Most cloud computing applications use caching to reduce latency, improve performance for heavy workloads, and improve performance. Caching is an essential component of any application and can be applied at various layers, such as the database, UI layer, session management, file system, or operating system.
Caching is important. It is important to determine if caching specific data will improve performance or reduce load. There are many issues related to JVM-in-memory cache when used in monolithic apps. A third-party caching service is required, as microservice applications are becoming more popular.
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Traditional In-memory Cache
Round trips to remote servers or databases are reduced by in-memory data cache. It speeds up application performance and improves response time. However, it has some drawbacks in microservices architectures. If multiple microservices in an organization share the same key/value information, the same data must be cached across all microservices.
The in-memory cache requires that the same code be repeated across all microservices to cache the data. To create, update, or delete data in the cache for an application that runs across multiple nodes, you will need to refresh or restart all nodes in order to reflect the changes.
If the application uses in-memory cache, and the data is large, it may slow down and possibly suffer from long garbage collection halts. In-memory cache code cannot be reused for other components because it is tightly coupled to application code. Rewriting code for components that share the same cached data can be difficult for developers.
New Technologies
The IT industry has seen a shift in application development from monolithic applications to microservices by forward-thinking organizations. A microservices architecture has one key characteristic: each service is independent and is separated from other services.
For building scalable microservices applications, you must have cache. Industry is moving to cloud-based microservices, which means that cloud-based services are needed that support distributed cache and are not dependent on application code. Amazon ElastiCache, a fully managed data store from Amazon Web Services, offers two Redis and Memcached data stores in-memory that can be used to cache.
The Caching Solution: Key Features
The following must be present in the caching solution:
Easy integration with your application code
Requires minimal APIs
Supports distributed cache in a clustered environment
Supports sharing objects across the JVM (in Java applications)
Is it scalable?
It is easy to maintain
Supports various data structures
If required, supports persisting data to disk
This reduces the burden on the back end
Allows for prediction of the application’s performance based on load
Database load and cost are reduced
Storage of key/value pairs is possible
In-memory cache stores data as key/value format. It supports any data structure, including strings, hashes and lists. A distributed cloud cache service replacement must also store data using key/value format. AWS ElastiCache is Redis meets all requirements to replace in memory cache. Memcached, which is intended for simpler applications only, does not.
Introduction to AWS ElastiCache Redis
Redis is an excellent choice to implement a distributed cache that stores flexible data structures in key/value format. It is usually an external service so multiple microservices applications and monolithic apps can share the same cluster or cache.
It is an external service so it allows scaling for higher loads without affecting or making changes in the application code. Redis cache is efficient for both read and write operations.
Most web applications today are built using restful web API over HTTP. This requires a low latency backend response. AWS ElastiCache Redis database caching allows for a dramatic increase in throughput and lower data retrieval latency.
The Web application UI layer can cache session data, which speeds up the exchange between the user (and the web application).
AWS ElastiCache is a developer-friendly service that supports almost all programming languages, including C, C# Java, Java, Go and Python.
Why use AWS Redis Cache
AWS ElastiCache Redis has many useful properties, such as the following:
Redis is a clustered caching system. It can be shared by multiple applications and multiple microservices to allow for easy access. This avoids duplication of the cache in each application.
If desired, it can save the data to the hard drive of the application.
Redis supports many
AWS ElastiCache Redis Application Cache
