Introduction:
As it stands, the Redis server already has a lot of takers amongst the developer and startup community. It is due to its excellence in providing an in-memory, session storage, data caching system. Developed to improve the scalability of various industrial functions, the Redis server started doing much more and fulfilled millions of user requests practically without any latencies.
The Azure cache for the Redis server:
The Redis server had already been endowed with the Redis cache, one of the latest innovations in data caching technology. The Azure cache memory for the Redis server acts as an excellent in-memory data store based on the Redis server. The systems that rely profoundly on the backend data stores undergo a tremendous improvement and scalability in function when the Redis server is used in the form of cache memory.
The Redis cache’s performance involves copying the most frequently accessed user data to fast storage locations that lie close to the application. This performance can be enhanced to a great extent with the Azure cache for the Redis server as this fast storage location resides in-memory. You don’t have to deal with excess hassles while loading it from the disk with the use of the database.
Characteristic features of the Azure cache:
- The Azure cache for the Redis server acts as a distributed data caching system and session storage It also acts as an efficient message broker. Using the Azure cache for the Redis windows allows the Redis server to perform as a high-throughput, low-latency open-source software that takes care of millions of user requests and serves them in the order of microseconds. This advanced feature of the Redis server will improve application performance significantly.
- A highly secure and dedicated Redis cache can be accessed by employing the Azure cache for the Redis server. The Azure cache is managed by Microsoft and is hosted by the Azure platform. It is also accessible to any application within or outside the Azure platform.
The key takeaways from the Azure cache in the performance of common application architecture patterns:
Integrating the Azure cache with the Redis server has numerous benefits that can be realized by improving various applications’ performance. Specific application architecture patterns are supported by the Azure cache for the Redis server, like the ones enumerated below.
● User session caching:
It is an application architecture pattern that can be typically employed in conjunction with shopping carts and similar user history data that a web application associates with user cookies. The continuously increasing cookie storage has a negative implication on performance. The cookie size keeps on growing and is passed and validated each time with a user request, thus increasing downtime. A stereotypical solution will always use the cookie as a key and probe into the data stored in a database. The Azure cache for the Redis server acts like an in-memory database caching system. Therefore, it offers the least effort in associating the information with a user, compared to interaction with a relational database system.
● Content caching:
Templates that use static content like banners, headers, and footers generate numerous web pages. The static materials mustn’t undergo much change. An in-memory cache will allow you easier access to such static contents in contrast to backend datastores. This architecture pattern eases the server load and reduces processing time and therefore creates a more responsive set of actions from the web servers. Moreover, the cache memory of Azure will reduce the number of servers that you require to handle loads and delivers the Redis Output Cache Provider to support this architectural pattern using ASP.NET.
● Cache-aside:
Usually, databases are too large to be loaded directly into the cache memory. It is in this context that the cache-aside pattern finds its application by loading data into the cache memory as and when required. While making necessary modifications to the data, the system can also update the cache memory and then distribute it to other clients. Along with these operations, the system can employ additional functions. These include setting an expiration on the data and using an eviction policy, triggering data updates directly into the cache memory.
● Distributed transactions:
Applications would often execute themselves as a single atomic operation through a series of commands against a backend data store’s landscape. Either every command succeeds or gets rolled back into the initial state from which they had generated. The Azure cache for the Redis server supports batch command execution as a single transaction.
● Task and message queuing:
Applications would typically add tasks to a queue when the associated operations take time to implement. Operations with extended running time are queued and are often sequentially processed by a different server. Deferring work in this way is known as task queuing, and the Azure cache for the Redis server enables this architecture pattern in your application using a distributed queue.