high availability. While there's no comparison to the complexity of failing over critical, albeit smaller-scale platforms to Netflix, several non-web facing internal applications for which I designed the architecture in 2011-2012 failed over to alternate data centers simply by  changing the endpoint returned by the Global Load Balancer.  In the case of Netflix, the option to migrate all the data was not an option, yet the instances remained healthy while those impacted by the ELB failure received no requests. An alternate strategy for directing traffic, in hindsight, could have made a difference.  It puzzles me to no end why given the extensive focus on Cloud failure modes, the AWS ELB remains a single point of failure for Netflix and many other applications running in AWS whether at modest or extreme scale.

I wonder if Netflix will select an additional Cloud in 2013 and in doing so create some real competition in the Cloud Service Provider space. After such a high profile failure (Christmas Eve, for Christ's Sake), I feel certain the decision has already been made. The impact of such a move would legitimize another Cloud. People who know these things tell me that 80% of Amazon Web Services capacity is in US-EAST-1. To me this suggest Amazon Web Services has fallen victim to it's own success. The nature of Clouds is such that as they grow bigger the network effect driven by the efficiency of locating data and compute capacity as close together as possible becomes overwhelming and the penalty for locating in another region, such as the West Coast, or another Cloud in another data center, becomes higher. While recently AWS has announced some capabilities to make it easier to migrate to the US-WEST-2 (Oregon region, which is priced about the same as US-EAST-1) such capabilities don't really seem to matter.

I spend a great deal of my time learning from web scale best practices such as those co-developed by firms like Netflix, Heroku, Pinterest, Google and redefine what people think they know about distributed computing..  Yet based on the theme of AWS re:invent, and my personal experience in Fortune 500 Cloud, 2012 may not only "not be the end of time and ancient calendars," but 2012 may mark the year when this thinking makes the leap and infects the DNA of Fortune 500 technology. The itchy little problem of Cloud as ready for big business remains the persistent failures, yet the risk of failures in hindsight can be minimized--and using technology commonly used by Enterprise that unlike Oracle RAC clusters and other High Availability technology works just fine in both Cloud and traditional data centers.

Listen closely to what Cloud and web scale practitioners have to teach. Architecture of Cloud applications deviates in ways that will make your database and application engineers pull-out their hair, scream, and storm out meetings (based on what I've seen, except for the hair pulling). For example the application server architecture and scale-out strategy for scaling applications in the Cloud is very different from how most of Fortune 500s do Enterprise Application Server clusters today. And after you fail in the Cloud trying to kick it old school, the enlightenment comes quickly. Yet at the same time, don't get too caught up in the hype and forget everything. The Global Load Balancer commonly used in large enterprise, when deployed effectively, could very well help you build applications which balance the new with the familiar.

Further Reading / Cultural Reception of Cloud

Summary of the December 24, 2012 Amazon ELB Service Event in the US-East Region

Some of the media reception of the events. I find the coverage to be grossly inaccurate, yet it's part of the cultural reception of the Cloud, so I've included some links:

‘The Cloud’ Challenges Amazon http://nyti.ms/ZBXT86

Read the original blog entry...

About Brian McCallion
Brian McCallion, founder of New York City-based consultancy Bronze Drum focuses on the unique challenges of Public Cloud adoption in the Fortune 500. Forged along the fault line of Corporate IT and line of business meet, Brian successfully delivers successful enterprise public cloud solutions that matter to the business. In 2011, while the Cloud was just a gleam in the eye of most Fortune 500 firms Brian designed and proved the often referenced hybrid cloud architecture that enabled McGraw-Hill Education to scale the web and application layer of its $160M revenue, 2M user higher education platform in Amazon Web Services. Brian recently designed and delivered the JD Power and Associates strategic customer facing Next Generation Content Platform, an Alfresco Content Management solution supported by a substantial data warehouse and data mart running in AWS and a batch job that processes over 500M records daily in RDS Oracle.”

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Cloud Expo - Cloud Looms Large on SYS-CON.TV


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Lastest Blog Posts
A key development for the Internet of Things will be the evolution and emergence of the ‘Cloud Name System’, a directory system for Cloud applications in the same way DNS (Domain Name System) works for the web and email. Lori MacVittie wrote a while back about the need for an ‘SNS’ – a Service Name System, a DNS type directory approach but for Cloud Services so that they can be entirely loosely coupled from their IT infrastructure. Tim Berners-Lee, the inventor of the web, himself described a scenario of ‘Socially Aware Cloud Storage‘ that applies this same ideal of abstraction to our personal data across all the social networks we use. This refers to a distributed (Cloud) storage service that is used to store personal user data for social networks, rather than the social sites holding it themselves.
I like this word re-imagination from Mary Meeker’s Internet Trends presentation. We are seeing so many aspects of our life being transformed by the internet. Take for example, ordering a cab to go somewhere. Either we phone for a yellow cab here in California or if you are in New York city, then you stand and wave for an incoming yellow cab to stop. The new game-changer is Uber. All you do is touch your smartphone screen for UberX or Black car and you get an instant message about the car coming in less than 5 minutes time with the driver and car info. It is cheaper and you pay by card (pre-registered in your Uber account). This is re-imagining the transport sector. Uber, a San Francisco company is worth about $17B and is operating in 70 cities around the world. Quite a disruptive force!
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.
I love receiving gifts in the form of new insights! It doesn't matter if others received the same gift years ago and I am just getting it now. If it is new to me, I get excited. It is like waking up in the morning and discovering a new room in your house. I read an article by Thomas Friedman in the New York Times this weekend titled, "And Now for a Bit of Good News." The subject of the article was the new "sharing economy," think Uber, Lyft, Airbnb, etc. In the article, Friedman calls Airbnb a "Trust Platform." To me, this weekend, this term was a gift. He is so right. I have used Airbnb many times when traveling with my family, and to date have been very pleased with our experiences. Often the transactions are sizeable as I am reserving a home in a desirable location for a week. I am engaging in a transaction of some size with a person I don't know, in a home I have never visited, most often in a foreign country using different currency, involving different laws and customs. Why did I risk it? I trusted the platform.
Do you avoid stores that have had a credit card breach? You are not alone. About 52% of people avoid merchants who have had a data breach according to a recent Lowcards survey. They surveyed over 400 random consumers to better understand the impact of identity theft on consumer behavior. 17% said they or a family member was a victim of identity theft over the last year with half the cases being credit card theft. 94% said they are more concerned or equally concerned about ID theft. They estimate that there were 13.5 million cases of credit card identity theft in the United States over the last 12 months.
If you've had to test one of today's composite applications, you know that "access" has become one of the most daunting barriers to SDLC acceleration. Whether we're talking about access to dev/test environments or access to dependent applications, the ability to pull all the required pieces together in order to test thoroughly is equivalent to herding feral cats. If you haven't experienced this fun firsthand, consider this: our recent research revealed that systems under test have an average of 30 dependencies, but team members have consistent access to only 6. The time available to access test environments is extremely limited (4 hour slots) and 30% of that limited time was consumed by configuration/setup tasks. Ultimately, testers had time to execute only 50% of the available test plan. Service virtualization is a revolutionary new technology that helps you break through these constraints by providing ubiquitous, global access to complete dev/test environments. Organizations leveraging service virtualization are able to conduct testing earlier, faster, more thoroughly, and more accurately—significantly reducing the risk of application failure. In case you're just starti...
Much has been published about the Open Compute Project. Initiated by Facebook, it has become an industry effort focused on standardization of many parts and components in the datacenter. Initially focused on racks, power and server design, it has also added storage and now networking to its fold. Its goal is fairly straightforward: “how can we design the most efficient compute infrastructure possible”, a direct quote from its web site. The focus of OCP has been mostly around hardware designs and specifications. If you look at the networking arm of OCP, you find several Top of Rack (ToR) ethernet switch hardware designs donated by the likes of Broadcom, Mellanox and Intel. By creating open specifications of hardware designs for fairly standard ethernet switches, the industry can standardize on these designs and economics of scale would drive down the cost to create and maintain this hardware. A noble goal and there are many opinions on both sides of this effort. Mostly referred to as “bare metal” and “commodity”, you can easily spend days reading up on many opinions. Mike Bushong yesterday discussed pricing implications for resellers in this blog post.
In a post Snowden world it is clear that for cloud data security, we need strong encryption. When properly implemented, encryption in the cloud reduces risk to levels acceptable for sensitive data. There is no doubt data protection in the cloud computing era is never going to be a ‘one size fits all’ kind of a solution. It requires a 360-degree view of the company with 365-days a year dedication. The best place to start is with a risk analysis so you know what kind of data you have, its levels of sensitivity, who’s using it, where it’s used and stored, and how and where and over what technologies it’s going to ‘commute’. You need to understand your company’s data – in terms of technology and human weaknesses. Data should be unreadable to an attacker. It must be incoherent at all times to anyone other than you and your trusted personnel: while it’s travelling – or you are; whether it’s in transit, storage, stopping, or resting, data is safest in encrypted form.
Some people are never satisfied. These fearless agents of change are everywhere. They're informed, confident and willing to experiment. They seek out the best business technology solution for the job at hand. They act on instinct. Yes, you could say that they're driven. However, they're also at risk of being labeled as "rogue employees" because they ordered a software-as-a-service (SaaS) offering and perhaps expensed it without prior approval. Sometimes they're the champion of progressive projects that are referred to as Shadow IT -- intentionally bypassing their company's formal evaluation and procurement process. How can this happen? Is it just because their activities are tolerated, or are they being encouraged? If so, by whom? Why would any business leader applaud a team member that breaks the rules? Maybe, the simple answer is that staying within the confines of the status-quo won't enable a top-performer to fully apply their talent, achieving their absolute best.
The GovCloud Media Network features agency specific video playlist for registered members. Please enjoy this feature on the Army IT. Please visit the new GovCloud Network Media Library for more video content. For membership information please send request to info@govcloudnetwork.com.
One of the primary principles of object-oriented programming (OOP) is encapsulation. Encapsulation is the way in which the state of an object is protected from manipulation in a way that is not consistent with the way the variable is intended to be manipulated. The variable (state) is made private, that is to say only the object itself can change it directly. Think of it as the difference between an automatic transmission and a standard (stick). With the latter, I can change gears whenever I see fit. The problem is that when I see fit may not be appropriate to the way in which the gears should be shifted. Which is how engines end up being redlined.
Cloud computing has finally come into its own. While we’ve been hearing for 8 years or more that cloud computing would one day take over the enterprise, the fact of the matter is that it’s been slow going. While the spread of cloud computing solutions hasn’t been as rapid as many early proponents predicted it would be, we are now to a place where cloud solutions are seen as viable for most organizations, and are being utilized regularly.
It's an application world; a world that is rapidly expanding. With new opportunities and markets arising driven by mobility and the Internet of Things, it is only going to keep expanding as applications are deployed to provision, license, and manage the growing sensors and devices in the hands of consumers. Applications are not isolated containers of functionality. No application winds up in production without a robust stack of resources and services to support it. Storage and compute, of course, are required, but so are the networking - both stateless and stateful - services that provide for scale, security and performance.
We're launching the "Tap In Open Forum": a new series of blog posts where we detail a current topic being discussed in the software development and testing community and invite you to participate in an open discussion with our best and brightest here at Skytap. Feel free to share your thoughts and we'll do the same! InformationWeek and IBM Mobile Technical Sales Leader Dustin Amrhein presented a webinar last week as part of their “DevOps Rado” series. The Frictionless Enterprise: Built for Business, looked at DevOps as a viable solution for removing the friction that prevents enterprises from innovating at not just the speed they would like, but at the speed absolutely required to stay relevant, and hopefully ahead of their competition.
Since the birth of Hadoop in 2005-06, the way we think about storing and processing information has evolved considerably. The term “Big Data” has become synonymous with this evolution. But still, many of our customers continue to ask, “What is Big Data?”, “What are its use cases?”, and “What is its business value?”. The Internet is overloaded with definitions, characteristics, and benefits; however, few discussions synthesize all three of these topics in one place. This paper answers these questions, and proposes a total cost calculation framework for CTOs and CIOs that are evaluating solutions for their organization’s use case(s). In the text below, I examine an on-premise Hadoop ecosystem as a general purpose Big Data solution in relation to alternative commercial purpose-built storage technologies (-e.g. Oracle, Teradata, IBM, SAP, Microsoft, EMC, etc). It may be difficult to determine the exact point at which you should leverage one over the other. It is my contention that when the total cost of using all your data exceeds what you are able to spend using purpose-built technologies, it is time to consider using a general purpose solution like Hadoop for process offloading....
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