Windows Azure Pattern Technology
The movie “A Brilliant Mind” featuring Russell Crowe was a story about Nobel Laureate John Nash. Nash’s gift was that he could recognize patterns in almost any type of repeated action or grouping. This talent presented the idea that there is a recognizable pattern in repeated actions. Storage technology offers the same type of pattern recognition through the repeated access of data. It is this applied model that can increase data reliability and accessibility. Here is how patterns impact data storage and usage and how Windows Azure Pattern Technology basically functions.
In order to ensure that critical data can be accessed quickly and reliably, a method for tracking a user’s habits in data usage needed to be developed. This data tracking is not new and its roots can be found in several modern technologies. The most obvious is file system data management. The technology of data distribution is used by operating systems within the confines of file system storage. A file system handler attempts to save data in a contiguous manner in a tight proximity. In other words, a file system tries to store the data in the same area on the hard drive in a linear fashion. This method allows for ease of access as well as an increase in access speed. Proximity and keeping the file contiguous is taken into consideration when saving a file to a drive. Anomalies like fragmentation are avoided, although sometimes cannot be helped.
The same is true for data centers and load balancing. Cloud servers offer a method for monitoring,not only which data is accessed, but also where the data is accessed from. In order to avoid network latency, a user’s pattern of access is tracked and data is made available at data centers that are geographically closer to the user. This offers a higher degree of internet reliability as well as an increase in response times.
Habits reflected in the amount of data used are also tracked and a pattern can emerge that will allow for faster access times as well as automatic load balancing. Peak access times are observed and accounted for and resources are then automatically allocated. It may be as simple as spawning more virtual machines to handle the load, or spreading the data across multiple data centers to account for heavy traffic. Whatever the reason for the extra load, Windows Azure offers an automatic method for upgrading the service as well as a configurable alternative that is used to fine tune the applications usage. Tracking and monitoring data use habits lead to more efficient storage and access actions. The emerging patterns from this tracking help make Windows Azure pattern technology a leader in the offering of cloud services.
