What is AWS
AWS is a cloud computing service provided by Amazon.
With AWS, you can use everything from basic services such as servers, storage, databases, and software to services such as data analysis, machine learning, and IoT through the Internet.
AWS provides services that demonstrate high performance at low cost, and will be useful for application development.
What is cache in AWS
Cache in AWS is storage for temporarily storing data in order to process data at high speed.
Cache is a high-speed storage that temporarily stores data, and can reduce the time to refer to data when a request for the same data occurs.
The caching feature allows for efficient reuse of learned and calculated data.
How caching works
By reducing the chances of accessing the low-speed storage that is the data storage source, the cache improves data retrieval performance and achieves high-speed processing.
Data in the cache is stored in fast-access hardware, such as RAM, and used when the same data is requested.
Database data is stored in long-term storage, while caches temporarily store a subset of data.
5 AWS services
AWS has various services that are convenient for application development and system development.
Examples include Amazon ElastiCache, Amazon RDS, Amazon Neptune, Amazon Redshift, and Amazon DynamoDB.
Here, we will introduce five services provided by AWS.
AWS Service 1: Amazon ElastiCache
The first AWS service is Amazon ElastiCache.
Amazon ElastiCache is an AWS in-memory cache service that functions as an in-memory data store and in-memory cache, enabling high-speed data processing.
Processing data at high speed will help you build applications that use large amounts of data and improve the performance of your applications.
AWS Service 2: Amazon RDS
The second AWS service is Amazon RDS.
Amazon RDS is a relational database service that makes it easy to build, manage, and operate relational databases on the cloud.
With Amazon RDS, databases can be used from six engines such as MySQL and SQL Server, and existing databases can be easily migrated to Amazon RDS.
AWS Service 3: Amazon Neptune
The third AWS service is Amazon Neptune.
Amazon Neptune is a fully managed graph database that allows you to store large amounts of data while preserving relationships.
Because Amazon Neptune is fully managed, it helps you set up and back up your database, making it easy to use a database with fast performance.
AWS Service 4: Amazon Redshift
The fourth AWS service is Amazon Redshift.
Amazon Redshift is a service that builds a data warehouse in the cloud, a tool that allows you to query and analyze large amounts of data.
You will be able to query large amounts of structured and unstructured data at low cost and at high speed, and you will be able to analyze it in real time.
AWS Service 5: Amazon DynamoDB
The fifth AWS service is Amazon DynamoDB.
Amazon DynamoDB is a fully managed key-value document database that can process large amounts of data at high speed. It can support over 20 million requests per second and handle over 10 trillion requests per day.
It will be useful for application development that requires large-scale real-time response and web service development.
7 benefits of using AWS cache
AWS cache is a convenient tool when using AWS services, and there are various advantages of using AWS cache.
For example, cost savings, reduced need for over-provisioning, reduced database load, and improved application performance.
Here, we will introduce seven benefits of using AWS caching.
Advantage 1 of using AWS cache: Cost reduction
The first benefit of using AWS caching is cost savings.
If you want to build a database that can perform high-speed processing without using cache, you will need to add AWS resources, which will increase the cost.
AWS caching supports high request rates and IOPS, and enhances data retrieval performance, so you can reduce the cost of using the database.
Advantage 2 of Using AWS Cache: Reduce the Need for Overprovisioning
A second advantage of using AWS caching is that it reduces the need for over-provisioning.
Provisioning is to prepare in advance so that resources such as data can be provided in anticipation of user requests on the application.
AWS caching reduces over-provisioning by storing common keys rather than data in in-memory caches.
Advantage 3 of using AWS cache: Reduced database load
The third advantage of using AWS cache is that it reduces the load on the database.
Caching in AWS redirects some of the critical read load from the backend database to the in-memory layer to reduce the load on the database.
Offloading can also prevent slow performance and crashes during spikes.
Advantage 4 of using AWS cache: Increased application performance
The fourth advantage of using AWS caching is that it improves application performance.
The memory used for cache can exchange data faster than hard disks and SSDs, so data can be read from the in-memory cache at high speed.
Access to faster data also improves overall application performance.
Advantage 5 of using AWS cache: Increased IOPS
The fifth benefit of using AWS caching is increased IOPS.
IOPS is the number of input and output operations per second, and high IOPS means that even large amounts of data can be exchanged at high speed.
A single cache instance used as a distributed side cache can serve hundreds of thousands of requests per second and potentially replace database instances, thus reducing overall costs.
Advantage of using AWS cache 6: Predictable response to application usage
A sixth advantage of using AWS caching is the predictability of application usage.
Being able to handle spikes in your app’s usage is important, and when the database is under load, the latency to retrieve data increases and is generally unpredictable.
A high-throughput in-memory cache enables predictive response to spikes in application usage.
Advantage 7 of Using AWS Cache: Provides Fast and Predictable Performance
A seventh advantage of using AWS caching is that it provides fast and predictable performance.
You can store keys in an in-memory cache to reduce the need for over-provisioning while providing fast, predictable performance for frequently accessed data.
AWS cache will be useful for systems that require access to large-scale data, SNS operations, etc.
5 Use Cases for AWS Caching
AWS caching is a tool that allows you to use AWS services at high speed and at low cost, and there are various examples of using AWS caching.
For example, design patterns, applications, cache practices, RAM, in-memory engines, and more.
Here, we will introduce five examples of using AWS caching.
AWS Cache Use Case 1: Design Pattern
The first use case for AWS caching is a design pattern.
The cache in the distributed computing environment design pattern acts as a centralized layer accessed by various systems. Also, the local cache can only be used by local applications.
A distributed cache environment stores data in a central location for all consumers of the data to benefit from.
AWS Cache Usage Example 2: Applications
A second use case for AWS caching is in applications.
Caching can be used for web applications, databases, etc., and can reduce latency and improve IOPS for read-intensive application workloads such as SNS and games.
Data such as database query results, calculations with high computation load, and API requests and responses are temporarily stored in the cache.
AWS Cache Usage Example 3: Cache Practice
The third example of using AWS cache is a cache practice method.
When using a cache, it is important to know the validity of the data in the cache, and to prevent cache misses, such as when the retrieved data does not exist.
Apply expiration controls to the cache so that you can adjust the expiration of data as needed, and adjust the availability of the cache as needed.
AWS cache use case 4: RAM
A fourth use case for AWS caching is RAM.
RAM supports high request rates and IOPS, and caching improves data retrieval performance and reduces costs.
Data in the cache is stored and used in fast-access hardware such as RAM, and can be accessed faster than using traditional database or disk-based hardware.
AWS cache usage example 5: In-memory engine
A fifth use case for AWS caching is the in-memory engine.
An in-memory engine is used to build an in-memory database that loads data into main memory such as RAM instead of a hard disk or SSD.
The in-memory engine reduces access to traditional disk-based hardware and delivers low-latency performance.
Use AWS caching to improve performance!
So far, we have introduced the advantages and usage examples of using AWS caching.
Caching in AWS is a useful tool that allows you to make AWS services perform better at a lower cost.
If you are using AWS, please use the AWS cache to improve the performance of AWS services.