Windows Azure SQL Database Marketplace
Editors note: this post was written by Michael Thomassy, Principal Program Manager, Windows Azure Customer Advisory Team
Following the blog on Designing Great Cloud Applications, the Azure CAT team is planning to give more detail and technical explanation to the components found in the code project Cloud Service Fundamentals in Windows Azure posted on MSDN Code Gallery. This starts the series of blogs and tech articles to describe the use of these fundamental build blocks which we’ll refer to as components. Over the course of the next several months, we will be publishing a series of blogs every other Thursday with detailed technical notes that walk through the individual components of Cloud Service Fundamentals.
Over the years we’ve worked with Windows Azure customers, within and outside of Microsoft, with many deep discussions about what is needed in their Windows Azure services. We’ve seen firsthand how answering some basic questions about implementing cloud services can grow quickly in complexity. For example, rather than giving just a piece of sharding code, we need a data access layer. Followed by resiliency of the data access layer that require developing retry logic as well as solid guidance for logging errors at scale. Not to mention building an ops store you can query for reports and generate alerts. You can see how the discussion progresses with each component as they depend and build on one another. These discussions and implementations resulted in the code project Cloud Service Fundamentals in Windows Azure that ties together a number of basic components into a working cloud application.
This code project was a challenge for the CAT team as we were focused on enabling complex, database backed services on Windows Azure for some of our largest customers. It’s based on work that we did with actual Windows Azure customers to solve specific problems. These problems often required best practices beyond the basic samples when we combined many of the requirements of large scale cloud services including elastic scale, partitionable workloads, availability, business continuity, large number of distributed users, and high volume, low latency requests. You can see the architecture for the Cloud Service Fundamentals code project below.
Our technical series will detail the components in the code project, including:
We’ll post technical blogs and publish the details on the TechNet Wiki. Looking forward to your comments and contributions.