Monthly Archives: March 2013

Talk (Guest Speaker at BU): Architecting to be Cloud Native – On Windows Azure or Otherwise

Tonight I had the honor of being a guest lecturer at a Boston University graduate cloud computing class – BU MET CS755, Cloud Computing, taught by Dino Konstantopoulos.

The theme of my talk was Architecting to be Cloud Native – On Windows Azure or Otherwise. The slide deck I used is included below.

Night class is tough. Thanks for a warm reception – so congratulations and many thanks to those of you able to stay awake until 9:00 PM (!).

clip_image001.png I hope to see all of you at future Boston Azure events – to get announcements, Join our Meetup Group. We are also the world’s first/oldest Azure User Group. Here are a couple of upcoming events:

Feel free to reach out with any questions (twitter (@codingoutloud) or  email (codingoutloud at gmail)) — especially if it will be “on the midterm” – and good luck in the cloud!

Bill Wilder



Talk: Azure Best Practices – How to Successfully Architect Windows Azure Apps for the Cloud

Webinar Registration:

  • Azure Best Practices – How to Successfully Architect Windows Azure Apps for the Cloud @ 1pm ET on 13-March-2013


Discover how you can successfully architect Windows Azure-based applications to avoid and mitigate performance and reliability issues with our live webinar
Microsoft’s Windows Azure cloud offerings provide you with the ability to build and deliver a powerful cloud-based application in a fraction of the time and cost of traditional on-premise approaches.  So what’s the problem? Tried-and-true traditional architectural concepts don’t apply when it comes to cloud-native applications. Building cloud-based applications must factor in answers to such questions as:

  • How to scale?
  • How to overcome failure?
  • How to build a manageable system?
  • How to minimize monthly bills from cloud vendors?

During this webinar, we will examine why cloud-based applications must be architected differently from that of traditional applications, and break down key architectural patterns that truly unlock cloud benefits. Items of discussion include:

  • Architecting for success in the cloud
  • Getting the right architecture and scalability
  • Auto-scaling in Azure and other cloud architecture patterns

If you want to avoid long nights, help-desk calls, frustrated business owners and end-users, then don’t miss this webinar or your chance to learn how to deliver highly-scalable, high-performance cloud applications.



The core ideas were drawn from my Cloud Architecture Patterns (O’Reilly Media, 2012) book:


Hosted by Dell:


Azure Cloud Storage Improvements Hit the Target

Windows Azure Storage (WAS)

Brad Calder SOSP talk from

Brad Calder delivering SOSP talk

Since its initial release, Windows Azure has offered a storage service known as Windows Azure Storage (WAS). According to the SOSP paper and related talk published by the team (led by Brad Calder), WAS is architected to be a “Highly Available Cloud Storage Service with Strong Consistency.” Part of being highly availably is keeping your data safe and accessible. The SOSP paper mentions that the WAS service retains three copies of every stored byte, and (announced a few months before the SOSP paper) another asynchronously geo-replicated trio of copies in another data center hundreds of miles away in the same geo-political region. Six copies in total.

WAS is a broad service, offering not only blob (file) storage, but also a NoSQL store and a reliable queue.

Further, all of these WAS storage offerings are strongly consistent (as opposed to other storage approaches which are sometimes eventually consistent). Again citing the SOSP paper: “Many customers want strong consistency: especially enterprise customers moving their line of business applications to the cloud.” This is because traditional data stores are strongly consistent and code needs to be specially crafted in order to handle an eventually consistent model. This simplifies moving existing code into the cloud.

The points made so far are just to establish some basic properties of this system before jumping into the real purpose of this article: performance at scale. The particular points mentioned (highly available, storage in triplicate and then geo-replicated, strong consistency, and supporting also a NoSQL database and reliable queuing features) were highlighted since they may be considered disadvantages – rich capabilities that may be considered to hamper scalability and performance. Except that they don’t hamper scalability and performance at all. Read on for details.

Performance at Scale

A couple of years ago, Nasuni benchmarked the most important public cloud vendors on how their services performed on cloud file storage at scale (using workloads modeled after those observed from real world business scenarios). Among the public clouds tested were Windows Azure Storage (though only the blob/file storage aspect was considered), Amazon S3 (an eventually consistent file store), and a couple of others.

In the first published result in 2011, Nasuni declared Amazon S3 the overall winner, prevailing over Windows Azure Storage and others, though WAS fininshed ahead of Amazon in some of the tests. At the time of these tests, WAS was running on its first-generation network architecture and supported capacity as described in the team’s published scalability targets from mid-2010.

In 2012, Microsoft network engineers were busy implementing a new data center network design they are calling Quantum 10 (or Q10 for short). The original network design was hierarchical, but the Q10 design is flat (and uses other improvements like SSD for journaling). The end result of this dramatic redesign is that WAS-based network storage is much faster, more scalable, and as robust as ever. The corresponding Q10 scalability targets were published in November 2012 and show substantial advances. EDIT: the information on scalability targets and related factors is kept up to date in official documentation here.

Q10 was implemented during 2012 and apparently was in place before Nasuni ran its updated benchmarks between November 2012 and January 2013. With its fancy new network design in place, WAS really shined. While the results in 2011 were close, with Amazon S3 being the overall winner, in 2012 the results were a blowout, with Windows Azure Storage being declared the winner, sweeping all other contenders across the three categories.

“This year, our tests revealed that Microsoft Azure Blob Storage has taken a significant step ahead of last year’s leader, Amazon S3, to take the top spot. Across three primary tests (performance, scalability and stability), Microsoft emerged as a top performer in every category.” -Nusani Report

The Nasuni report goes on to mention that “the technology [Microsoft] are providing to the market is second to none.”


One aspect of the report I found very interesting was in the error rates. For several of the vendors (including Amazon, Google, and Azure), Nasuni reported not a single error was detected during 100 million write attempts. And Microsoft stood alone for the read tests: “During read attempts, only Microsoft resulted in no errors.” In my book, I write about the Busy Signal Pattern which is needed whenever transient failures result during attempts to access a cloud service. The scenario described in the book showed the number of retries needed when I uploaded about four million files. Of course, the Busy Signal Pattern will still be needed for storage access and other services – not all transient failures can be eliminated from multitenant cloud services running on commodity hardware served over the public internet – and while this is not a guarantee there won’t be any, it does bode well for improvements in throughput and user experience.

And while it’s always been the case you can trust WAS for HA, these days it is very hard to find any reason – certainly not peformance or scalability – to not consider Windows Azure Storage. Further, WAS, S3, and Google Storage all have similar pricing (already low – and trending towards even lower prices) – and Azure, Google, and Amazon have the same SLAs for storage.


Note that the Nasuni report was published February 19, 2013 on the Nasuni blog and is available from their web site, though is gated, requiring that you fill out a contact form for access. The link is here:

Other related articles of interest:

  1. Windows Azure beats the competition in cloud speed test – Oct 7, 2011 –
  2. Amazon bests Microsoft, all other contenders in cloud storage test – Dec 12, 2011 –
  3. Only Six Cloud Storage Providers Pass Nasuni Stress Tests for Performance, Stability, Availability and Scalability – Dec 11, 2011 –
  4. Dec 3, 2012 – – Cloud computing showdown: Amazon vs. Rackspace (OpenStack) vs. Microsoft vs. Google
  5. – Feb 19, 2013 – Microsoft Azure overtakes Amazon’s cloud in performance test

Talk: Architecting for the Cloud at Boston Code Camp #19

On Saturday March 9, 2013, I teamed up with Joan Wortman on a talk at the 19th (!) Boston Code Camp. Some of the patterns I discuss require some different thinking about application architecture, including aspects that impact the user experience (UX). I teamed up with Joan Wortman (who is a UX expert) to better include some context around how to deal with some of these UX challenges as they intersect with architecture.

I also hope to see many of the attendees at future Boston Azure meetings (held at same location as the Boston Code Camp – NERD in Cambridge, MA). Also feel free to post follow-up questions to this post or email me (codingoutloud on gmail) or ask me on twitter where I am @codingoutloud.

Here are a couple of questions that came up in the talk:

  1. How much does the cloud cost? As I mentioned, this is a question that deserves some discussion since it is not as simple as looking at the pricing calculator (which can be found here). Sometimes it will be less costly, sometimes more costly. (I did point out there is a free tier for Windows Azure Web Sites.) One major factor is the cost of resources (which is trending down over time). Another major factor is the impact of reducing resource usage when it is not needed; for example, consider a Line of Business application which is used only during business hours in North America and can be turned off completely (accruing no VM usage charges) during non-business hours/weekends/holidays; as another example consider that you don’t need to own resource for the “spike” at the Superbowl (like Shazam scenario described by Joan) since you can “give it all back” (stop paying) once the rush is over. There are also other considerations when you get into DR and HA and geo-distribution. (I wrote about RPO and RTO terms in the context Engineering for DR in the Cloud recently.) And still another factor is understanding what you are paying for — don’t forget the Iceberg idea — so do not compare pricing with those of traditional hosting (unless that’s what you really want) since hosting is not cloud computing!
  2. Why can I only access 32 messages at a time from the Windows Azure Storage Queue? This is the same limit when we talk about “peeking” (looking at what’s on the queue without removing it) and retrieving messages for exclusive access. I don’t know why this particular limit was chosen (why not 20? why not 100?) so could only speculate on that. The bottom line is that all messages can be accessed – sometimes requiring more than one call. I wish I had time to probe into the application scenario that would benefit from grabbing so many messages at once, but due to time constraints did not do that. I will answer the question further if I get a follow-up question.
  3. Where can I find the mail app that Joan mentioned? The Mailbox app is for iOS and can be found in your app store or directly on iTunes here: (and there’s a lot of press – such as this story here).
  4. OTHER QUESTIONS? Send ’em along!

Hope to see you at Boston Azure:


Much of the material for the talk also appears in my book:

Cloud Architecture Patterns book