Tag Archives: azure

Our Cloud Products And How We Did It

Hey, I’m not a sales guy, and none of us spend a lot of time on this blog pimping our company’s products, but we’re pretty proud of our work on them and I figured I’d toss them out there as use cases of what an enterprise can do in terms of cloud products if they get their act together!

Some background.  Currently all the agile admins (myself, Peco, and James) work together in R&D at National Instruments.  It’s funny, we used to work together on the Web Systems team that ran the ni.com Web site, but then people went their own ways to different teams or even different companies. Then we decided to put the dream team back together to run our new SaaS products.

About NI

Some background.  National Instruments (hereafter, NI) is a 5000+ person global company that makes hardware and software for test & measurement, industrial control, and graphical system design. Real Poindextery engineering stuff. Wireless sensors and data acquisition, embedded and real-time, simulation and modeling. Our stuff is used to program the Lego Mindstorms NXT robots as well as control CERN’s Large Hadron Collider. When a crazed highlander whacks a test dummy on Deadliest Warrior and Max the techie looks at readouts of the forces generated, we are there.

About LabVIEW

Our main software product is LabVIEW.  Despite being an electrical engineer by degree, we never used LabVIEW in school (this was a very long time ago, I’ll note, most programs use it nowadays), so it wasn’t till I joined NI I saw it in action. It’s a graphical dataflow programming language. I assumed that was BS when I heard it. I had so many companies try to sell be “graphical” programming over the years, like all those crappy 4GLs back in the ’9o’s, that I figured that was just an unachieved myth. But no, it’s a real visual programming language that’s worked like a champ for more than 20 years. In certain ways it’s very bad ass, it does parallelism for you and can be compiled and dropped onto a FPGA. It’s remained niche-ey and hasn’t been widely adopted outside the engineering world, however, due to company focus more than anything else.

Anyway, we decided it was high time we started leveraging cloud technologies in our products, so we created a DevOps team here in NI’s LabVIEW R&D department with a bunch of people that know what they’re doing, and started cranking on some SaaS products for our customers! We’ve delivered two and have announced a third that’s in progress.

Cloud Product #1: LabVIEW Web UI Builder

First out of the gate – LabVIEW Web UI Builder. It went 1.0 late last year. Go try it for free! It’s a Silverlight-based RIA “light” version of LabVIEW – you can visually program, interface with hardware and/or Web services. As internal demos we even had people write things like “Duck Hunt” and “Frogger” in it – it’s like Flash programming but way less of a pain in the ass. You can run in browser or out of browser and save your apps to the cloud or to your local box. It’s a “freemium” model – totally free to code and run your apps, but you have to pay for a license to compile your apps for deployment somewhere else – and that somewhere else can be a Web server like Apache or IIS, or it can be an embedded hardware target like a sensor node. The RIA approach means the UI can be placed on a very low footprint target because it runs in the browser, it just has to get data/interface with the control API of whatever it’s on.

It’s pretty snazzy. If you are curious about “graphical programming” and think it is probably BS, give it a spin for a couple minutes and see what you can do without all that “typing.”

A different R&D team wrote the Silverlight code, we wrote the back end Web services, did the cloud infrastructure, ops support structure, authentication, security, etc. It runs on Amazon Web Services.

Cloud Product #2: LabVIEW FPGA Compile Cloud

This one’s still in beta, but it’s basically ready to roll. For non-engineers, a FPGA (field programmable gate array) is essentially a rewritable chip. You get the speed benefits of being on hardware – not as fast as an ASIC but way faster than running code on a general purpose computer – as well as being able to change the software later.

We have a version of LabVIEW, LabVIEW FPGA, used to target LabVIEW programs to an FPGA chip. Compilation of these programs can take a long time, usually a number of hours for complex designs. Furthermore the software required for the compilation is large and getting more diverse as there’s more and more chips out there (each pretty much has its own dedicated compiler).

So, cloud to the rescue. The FPGA Compile Cloud is a simple concept – when you hit ‘compile’ it just outsources the compile to a bunch of servers in the cloud instead of locking up your workstation for hours (assuming you’ve bought a subscription).  FPGA compilations have everything they need with them, there’s not unique compile environments to set up or anything, so it’s very commoditizable.

The back end for this isn’t as simple as the one for UI Builder, which is just cloud storage and load balanced compile servers – we had to implement custom scaling for the large and expensive compile workers, and it required more extensive monitoring, performance, and security work. It’s running on Amazon too. We got to reuse a large amount of the infrastructure we put in place for systems management and authentication for UI Builder.

Cloud Product #3: Technical Data Cloud

It’s still in development, but we’ve announced it so I get to talk about it! The idea behind the Technical Data Cloud is that more and more people need to collect sensor data, but they don’t want to fool with the management of it. They want to plop some sensors down and have the acquired data “go to the cloud!” for storage, visualization, and later analysis. There are other folks doing this already, like the very cool Pachube (pronounced “patch-bay”, there’s a LabVIEW library for talking to it), and it seems everyone wants to take their sensors to the cloud, so we’re looking at making one that’s industrial strength.

For this one we are pulling our our big guns, our data specialist team in Aachen, Germany. We are also being careful to develop it in an open way – the primary interface will be RESTful HTTP Web services, though LabVIEW APIs and hardware links will of course be a priority.

This one had a big technical twist for us – we’re implementing it on Microsoft Windows Azure, the MS guys’ cloud offering. Our org is doing a lot of .NET development and finding a lot of strategic alignment with Microsoft, so we thought we’d kick the tires on their cloud. I’m an old Linux/open source bigot and to be honest I didn’t expect it to make the grade, but once we got up to speed on it I found it was a pretty good bit of implementation. It did mean we had to do significant expansion of our underlying platform we are reusing for all these products – just supporting Linux and Windows instance in Amazon already made us toss a lot of insufficiently open solutions in the garbage bin, and these two cloud worlds are very different as well.

How We Did It

I find nothing more instructive than finding out the details – organizational, technical, etc. – of how people really implement solutions in their own shops.  So in the interests of openness and helping out others, I’m going to do a series on how we did it!  I figure it’ll be in about three parts, most likely:

  • How We Did It: People
  • How We Did It: Process
  • How We Did It: Tools and Technologies

If there’s something you want to hear about when I cover these areas, just ask in the comments!  I can’t share everything, especially for unreleased products, but promise to be as open as I can without someone from Legal coming down here and Tasering me.

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Amazon CloudFormation: Model Driven Automation For The Cloud

You may have heard about Amazon’s newest offering they announced today, CloudFormation.  It’s the new hotness, but I see a lot of confusion in the Twitterverse about what it is and how it fits into the landscape of IaaS/PaaS/Elastic Beanstalk/etc. Read what Werner Vogels says about CloudFormation and its uses first, but then come back here!

Allow me to break it down for you and explain why this is such a huge leverage point for cloud developers.

What Has Come Before

Up till now on Amazon you could configure up a single virtual image the way you wanted it, with an AMI. You could even kind of construct a scalable tier of similar systems using Auto Scaling, by defining Launch Configurations. But if you wanted to construct an entire multitier system it was a lot harder.  There are automated configuration management tools like chef and puppet out there, but their recipes/models tend to be oriented around getting a software loadout on an existing system, not the actual system provisioning – in general they come from the older assumption you have someone doing that on probably-physical systems using bcfg2 or cobber or vagrant or something.

So what were you to do if you wanted to bring up a simple three tier system, with a Web tier, app server tier, and database tier?  Either you had to set them up and start them manually, or you had to write code against the Amazon APIs to explicitly pull up what you wanted. Or you had to use a third party provisioning provider like RightScale or EngineYard that would let you define that kind of model in their Web consoles but not construct your own model programmatically and upload it. (I’d like my product functionality in my own source control and not your GUI, thanks.)

Now, recently Amazon launched Elastic Beanstalk, which is more way over on the PaaS side of things, similar to Google App Engine.  “Just upload your application and we’ll run it and scale it, you don’t have to worry about the plumbing.” Of course this sharply limits what you can do, and doesn’t address the question of “what if my overall system consists of more than just one Java app running in Beanstalk?”

If your goal is full model driven automation to achieve “infrastructure as code,” none of these solutions are entirely satisfactory. I understand CloudFormation deeply because we went down that same path and developed our own system model ourselves as a response!

I’ll also note that this is very similar to what Microsoft Azure does.  Azure is a hybrid IaaS/PaaS solution – their marketing tries to say it’s more like Beanstalk or Google App Engine, but in reality it’s more like CloudFormation – you have an XML file that describes the different roles (tiers) in the system, defines what software should go on each, and lets you control the entire system as a unit.

So What Is CloudFormation?

Basically CloudFormation lets you model your Amazon cloud-based system in JSON and then provision and control it as a unit.  So in our use case of a three tier system, you would model it up in their JSON markup and then CloudFormation would understand that the whole thing is a unit.  See their sample template for a WordPress setup. (A mess more sample templates are here.)

Review the WordPress template; it lets you define the AMIs and instance types, what the security group and ELB setups should be, the RDS database back end, and feed in variables that’ll be used in the consuming software (like WordPress username/password in this case).

Once you have your template you can tell Amazon to start your “stack” in the console! It’ll even let you hook it up to a SNS notification that’ll let you know when it’s done. You name the whole stack, so you can distinguish between your “dev” environment and your “prod” environment for example, as opposed to the current state of the Amazon EC2 console where you get to see a big list of instance IDs – they added tagging that you can try to use for this, but it’s kinda wonky.

Why Do I Want This Again?

Because a system model lets you do a number of clever automation things.

Standard Definition

If you’ve been doing Amazon yourself, you’re used to there being a lot of stuff you have to do manually.  From system build to system build even you do it differently each time, and God forbid you have multiple techies working on the same Amazon system. The basic value proposition of “don’t do things manually” is huge.  You configure the security groups ONCE and put it into the template, and then you’re not going to forget to open port 23 AGAIN next time you start a system. A core part of what DevOps is realizing as its value proposition is treating system configuration as code that you can source control, fix bugs in and have them stay fixed, etc.

And if you’ve been trying to automate your infrastructure with tools like Chef, Puppet, and ControlTier, you may have been frustrated in that they address single systems well, but do not really model “systems of systems” worth a damn.  Via new cloud support in knife and stuff you can execute raw “start me a cloud server” commands but all that nice recipe stuff stops at the box level and doesn’t really extend up to provisioning and tracking parts of your system.

With the CloudFormation template, you have an actual asset that defines your overall system.  This definition:

  • Can be controlled in source control
  • Can be reviewed by others
  • Is authoritative, not documentation that could differ from the reality
  • Can be automatically parsed/generated by your own tools (this is huge)

It’s also nicely transparent; when you go to the console and look at the stack it shows you the history of events, the template used to start it, the startup parameters it used… Moving away from the “mystery meat” style of system config.

Coordinated Control

With CloudFormation, you can start and stop an entire environment with one operation. You can say “this is the dev environment” and be able to control it as a unit. I assume at some point you’ll be able to visualize it as a unit, right now all the bits are still stashed in their own tabs (and I notice they don’t make any default use of their own tagging, which makes it annoying to pick out what parts are from that stack).

This is handy for not missing stuff on startup and teardown… A couple weeks ago I spent an hour deleting a couple hundred rogue EBSes we had left over after a load test.

And you get some status eventing – one of the most painful parts of trying to automate against Amazon is the whole “I started an instance, I guess I’ll sit around and poll and try to figure out when the damn thing has come up right.”  In CloudFront you get events that tell you when each part and then the whole are up and ready for use.

What It Doesn’t Do

It’s not a config management tool like Chef or Puppet. Except for what you bake onto your AMI it has zero software config capabilities, or command dispatch capabilities like Rundeck or mcollective or Fabric. Although it should be a good integration point with those tools.

It’s not a PaaS solution like Beanstalk or GAE; you use those when you just have an app you want to deploy to something that’ll run it.  Now, it does erode some use cases – it makes a middle point between “run it all yourself and love the complexity” and “forget configurable system bits, just use PaaS.”  It allows easy reusability, say having a systems guy develop the template and then a dev use it over and over again to host their app, but with more customization than the pure-play PaaSes provide.

It’s not quite like OVF, which is more fiddly and about virtually defining the guts of a single machine than defining a set of systems with roles and connections.

Competitive Analysis

It’s very similar to Microsoft Azure’s approach with their .cscfg and .csdef files which are an analogous XML model – you really could fairly call this feature “Amazon implements Azure on Amazon” (just as you could fairly call Elastic Beanstalk “Amazon implements Google App Engine on Amazon”.) In fact, the Azure Fabric has a lot more functionality than the primitive Amazon events in this first release. Of course, CloudFormation doesn’t just work on Windows, so that’s a pretty good width vs depth tradeoff.

And it’s similar to something like a RightScale, and ideally will encourage them to let customers actually submit their own definition instead of the current clunky combo of ServerArrays and ServerTemplates (curl or Web console?  Really? Why not a model like this?). RightScale must be in a tizzy right now, though really just integrating with this model should be easy enough.

Where To From Here?

As I alluded, we actually wrote our own tool like this internally called PIE that we’re looking to open source because we were feeling this whole problem space keenly.  XML model of the whole system, Apache Zookeeper-based registry, kinda like CloudFormation and Azure. Does CloudFormation obsolete what we were doing?  No – we built it because we wanted a model that could describe cloud systems on multiple clouds and even on premise systems. The Amazon model will only help you define Amazon bits, but if you are running cross-cloud or hybrid it is of limited value. And I’m sure model visualization tools will come, and a better registry/eventing system will come, but we’re way farther down that path at least at the moment. Also, the differentiation between “provisioning tools” that control and start systems like CloudFormation and bcfg2 and “configuration” tools that control and start software like Chef and Puppet (and some people even differentiate between those and “deploy” tools that control and start applications like Capistrano) is a false dichotomy. I’m all about the “toolchain” approach but at some point you need a toolbelt. This tool differentiation is one of the more harmful “Dev vs Ops” differentiations.

I hope that this move shows the value of system modeling and helps people understand we need an overarching model that can be used to define it all, not just “Amazon” vs “Azure” or “system packages” vs “developed applications” or “UNIX vs Windows…” True system automation will come from a UNIVERSAL model that can be used to reason about and program to your on premise systems, your Amazon systems, your Azure systems, your software, your apps, your data, your images and files…

Conclusion

You need to understand CloudFormation, because it is one of the most foundational changes that will have a lot of leverage that AWS has come out with in some time. I don’t bother to blog about most of the cool new AWS features, because they are cool and I enjoy them but this is part of a more revolutionary change in the way systems are managed, the whole DevOps thing.

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Inside Microsoft Azure

Recently, I delivered a presentation at the Austin Cloud User Group introducing them to Microsoft Azure.  I’m a UNIX bigot and have been doing the Amazon Cloud and open source thing, but we are delivering a product via Azure next so our team is learning it.  It’s actually quite interesting and has a number of good points; it’s mainly hindered by the Microsoft marketing message trying to pretend it’s all magical fairy dust instead of clearly explaining what it is and what it can do. So if you want to hear what Azure is in straight shooting UNIX admin speak, check it out!

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Microsoft Azure for Dummies – or for Smarties?

What Is Microsoft Azure?

I’m going to attempt to explain Microsoft Azure in “normal Web person” language.  Like many of you, I am more familiar with Linux/open source type solutions, and like many of you, my first forays into cloud computing have been with Amazon Web Services.  It can often be hard for people not steeped in Redmondese to understand exactly what the heck they’re talking about when Microsoft people try to explain their offerings.  (I remember a time some years ago I was trying to get a guy to explain some new Microsoft data access thing with the usual three letter acronym name.  I asked, “Is it a library?  A language?  A protocol?  A daemon?  Branding?  What exactly is this thing you’re trying to get me to uptake?”  The reply was invariably “It’s an innovative new way to access data!”  Sigh.  I never did get an answer and concluded “Never mind.”)

Microsoft has released their new cloud offering, Azure.  Our company is a close Microsoft partner since we use a lot of their technologies in developing our company’s desktop software products, so as “cloud guy” I’ve gotten some in depth briefings and even went to PDC this year to learn more (some of my friends who have known me over the course of my 15 years of UNIX administration were horrified).  “Cloud computing” is an overloaded enough term that it’s not highly descriptive and it took a while to cut through the explanations to understand what Azure really is.  Let me break it down for you and explain the deal.

Point of Comparison: Amazon (IaaS)

In Amazon EC2, as hopefully everyone knows by now, you are basically given entire dynamically-provisioned, hourly-billed virtual machines that you load OSes on and install software and all that.  “Like servers, but somewhere out in the ether.”  Those kinds of cloud offerings (e.g. Amazon, Rackspace, most of them really) are called Infrastructure As A Service (IaaS).  You’re responsible for everything you normally would be, except for the data center work.  Azure is not an IaaS offering but still bears a lot of similarities to Amazon; I’ll get into details later.

Point of Comparison: Google App Engine (PaaS)

Take Google’s App Engine as another point of comparison.  There, you just upload your Python or Java application to their portal and “it runs on the Web.”  You don’t have access to the server or OS or disk or anything.  And it “magically” scales for you.  This approach is called Platform as a Service (PaaS).   They provide the full platform stack, you only provide the end application.  On the one hand, you don’t have to mess with OS level stuff – if you are just a Java programmer, you don’t have to know a single UNIX (or Windows) command to transition your app from “But it works in Eclipse!” to running on a Web server on the Internet.  On the other hand, that comes with a lot of limitations that the PaaS providers have to establish to make everything play together nicely.  One of our early App Engine experiences was sad – one of our developers wrote a Java app that used a free XML library to parse some XML.  Well, that library had functionality in it (that we weren’t using) that could write XML to disk.  You can’t write to disk in App Engine, so its response was to disallow the entire library.  The app didn’t work and had to be heavily rewritten.  So it’s pretty good for code that you are writing EVERY SINGLE LINE OF YOURSELF.  Azure isn’t quite as restrictive as App Engine, but it has some of that flavor.

Azure’s Model

Windows Azure falls between the two.  First of all, Azure is a real “hosted cloud” like Amazon Web Services, like most of us really think about when we think cloud computing; it’s not one of these on premise things that companies are branding as “cloud” just for kicks. That’s important to say because it seems like nowadays the larger the company, the more they are deliberately diluting the term “cloud” to stick their products under its aegis.  Microsoft isn’t doing that, this is a “cloud offering” in the classical (where classical means 2008, I guess) sense.

However, in a number of important ways it’s not like Amazon.  I’d definitely classify it as a PaaS offering.  You upload your code to “Roles” which are basically containers that run your application in a Windows 2008(ish) environment.  (There are two types – a “Web role” has a stripped down IIS provided on it, a “Worker role” doesn’t – the only real difference between the two.)  You do not have raw OS access, and cannot do things like write to the registry.  But, it is less restrictive than App Engine.  You can bundle up other stuff to run in Azure – even run Java apps using Apache Tomcat.  You have to be able to install whatever you want to run “xcopy only” – in other words, no fancy installers, it needs to be something you could just copy the files to a Windows PC, without administrative privilege, and run a command from the command line and have it work.  Luckily, Tomcat/Java fits that description. They have helper packs to facilitate doing this with Tomcat, memcached, and Apache/PHP/MediaWiki.  At PDC they demoed Domino’s Pizza running their Java order app on it and a WordPress blog running on it.  So it’s not only for .NET programmers.  Managed code is easier to deploy, but you can deploy and run about anything that fits the “copy and run command line” model.

I find this approach a little ironic actually.  It’s been a lot easier for us to get the Java and open source (well, the ones with Windows ports) parts of our infrastructure running on Azure than Windows parts!  Everybody provides Windows stuff with an installer, of course, and you can’t run installers on Azure.  Anyway, in its core computing model it’s like Google App Engine – it’s more flexible than that (good) but it doesn’t do automatic scaling (bad).  If it did autoscaling I’d be willing to say “It’s better than App Engine in every way.”

In other ways, it’s a lot like Amazon.  They offer a variety of storage options – blobs (like S3), tables (like SimpleDB), queues (like SQS), drives (like EBS), SQL Azure (like RDS).  They have an integral CDN.  They do hourly billing.  Pricing is pretty similar to Amazon – it’s hard to totally equate apples to apples, but Azure compute is $0.12/hr and an Amazon small Windows image compute is $0.12/hr (Coincidence?  I think not.).  And you have to figure out scaling and provisioning yourself on Amazon too – or pay a lot of scratch to one of the provisioning companies like RightScale.

What’s Unique and Different

Well, the largest thing that I’ve already mentioned is the PaaS approach.  If you need OS level access, you’re out of luck;  if you don’t want to have to mess with OS management, you’re in luck!  So to the first order of magnitude, you can think of Azure as “like Amazon Web Services, but the compute uses more of a Google App Engine model.”

But wait, there’s more!

One of the biggest things that Azure brings to the table is that, using Visual Studio, you can run a local Azure “fabric” on your PC, which means you can develop, test, and run cloud apps locally without having to upload to the cloud and incur usage charges.  This is HUGE.  One of the biggest pains about programming for Amazon, for instance, is that if you want to exercise any of their APIs, you have to do it “up there.”  Also, you can’t move images back and forth between Amazon and on premise.  Now, there are efforts like EUCALYPTUS that try to overcome some of this problem but in the end you pretty much just have to throw in the towel and do all dev and test up in the cloud.  Amazon and Eclipse (and maybe Xen) – get together and make it happen!!!!

Here’s something else interesting.  In a move that seems more like a decision from a typical cranky cult-of-personality open source project, they have decided that proper Web apps need to be asynchronous and message-driven, and by God that’s what you’re going to do.  Their load balancers won’t do sticky sessions (only round robin) and time out all connections between all tiers after 60 seconds without exception.  If you need more than that, tough – rewrite your app to use a multi-tier message queue/event listener model.  Now on the one hand, it’s hard for me to disagree with that – I’ve been sweating our developers, telling them that’s the correct best-practice model for scalability on the Web.  But again you’re faced with the “Well what if I’m using some preexisting software and that’s not how it’s architected?” problem.  This is the typical PaaS pattern of “it’s great, if you’re writing every line of code yourself.”

In many ways, Azure is meant to be very developer friendly.  In a lot of ways that’s good.  As a system admin, however, I wince every time they go on about “You can deploy your app to Azure just by right clicking in Visual Studio!!!”  Of course, that’s not how anyone with a responsibly controlled production environment would do it, but it certainly does make for fast easy adoption in development.   The curve for a developer who is “just” a C++/Java/.NET/whatever wrangler to get up and going on an IaaS solution like Amazon is pretty large comparatively; here, it’s “go sign up for an account and then click to deploy from your IDE, and voila it’s running on the Intertubes.”  So it’s a qualified good – it puts more pressure on you as an ops person to go get the developers to understand why they need to utilize your services.  (In a traditional server environment, they have to go through you to get their code deployed.)  Often, for good or ill, we use the release process as a touchstone to also engage developers on other aspects of their code that need to be systems engineered better.

Now, that’s my view of the major differences.  I think the usual Azure sales pitch would say something different – I’ve forgotten two of their huge differentiators, their service bus and access control components.  They are branded under the name “AppFabric,” which as usual is a name Microsoft is also using for something else completely different (a new true app server for Windows Server, including projects formerly code named Dublin and Velocity – think of it as a real WebLogic/WebSphere type app server plus memcache.)

Their service bus is an ESB.  As alluded to above, you’re going to want to use it to do messaging.   You can also use Azure Queues, which is a little confusing because the ESB is also a message queue – I’m not clear on their intended differentiation really.  You can of course just load up an ESB yourself in any other IaaS cloud solution too, so if you really want one you could do e.g. Apache ServiceMix hosted on Amazon.  But, they are managing this one for you which is a plus.  You will need to use it to do many of the common things you’d want to do.

Their access control – is a mess.  Sorry, Microsoft guys.  The whole rest of the thing, I’ve managed to cut through the “Microsoft acronyms versus the rest of the world’s terms and definitions” factor, but not here.   “You see, you use ACS’s WIF STS to generate a SWT,” says our Microsoft rep with a straight face.   They seem to be excited that it will use people’s Microsoft Live IDs, so if you want people to have logins to your site and you don’t want to manage any of that, it is probably nice.  It takes SAML tokens too, I think, though I’m not sure if the caveats around that end up equating to “Well, not really.”  Anyway, their explanations have been incoherent so far and I’m not smelling anything I’m really interested in behind it.  But there’s nothing to prevent you from just using LDAP and your own Internet SSO/federation solution.  I don’t count this against Microsoft because no one else provides anything like this, so even if I ignore the Azure one it doesn’t put it behind any other solution.

The Future

Microsoft has said they plan to add on some kind of VM/IaaS offering eventually because of the demand.  For us, the PaaS approach is a bit of a drawback – we want to do all kinds of things like “virus scan uploaded files,” “run a good load balancer,” “run an LDAP server”, and other things that basically require more full OS access.  I think we may have an LDAP direction with the all-Java OpenDS, but it’s a pain point in general.

I think a lot of their decisions that are a short term pain in the ass (no installs, no synchronous) are actually good in the long term.  If all developers knew how to develop async and did it by default, and if all software vendors, even Windows based ones, provided their product in a form that could just be “copy and run without admin privs” to install, the world would be a better place.  That’s interesting in that “Sure it’s hard to use now but it’ll make the world better eventually” is usually heard from the other side of the aisle.

Conclusion

Azure’s a pretty legit offering!  And I’m very impressed by their velocity.  I think it’s fair to say that overall Azure isn’t quite as good as Amazon except for specific use cases (you’re writing it all in .NET by hand in Visual Studio) – but no one else is as good as Amazon either (believe me, I evaluated them) and Amazon has years of head start; Azure is brand new but already at about 80%! That puts them into the top 5 out of the gate.

Without an IaaS component, you still can’t do everything under the sun in Azure.  But if you’re not depending on much in the way of big third party software chunks, it’s feasible; if you’re doing .NET programming, it’s very compelling.

Do note that I haven’t focused too much on the attributes and limitations of cloud computing in general here – that’s another topic – this article is meant to compare and contrast Azure to other cloud offerings so that people can understand its architecture.

I hope that was clear.  Feel free and ask questions in the comments and I’ll try to clarify!

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