Search results matching tags 'Best Practices', 'Development', 'Windows Azure', and 'Design'

Preparation is key to a successful cloud deployment

BuckWoody — Tue, 01 May 2012 13:09:16 GMT

If you want to be wise, watch the actions and outcomes of others. Emulate the successful actions, and avoid the actions that cause failure. That’s true in life in general - and in technology projects in specific.

I’ve worked with several clients who have created or migrated an application to “the cloud” - meaning using Microsoft Windows Azure or another provider. Although the statement in the title of this post is trite, I cannot over-emphasize how accurate it is. In every case of those who had a great experience with a distributed computing environment (which is thankfully the vast majority of my projects),

What kind of preparation do you need to do? Here are some tips I’ve learned in the successful (and not-so-successful) deployments I’ve seen:

Follow standard recommendations for successful projects in general

You and your organization have probably done a few projects before - this one should have the same general attributes: a well-defined goal, a small, motivated team, a realistic timeline, and an adequate budget. I know, I know, you *never* seem to get those things - but if you don’t, you’ll fail. Simple as that.

Educate yourself

Computing technology started out on a single set of hardware for a single purpose - and realizing the limits of the hardware at hand, systems designers quickly realized that scale-out and virtualization was key. No, that’s not new - mainframes almost always worked on the concept of scale-out and virtual machines. But we switched in the 1980’s to single-user systems again, and we’ve been there ever since. By that I mean you install an OS on the things you work on. Now we move back to distributed system concepts, and there are some real differences. You’ll need to learn how those work, and do things a new way. Hey, we’re IT - we LOVE learning new things, right?

Get a partner if needed

There are a few of us white-haired Gandalf’s around that remember how to work in a distributed system, but if it’s new to you, that’s completely OK. You can save yourself a world of trouble by working with someone who’s done this before - a partner you hire, someone from Microsoft Consulting, whatever.

And don’t forget support - who will handle each issue, what is the escalation model, who are your contacts at Microsoft, and what is your “light’s out” strategy?

“A new broom sweeps clean”, the old adage goes, but the old brooms know where the dirt is.

Build a model

Take some time to do a Proof of Concept on your local system and using your Azure hours from your MSDN account if you have one. Going through this build - and being willing to throw it away and try it a different way - is invaluable.

Test your theories

Three statisticians are walking in a field. They see a rabbit - the first guy raises his gun, firing far in front of the rabbit. The second guy simultaneously raises his gun and fires far behind the rabbit. The third guy yells “We got him!”

Not every theory is correct - not every attempt is the right one. Build in your success tests while you’re building your model. Then check them - don’t leave this step out.

Rinse, lather, repeat

This is advice from a shampoo bottle - which I’ve never used (I don’t really have that much hair - especially now). But in a “Cloud” project, it’s important. It’s an evolving system, that gains new improvements at an amazing rate. As soon as you deploy and stabilize you need to start the process over again. If you created your system in a Services model, with contracts for the APIs and abstracted code, this is far easier.

It’s not hard to do a cloud project right. But it’s really simple to do it wrong. Follow these guidelines and you’ll learn from the successes - and mistakes - of others.

Application Lifecycle Management Overview for Windows Azure

BuckWoody — Tue, 07 Feb 2012 14:58:39 GMT

Developing in Windows Azure is at once not that much different from what you’re familiar with in on-premises systems, and different in significant ways. Because of these differences, developers often ask about the specific process to develop and deploy a Windows Azure application - more formally called an Application Lifecycle Management, or ALM.

There are specific resources you can use to learn more about various parts of ALM - I’ve referenced those at the end of this post. But ALM has multiple definitions, from the governance of code injection, domain upgrade, testing, process flow and more. Many developers are interested in the finer-grained information, like how do I develop and deploy an application? What tools do I need, and how do I get the code running somewhere that I can test?

I’ll cover the very high-level process here, and refer you to specifics at the end of each section, so that you can take it all in at one viewing, and then bookmark for more detail when you need more information. I won’t be covering processes like Continuous Integration or Agile and other methodologies in this post - I’ll blog those later.

Initial Development

You start with writing code. You have three ways to do this. You can use Visual Studio (even the Express Edition Works), Eclipse, or by leveraging the REST API format. You can do this in a standalone (non-connected) environment like your laptop.

Using Visual Studio is one of the simplest methods to create an Azure application, allowing you to combine the Azure components you want to leverage (Storage, Compute, SQL Azure, the Service Bus, etc.) along with the on-premises code you have now or are creating. Once you’ve installed and patched Visual Studio, just download and install the Windows Azure Software Development Kit (SDK) and you’ll have not only all the API’s you need to talk to Azure, but a fully functioning local environment to run and test your code before you deploy it. You’ll also get a robust set of samples. You can download what you need for all of that (free) here: http://www.windowsazure.com/en-us/develop/downloads/ . There’s a step-by-step process here: http://msdn.microsoft.com/en-us/magazine/ee336122.aspx

You can also use Eclipse to develop for Windows Azure. You won’t get the full runtime environment in just that kit alone, but you can use this successfully on a Linux system. I have several folks using this method. The downloads and documentation for that is here: http://www.windowsazure4e.org/

You can use REST API’s to hit Azure Assets and control them. Not my preferred method, but possible. There are REST API’s for various sections of Azure. You can find the main reference for that here: http://msdn.microsoft.com/en-us/library/windowsazure/ff800682.aspx

Note: We recently demonstrated using a Cloud-based Integrated Development Environment (IDE) for Node.js deployment to Windows Azure. More on that here: http://www.readwriteweb.com/cloud/2012/01/cloud9-ide-to-enable-nodejs-ap.php

Deploying to a Test Instance

After you write the code, you’ll need to test it somewhere. The Azure Emulator on your development laptop is for a single user on that laptop, and it also has some subtle differences from the production fabric as you might imagine. Normally you’ll set up a small subscription to run and test the application, just like you would have a set of test servers. Each subscription has its own management keys and certificates, so this assists in keeping the testing environment separate for billing and control.

More on that general information here: http://msdn.microsoft.com/en-us/library/ff803362.aspx

Deploying to Production

Once you have developed the code and tested it, you need to move it to a location where users can access it. In reality, there is no physical difference in the type of machines, fabric or any other component in “Production” Windows Azure accounts and the “Test” accounts, but you’ll most often pick smaller systems to deploy on in testing, and you’ll probably keep the URL in the plain format.

In the Production Windows Azure account, the team normally limits the access to the account for deployment to a separate set of developers. This ensures code flow and control. A DNS name is normally mapped to the longer, Microsoft-generated URL so that your users access the application or data the way you want them to.

More on setting up an account here: http://techinch.com/2010/06/14/setup-your-windows-azure-account/

Managing Code Change

With the application deployed, there are two broad tasks you need to consider. One is managing changes through the application, and the other involves management, monitoring and performance tuning for an application.

To make a code change, the standard ALM process is followed, just as above. You can use command-line tools to automate the process as you would with an on-premises system. A vide on that shows you how: http://www.microsoftpdc.com/2009/SVC25. Normally this is used with an “In-Place” upgrade into Production Account, since your testing is completed in a separate account. More on that process here: http://msdn.microsoft.com/en-us/library/windowsazure/ee517255.aspx

One difference is the “VIP Swap” process you can use for the final push to Production. In essence, this allows you to have two copies of the application running on the Production account, with a quick way to cut over and back when you’re ready. The process for that is detailed here: http://msdn.microsoft.com/en-us/library/windowsazure/ee517253.aspx

For monitoring, you have several options. You should enable the Windows Azure Diagnostics in your code - more on that here: http://archive.msdn.microsoft.com/WADiagnostics.

You can observe uptime and other information on the Windows Azure Service Dashboard, where you can also consume the uptime as an RSS feed: http://www.windowsazure.com/en-us/support/service-dashboard/

From there, you can also use System Center to monitor not only Windows Azure deployments but internal applications as well. The Management Pack and documentation for that is here: http://www.microsoft.com/download/en/details.aspx?id=11324.

There are also 3rd-party tools to manage Windows Azure. More on that here: http://www.bing.com/search?q=monitor+Windows+Azure&form=OSDSRC

Other References:

There is a lot more detail in this official reference: https://www.windowsazure.com/en-us/develop/net/fundamentals/deploying-applications/

Bryan Group explains the ramifications of the Secure Development Lifecycle (SDL) with lots of collateral you can review: http://blogs.msdn.com/b/bryang/archive/2011/04/26/applying-the-sdl-to-windows-azure.aspx

Rip and Replace or Extend and Embrace?

BuckWoody — Tue, 13 Sep 2011 11:20:05 GMT

As most of you know, I don’t like the term “cloud” very
much. It isn’t defined, which means it can be anything. I prefer “distributed
computing”, which is more technically accurate and describes what you’re doing
in more concrete terms.

So when you think about Windows and SQL Azure, you don’t
have to think about an entire product – you can use parts of the system
together or independently to accomplish what you need to do. You can use the
computing functions, storage, and more and more I see folks leverage the
Service Bus to enable current applications to expose things to the web.

And that brings up the point of this post. Once you decide
that a distributed architecture works to solve a problem, you’re faced with a
decision: should you completely re-write your architecture to take advantage of
the current systems or should you just fold in new code that makes the data or
function available to the web?

Of course, the answer is always “it depends” on the situation
– and it does. But unless you’re fixing a problem with current code, I usually
advocate a migration approach. That means at the very least retaining the
business logic (again, unless it’s not currently working) and as much of the
code as you can. In fact, if you follow this paradigm, you’re on your way to
making a Service Bus out of the functions you currently have. You can expose
the results of a system rather than opening the system up. Let’s take an
example.

Assume for a moment that you have an order-taking system
on-premise. That system performs many functions, one of which might creating a
Purchase Order. Your system might be enclosed, meaning that it has an
application that talks to a middle-tier, and then from there to a database
system. A query is generated from a screen, and passed along to eventually
compute, store and return a Purchase Order Number, along with other
information. Imagine now that you wire up the code not only to return the PO
number to the client, but to make that number available on an endpoint –
actually really not that hard to do.

Now you can make that PO number available to the web using
Azure. You could restrict who can make that call to the system, or open it up
to a broader audience. Or instead of the PO Number, you could make a product
list available. And you can go further than that – EBay, for instance, uses the
OData protocol (which is very cool in and of itself) which you can query from
the web. You could compare your company’s product catalog to what is on EBay,
and list the items you have there if there are no competitors in that space.
And on and on it goes.

So the point is this – where you can, retain what works.
Fold in systems like Azure where they make sense. Extend and Embrace.

Plan for Diagnostics in Cloud Computing From the Git-Go

BuckWoody — Tue, 06 Sep 2011 13:11:22 GMT

“Git-Go” is something we say in the South that means “right at the start”. I’ve seen several applications for on-premise systems that don’t have much in the way of diagnostics - the developers rely on a debugger, the event logs on the server and client workstation, and most of all, the ability to watch the system from end-to-end.

This approach is a mistake for an on-premise system, and it’s definitely a problem for a distributed architecture. You simply do not own all of the components from end to end in a cloud environment, nor are you always able to attach a debugger or other remote monitoring tools to the various areas within the code path. So you need to make sure that from the very outset of your design that you build in diagnostics. My personal preference is to build a system such that a control file turns on deeper information gathering from the system, up to a minimal level.

When I do that, I set a high level of logging, a medium level, and a moderate level. I normally use the deepest level of information during the testing and acceptance phase of the deployment, then switch to moderate and then the least level of information gathering. Also in my design I often set an error condition to begin gathering the deeper information along with the exception, where possible.

There are decisions you need to make as to where to store the diagnostics (many operations in the cloud cost money), how often you collect them, and so on. You can get a quick overview on using the diagnostics that come with Windows Azure here: http://www.azuresupport.com/2010/03/getting-started-with-windows-azure-diagnostics-and-monitoring/ This is where you should start first. More detail on that: http://msdn.microsoft.com/en-us/library/gg433048.aspx

My friend Dave Pallman has a great tool he’s released for free: http://davidpallmann.blogspot.com/2009/03/azure-application-monitor-now-on.html

If the issue is in storage apps: http://social.msdn.microsoft.com/Forums/en-US/windowsazuredata/thread/d84ba34b-b0e0-4961-a167-bbe7618beb83

If you have System Center, this is the quickest and easiest way to implement the monitoring – really handy: http://pinpoint.microsoft.com/en-us/applications/windows-azure-application-monitoring-management-pack-release-candidate-12884907699