There is a lot of great cloud information in here that I don’t get a chance to talk about in venues where time is short like panels or blog entries.  Definitely recommended listening, but it’s a long interview so it might be easier to consume in small chunks.  To make this a bit easier for you, I’ve chopped it into five smaller and more consumable MP3s (below) OR go directly to the Intellum page to listen.

• Part 1. Introduction (6:35)
• Part 2. Cloud Computing Defined (13:11)
• Part 3. Leveraging the Cloud for Startups, SMBs, and Enterprise (14:54)
• Part 4. Fears and Concerns (13:09)
• Part 5. Future of Cloud in 2010 and Beyond (7:13)

During this interview series I also refer to four layers in cloud.  Most folks like to talk about infrastructure (Infrastructure-as-a-Service), platforms (Platform-as-a-Service), and applications (Software-as-a-Service).  There is a fourth layer that rides on top that I haven’t had a chance to blog on yet, but Part 2 goes into some detail.  To make it a little more clear what I mean, see the diagram below.

• How to adopt cloud now
• Choosing between clouds: internal, external, or both?
• Real world example use cases
• Understanding how clouds are built when creating a strategy

There are some great panelists who are attending and I thought I would run through them here to give you a flavor of for our track.

Folks Who Really Did It
All of the folks on our first panel, “Moving to clouds: it’s not all or nothing”, have experience with migrating to clouds, but two of them, Victoria Livschitz and Tom Gregory have some really interesting experiences.  Victoria’s company, GridDynamics, was responsible for the famous Macys.com use case highlighted on GoGrid’s website.  Tom Gregory, CTO of PresidioHealth has some great insights to share with his recent migration from his own co-location space to a cloud computing provider.

Also on our first panel is the illustrious Geva Perry, author of Thinking Out Cloud, one of the earliest and more insightful cloud blogs.  Geva was also previously CMO at Gigaspaces and GM for their cloud computing product.  Gigaspaces was one of the first application frameworks to provide a scalable platform that abstracts infrastructure clouds.  Now we advises with a number of startups and enterprises in various stages of migrating to clouds including Heroku, Twilio, ScaleDB, Sauce Labs, and NEC.

Last, but not least on our first panel, and bridging nicely to the following section, is Ellen Rubin, who’s company, CloudSwitch, provides a novel approach to migrating apps to the cloud.  Their technology is unique in that it picks up a currently deployed application, moves it to Amazon’s EC2 in a secure fashion, and then makes it appear that the application is still deployed in your datacenter.

Vendors Who Enable It
Who better than RightScale’s CEO Michael Crandell to talk about enterprise businesses who migrated their web applications to the cloud?  Complementing Michael is George Reese of enStratus.  George wrote the book on Cloud Application Architectures and enStratus competes with RightScale, but has a particular focus on enterprise businesses.  He’s got a great use case he’s planning on sharing that I think will highlight the value of cloud for big businesses.

Hearing from these two cloud enablement businesses, one an ‘old’ stalwart with deep experience like RightScale and another an up and comer like enStratus will help us see a broader spectrum of success in cloud adoption.

People Who Built It
How can you pick to embrace external clouds, build an internal cloud, or mix the models if you don’t know what it’s all about?  We’ve got a tremendous lineup of folks who have actually built external/internal, private/public clouds, or the tools for them.

Ken Owens of Savvis was key to architecting their Spirit offering.  I’ve spent time with Ken before and he’s the real deal.

Philip Morris, the CTO of HPC for Platform Computing is another long time builder of large scale infrastructure and an expert, in particular, on HPC and grid computing.

Martin Casado, CTO of Nicira was one of the authors of the OpenFlow protocol.  He and Nicira are set to revolutionize the world of networking with true network virtualization.  Martin is a dynamic individual with deep insights on how the network is going to change in cloud computing environments of the future.

Cloud Migrations
Build vs. buy?  Embrace and extend?  Get real value today?  We’re going to answer all of these questions during the Cloud Migrations track.  I hope to see you there!

–Randy Bias

UPDATE: Added information on all of the track panelists.

Hope you can join us.  You can use the code “CNJRCC06″ to get a free expo pass or 40% off the entire event.  You can register here.  We look forward to seeing you there.

Here’s the Wikipedia page on hybrid. As used in almost every case the result is that you have a kind of equation:

A + B = C

As used today in cloud computing, hybrid is abused to mean CONNECTING, not COMBINING two kinds of clouds:

• Private + public clouds
• Internal + external clouds
• Physical servers + virtual servers

The fundamental issue with all of these (except arguably the third, but I’ll cover that shortly) is that the end result is not A + B = C, but rather:

A + B = A + B

As long as the industry misuses (some might even say ‘abuses’) the term hybrid by using it any time they connect two clouds, more confusion is added to what is already a difficult conversation:

Joe:  "Our new hybrid cloud is up and running!"

Bob:  "Which kind of hybrid is that?  Public and private?  Private and

private?  Internal and external? ..."

The most accurate use of the term I’ve seen to date is GoGrid’s use for their combination of physical and virtual servers. However, the assumption is that cloud computing is about virtualized servers, which it’s clearly not. Virtualization is a multi-tenancy strategy. It allows you to chop up a physical server into smaller bite-sized chunks.

Cloud computing is about on-demand self-service IT resources, whether it’s servers (physical or virtual), storage, or network. There is no need to make up a new marketing name for ‘physical & virtual’. Just say: “Our cloud now provides physical servers on-demand for high performance workloads!” Everyone gets that.

Precise language, especially when discussing the confusing bleeding edge, is critical. Fuzzy terms, which can be perceived as marketing fluff, are best left at the door. We (those of us in the cloud industry) do ourselves and our customers a disservice by misuse of the term ‘hybrid’ unless we truly have figured out how to do the equation of A + B = C and C is something brand new. I challenge all thought leaders (myself included) to figure something else out or reuse one of the above terms.

An aside: a ‘model’ is a way of doing things.  Technology models are ways of putting technology together.  Financial models are ways to arrange finances.  Service models are ways of providing a service that is consumed by someone else.

There are two primary ways you can use cloud computing[1]:

1. Outsourced to an external public utility that uses economies of scale to service many customers
2. Maintained in-house as an internal shared infrastructure (aka ‘private’ or more properly ‘internal’ cloud)[2]

The myth about private clouds above conflates 3 ideas worth digging into:

1. The cloud diagram was used only to represent the Internet by network engineers and means ‘outsourcing’
2. Cloud is a business model and must be delivered as a public utility
3. Implied: clouds cannot be ‘private’ and owned by a single entity

Understanding the importance of private clouds is important, because the cloud computing model (like the client/server computing model before it) is about how IT works, not where it works.

Let’s address each part of the “no such thing as an (internal) private cloud” myth.

The Cloud Picture
I can say with 100% certainty that cloud pictures were used for much more than the Internet in the early 90s when the commercial Internet was forming. I know this because I was a network engineer.  My peers and I used clouds to represent any ‘autonomous system’ or group of such in a routing architecture.  It was a convenience mechanism to simplify network diagrams.

One example was using it to represent a large private wide area network (WAN), consisting of Frame Relay circuits or T-1s.  A cloud was also frequently used to represent the entire public switched telephone network (PSTN) or even, at times, entire groups of internal enterprise datacenters & networks.

One of my colleagues at Cloudscaling who is also a network engineering expert says:

Want more?  Here are three of the first page of network diagrams that came up on a Google image search for ‘network diagram’: 1, 2, 3.  As you will see there is liberal usage of the cloud picture for purposes other than representing the Internet.  Many of these clouds also represent ‘private’ areas of the network.

Without the historical context, it is understandable how one could conclude that the term “the cloud” was used as another term for “The Internet”.

Clouds Are Shared Infrastructure, not Utilities
Let’s explore the “utility” concept outside the context of the IT function[3]. A common definition of a ‘utility’ amongst cloud pundits today is: a shared infrastructure with metered usage, which has a pay-as-you-go model. An example of a non-IT utility is power companies like Pacific Gas & Electric (PG&E) which are energy utilities.  Nick Carr’s famous books, Does IT Matter? and The Big Switch extensively examine the concept of shared infrastructures leading to the rise of utility computing.

Nick posits that all shared infrastructures, including roads, telegraph, the national air system, railroad system, electrical system, and gas system, are utilities.  Do you think of a road as a utility?  What about the air traffic control system?  I don’t and neither does Wikipedia nor is that term used commonly.  A public utility is “a company that performs a public service; subject to government regulation” according to WordNet.  In other words, a utility is a for-profit entity entrusted to perform an important public function and is commonly regulated.

There is a common notion in the discussion of cloud today, which is that “utility” or “utility billing” is a financial arrangement where usage is “metered” and you “pay-as-you-go”, paying only for actual consumption.  This idea comes directly from the way true public utilities such as water, gas, electricity, and telecommunications operate.  These are all systems we commonly consider to be utilities.

But other shared infrastructures do not use the utility billing model.  Certainly, some roads have tolls, but the bulk of roadways are paid for with public money and are unmetered.  The railroad system is not metered.  Neither is air travel.  You do not ‘pay-as-you-go.’  While these systems aren’t labeled as ‘utilities’, Nick Carr lumps them into the same bucket.

It might be heresy, but I think there are essentially two big buckets: shared infrastructure and utilities.  Public utilities are a subset of shared infrastructure as is illustrated in the Venn diagram below.

Infrastructure Can Be a Public Utility OR a Private Shared Infrastructure
Infrastructure is frequently deployed by private individuals or entities for the purpose of sharing with others. Private road and highways are commonly shared.  No, I’m not referring to a simple driveway; I’m talking about large-scale construction efforts in which on-campus roads are built on university campuses, enterprise businesses, military bases, etc.  People fly private planes all the time, yet they share the national air infrastructure in terms of air controllers and air space, but not the planes themselves.  The military or large federated organizations also have large-scale shared infrastructure that is not a ‘public’ service.  There are many more examples and it is clear that not all shared infrastructure is a public utility.

We now have a conundrum.  The  ‘utility’ concept isn’t as clear-cut as being simply a shared infrastructure.  It clearly implies a financial arrangement.  What do we do?

For me it’s clear:  There is ’shared infrastructure’ and there are ‘utilities’.  Utilities are usually shared infrastructure, but not all shared infrastructure is a utility.  Utilitization is the act of taking a shared infrastructure and applying a financial model to it that charges for metered usage.  That means that utilitization is a business model that can be layered on top of a shared infrastructure (aka ‘public cloud’).

“Cloud” or “cloud computing” are limited terms. Nick Carr predicted the rise of utility computing.  He did not call it ‘cloud’ or ‘cloud computing’, nor did he coin those terms.  Nick correctly predicted the advent of a cost/economics model that inevitably moves large amounts of computing infrastructure to specialized providers who operate as public utilities and can use their scale to cost effectively deliver this service.  That’s the utility model and there is absolutely no doubt that it exists, is real, and will eventually apply to every shared infrastructure that human beings will create now and in the future.

So What’s a Private Cloud?
To better understand the concept of a ‘private’ cloud, we need to explore the concept of cloud computing itself.

Cloud computing can be seen not as a utility business model, but as a technology infrastructure model. The infrastructure in play is ‘data infrastructure’, not electrical infrastructure, people moving infrastructure, or others.  This new model determines how data infrastructure will be delivered and was pioneered by Google and Amazon among others.  Amazon used their data infrastructure to drive new revenue (AWS), and Google later introduced its Google App Engine (GAE) to do the same.

Were Amazon and Google clouds before they added revenue generation models?  I, and many others, would say “yes”.  The utility financial model for revenue generation is being applied to their clouds, but it does not, and never has, defined their clouds.

What defines their clouds is the method by which they built the actual IT infrastructure.  It was designed to be completely self-service, has no major single points of failure, and relies on commodity software and hardware.

That’s cloud computing.  Cloud computing is a methodology for delivering IT that changes everything. This is similar to how client/server computing disrupted mainframe computing changing IT in the process. The diagram below clearly illustrates my point.

This diagram shows the evolution to client-server from mainframe computing. Cloud computing is the next progression in the evolution of IT. Public cloud proponents want us to believe that everything in that third column is subsumed by the financial & business model, which is not true.  If you extract cloud computing from the public utility business model, there are significant and important advantages to moving away from the client-server model.  These advantages will be embraced by larger businesses that cannot easily progress to the public cloud model. In fact, the private cloud model is a critical transitional step. It is an essential component to help larger organizations move their compute capacity to the public cloud.[4]

Just what is a private cloud?  Private clouds are the cloud computing methodologies that Amazon and Google pioneered but applied in such a fashion that only a single tenant uses them.  They are owned by a single entity and optionally shared.  If Amazon deploys a copy of their Elastic Compute Cloud (EC2) for a customer, that copy of EC2 is a little private cloud used only by that customer.  It’s the same technology and methodology wrapped up in one little neat ‘cloud’ ball for the client.  It’s private, it’s a cloud, and the financial model it uses is not the utility billing model.

Summary
Will cloud be delivered as a utility?  Absolutely.  It is today.  In fact, the public utility model will be the dominant financial paradigm for cloud computing within the next two decades.  Most people will consume cloud computing built and delivered by others.  The cost economics are too compelling.

However, there will always be a demand for a private, unshared, cloud option.   This option could be outsourced or not, but it is ‘private’ because organizations will have some kind of requirement that disallows public cloud usage.  It could be security, regulatory, performance, or just plain old paranoia driving these requirements that prevent the ‘public cloud option’.

The old client/server computing paradigm is no longer good enough, just as the mainframe computing model before it wasn’t good enough.  The cloud computing model is displacing both client/server computing as the de facto way to deliver IT services.  At the same time, cloud computing pioneers (i.e.Amazon and Google) are finding that by utilitizing their cloud services, they can leverage their leadership while offering unprecedented value. Large enterprises will eventually move much of IT outside their walls. However, there will be areas which cannot be moved. That which remains inside their walls will be delivered using internal private cloud technologies.

I predict that 2010 will be the year of the private cloud.  We are at the beginning of a huge growth curve and this is the year it will start to see significant traction.

    Xen Cloud Platform offers ISVs and service providers a complete cloud
    infrastructure platform with a powerful management stack based on
    open, standards-based APIs, support for mutli-tenancy, SLA guarantees
    and deteailed metrics for consumption based charging.

From the website:

    In a classical router or switch, the fast packet forwarding (data path)
    and the high level routing decisions (control path) occur on the same
    device. An OpenFlow Switch separates these two functions. The data
    path portion still resides on the switch, while high-level routing decisions
    are moved to a separate controller, typically a standard server. The
    OpenFlow Switch and Controller communicate via the OpenFlow protocol,
    which defines messages, such as packet-received, send-packet-out,
    modify-forwarding-table, and get-stats.

This means you can create a fully multi-tenant, highly secure, extremely flexible, cloud network topology that maps exactly to your requirements.  This contrasts starkly to the current cloud networking today, which is either extremely restrictive (Amazon’s EC2), has scaling problems (e.g. 802.1q VLAN tagging), or doesn’t give you complete control (Rackspace Cloud, et al).

Let me clarify what I mean by complete control before anyone is offended. Rackspace Cloud does provide more control than EC2, but it doesn’t put you in the driver’s seat.  Imagine that instead of having a fixed network architecture like, every customer has a ‘frontend public network’ and a ‘backend private network’, you have something that allows arbitrary network configurations?  Customers get a ‘private’ network by default and buy networks as their applications need them.  Now having a separate network for database servers per PCI compliance (or other) rules is trivial.

Many other things are possible if you move towards an OpenFlow-based network architecture with a centralized control system, including:

• Distributed firewall just like Amazon EC2’s distributed firewall
• On-demand network introspection / tapping
• On-demand in-line firewall / IPS
• N-tier network topologies
• Distributed Virtual Switch (a la Cisco Nexus 1000V)

There are many other possibilities.  The eventual promise here is network virtualization as good as storage or computing virtualization is today.

Way to go Nicira and Citrix!

In particular, a number of articles posted here last year were extremely widely read.  In fact, the #1 article had well over 10,000 pageviews and almost 9,000 unique visitors.  3,500 pageviews came in that first week of posting 09/27/09 – 10/03/09.  That’s an average of 500 per day.

Here’s a chart showing our blog traffic growth over 2009:

As you can see we had tremendous growth and we’re expecting more in 2010.  Thanks for your readership and especially your comments.  We’re looking forward to even more conversation this year.

Here’s a list of our top ten blog posts in 2009 (in order of most read) if you want to go back and review.

1. Amazon’s EC2 Generating 220M+ Annually
2. VMware vs. Amazon … ROUND ONE … FIGHT!
3. Why is Amazon’s SAS70 Audit Bogus?
4. EngineYard uses Chef, a Puppet Alternative
5. The “Open” Cloud is Coming
6. VMware’s vCloud API Forces Cloud Standards
7. Amazon Threatens VPS Market
8. On Second Thought…How Big Is AWS Really?
9. Infrastructure-as-a-Service Builder’s Guide v1.0
10. Defining Infrastructure Clouds

It’s worth pointing out that the Infrastructure-as-a-Service Builder’s Guide made #9 in the list, but was posted on 12/19/09.  It made #9 in only 12 days time.  The actual white paper has been downloaded almost 1,000 times in less than one month.

Again, thanks so much for readership.

Best,

–Randy Bias, CEO, Cloudscaling

As you know, since then quite a bit has changed.  Amazon’s Elastic Compute Cloud crossed the Atlantic to Europe, EC2 opened up a U.S. West Coast presence, AWS also recently pre-announced their Asian expansion, and a number of other clouds sprung up across the globe, including a very strong new Australian entrant, Cloud Central.[1]

All of this goes to show that my prediction around the importance of reach in cloud computing is coming true.  One of the examples that brings this home that I enjoy talking about is Friendster.

For those of you new to social networking, Friendster was one of the very first social networks.  They were a true first mover in the space, but due to some strategic and tactical errors, they quickly fell behind sites like MySpace, Facebook, and LinkedIn. Except in the AsiaPacific region!

Friendster is one of the largest social networking sites still within that geographic region. You can see how they have re-tooled their business to be friendly to the AsiaPac region by providing localization in many Asian languages.

Now here’s the kicker: Friendster’s initial infrastructure was all in the United States.  What happens when your market changes underneath you?  How do you respond?  What tools are there to adapt?

As cloud computing goes global, it’s very nature provides a whole new opportunity in how businesses think about responding to market shifts.  Now you can follow-the-sun, follow-the-moon, follow-the-law, and up and move your entire application to a new country with much less effort than ever before … and, it will get even easier over time.

Cloud computing is going global and it’s going to change the way we think about service delivery models completely.

Of course, we welcome comments and feedback.  They will be incorporated into future revisions.  The paper itself does go into some technical depth in a few areas, but we can provide quite a bit more color in our workshops.

For your reading pleasure, I present our first big technical whitepaper:

• The Infrastructure-as-a-Service Builder’s Guide v1.0 (PDF)

Thanks!

The Cloudscaling Team

Ps. We realize the definition of ‘workload’ or ‘cloud workload’ is not as crisp as it could be and request your feedback and thinking on better nomenclature or definitions.  Credit will be given as appropriate.

To be clear, the top three U.S. clouds do not use iSCSI SANs: Amazon’s EC2, Rackspace Cloud, and GoGrid, all use local RAID subsystems.  This is common knowledge.  Of the early cloud pioneers, as far as I’m aware, mostly the U.K.-based clouds such as ElasticHosts and FlexiScale use iSCSI SANs.  The latest set of new cloud entrants, such as Savvis, Terremark, and Hosting.com all use either iSCSI or Fiber Channel-based SANs.  This is also commonly known.

Your Mileage May Vary on these performance numbers.  I’m not trying to highlight any ‘right’ way to build a cloud here.  I’m simply trying to show what the difference in performance is between a single SATA disk and a VM disk drive backed by an iSCSI SAN over a single Gigabit Ethernet.

This is not a robust performance and benchmarking analysis.  It’s a simple “run the numbers and compare” blog posting.  These are by no means authoritative performance numbers and that’s not their purpose either.  Their purpose is to highlight how performance differs between a single spindle and many in a RAID configuration, even when that RAID is available via a SAN over Gigabit Ethernet.

Please avoid overly critiquing the testing technique here.  It’s not meant to be robust, so nitpicking it serves no purpose.

Setup & Methodology
This is a very simple test in the Cloudscaling hosting & cloud lab environment.  Both servers running the test are on latest Ubuntu Jaunty Jackalope release.  One is a physical server with a single SATA disk and the other is a VMware vSphere VM backed by an iSCSI LUN.  The iSCSI LUN is provided by a ZFS-based SAN product called NexentaStor from Nexenta Systems.  This is an OpenSolaris derivative and a very cost effective alternative to say a NetApp or EqualLogic system.

The iSCSI SAN hardware is a simple Sun x2200 M2 with a Sun J4200 JBOD and 6 15K RPM SAS drives.

The bonnie++ command line was as simple as possible:

bonnie++ -n 512

Basic Numbers
Here is a basic high-level chart showing the numbers.

Figure 1. High level of SATA vs. VM disk

The first thing you will notice, of course, is the two big spikes for sequential and random file reads.  These numbers are artificially inflated as clearly 325,000 IOPS for sequential and 460,000 IOPS for random reads are ridiculous.  This is likely due to caching either in the OS or the controller on the physical box.  bonnie++ is supposed to account for this, but for some reason, in this instance it did not.  So it might be a little easier to evaluate the relative performance on a logarithmic scale:

Figure 2. Logarithmic scale for test Results

Much better.  What is easier to notice here is that the VM generally performs better on both standard measures of disk speed: raw throughput and disk operations (I/O per second or IOPS) with the obvious exception of the two aberrant data points.

Removing those two data points will give us an even clearer picture:

Figure 3. Normalized test results

Great.  Now this is very clear.  As you can see, the first half of the chart shows raw throughput (Kbytes/second).  When reading blocks from the VM disk we’re nearly saturating the gigabit ethernet link which should top out at 125Mbps theoretical, and we’re hitting 107MBps on average over 10 runs, so this is quite acceptable.  The SATA disk, in comparison gets just over 60MBps, which is about right, even though the SATA spec and controller are capable of more.  Sustained block reads from SATA disks will typically be 60-80MBps in the real world.

Much more interesting is the number of IOPS.  Many real world disk workloads, like a database spend the majority of their time doing large amounts of their ’seeking’ from one position of the disk to another, meaning lots of random file access.  They will bottleneck on waiting for the disk ‘head’ to move from one position to another on a disk drive and read new data.  It’s hard to tell the difference above because the SATA disk is so slow it barely registers on the chart.

If we change to a logarithmic scale again the data becomes much easier to read:

Figure 4. Normalized logarithmic scale test data

Now you can see that doing random seeks (i.e. moving the head of the disk drive from one location to a new one to read a piece of data) are starkly different.  A single SATA disk gets about 185 IOPS while a set of 6 SAS disks in the SAN is right around 10,000 IOPS.  This is a huge performance difference.  There are several reasons for this.  One, a typical SATA disk has an average latency of 8.5ms and a 15K SAS disk has only 3ms.  Also, with 6 disks in a RAID configuration, I have 6x more disk heads to read with.

It’s still a bit hard to see with this chart, but for most of the rest of the IOPS tests above, the SAN solution is roughly 3x the performance of the single disk.  For example, Sequential File deletion is 2,573 (SAN) vs. 840 (SATA).

Rather than going through the entire set of results, I recommend you download my simple spreadsheet.

Note that for Amazon, Rackspace, or GoGrid, local VM disk results will likely look very similar to the iSCSI SAN results for IOPS and sequential read/write (first half of chart) will be much higher.

Amazon’s Elastic Block Storage (EBS) would have similar performance characteristics to the iSCSI SAN above and hence you can see why it can be acceptable for running a database.

Summary
My point here is very simple.  I want to highlight the difference between purchasing a dedicated server with a single (or small number of) SATA disks vs. going with a cloud solution that uses a shared iSCSI SAN or local RAID on a single physical node.  Purchasing your  own dedicated server solution with a RAID can be extremely costly compared to a similar cloud solution.

More importantly, for those workloads that require random I/O and file access, like database applications, RAID is clearly a winner.  That’s why using a shared RAID (via an iSCSI SAN or a local RAID) on a physical node for your cloud VM can be a clear advantage of the cloud today.