In this 4th article for the Amazon Aurora series , we will discuss and implement an Amazon Aurora Serverless cluster.
Introduction
Amazon Aurora offers a managed relational database environment compatible with MySQL and PostgreSQL databases. Traditionally, database administrators monitor and manage their database environment for infrastructure resources such as storage, CPU, and memory. Sometimes, due to unexpected application load, it might be challenging to scale the resources quickly. You cannot predict the actual requirements, but you can predict based an approximate amount of resources based on past database growths.
Imagine a database that does starts, stops, increases or decreases the compute resources as per your application load. Aurora manages the storage and computes capacity for you without your intervention. It increases or decreases the capacity as per your application requirements. It charges you only for the actively used instance capacity. Therefore, if your application has free space in storage volume and aurora shrinks the resources for you, it saves the cost for you.
In the previous article, we explored the provisioned Amazon Aurora clusters. AWS provides the Serverless configuration for automatic resource management.
- Note:_ The term Serverless might be confusing for you. It is a term used to highlight that you do not have to manage any backend resources such as a server, hardware, storage, and networking. There are still servers, but it is not visible or accessible directly to you._
Look at the below high-level diagram for Amazon Aurora Serverless architecture:
- It maintains a warm pool of aurora instances in the serverless configuration
- The monitoring service captures and monitors the compute resources ( CPU, Memory, Storage)
#aws #aws rds #mysql #serverless
