Past review:
Chapter 1: [Cloud Native Concepts and Technologies]
Chapter 2: [Containerized Application Design and Development]
Chapter 3: [Container-based deployment, management and scaling]
Chapter 4: [4.1 Microservice Architecture Overview and Design Principles]
Chapter 4: [4.2 Definition and Division of Service Boundary]
Chapter 4: [4.3 Communication between services and API design]
4.4 Separation and service of database and data storage
4.4 Separation and service of database and data storage
Cloud native is an emerging software development and deployment model that supports automation, microservices, and containerized deployment of applications and services. In this model, the separation and service of database and data storage is a very important part.
First, let's take a look at the separation of database and data storage under cloud native. Traditional database systems are usually designed based on a centralized architecture, which means that the database server needs to handle all data access requests. This design works well in a single server environment, but has some problems in a distributed environment.
For example, when a database server fails, the entire application may need to be restarted, which affects application reliability and availability. In addition, centralized database architectures also limit the flexibility and scalability of applications because the database server must handle all requests, and when the load increases, the server may not be able to cope, resulting in performance degradation.
In order to solve these problems, the cloud native architecture adopts the separation strategy of database and data storage. In this model, the database is placed in a separate container and made available to users through an API. This design enables the application to process data access requests more flexibly, while improving the scalability and reliability of the application. In addition, database containers can be highly customized to meet the needs of the application, such as using a specific database management system or storage bucket.
Next, let's take a look at the service-oriented data storage under cloud native. Traditional data storage systems are usually centralized, which means that data storage services must be responsible for the entire system. This means that data storage services need to be highly scalable and reliable to ensure that the system can handle high loads and failures. However, this design also has some disadvantages. For example, when a data storage service fails, the entire system may stop functioning, affecting application reliability and availability.
In order to solve these problems, the cloud-native architecture adopts a data storage service strategy. In this model, data storage services are decomposed into multiple independent services, each of which can be deployed, configured, and managed independently.
These services are available to users through APIs and can be highly customized to meet the needs of the application. Additionally, these services are highly scalable to ensure the system can handle high loads and failures. This design enables the application to process data access requests more flexibly, and improves the scalability and reliability of the application.
Cloud native is an emerging software development and deployment model that emphasizes containerization, automation, and microservices architecture. In the cloud-native architecture, the separation and service of database and data storage is a very important aspect, which can greatly improve the scalability and reliability of applications.
First, let's look at how to use Java code to achieve the separation of database and data storage. Suppose we have a cloud-native service called "UserService" that needs to use a MySQL database to store user data. The traditional way of writing is to put the database and user services together, which will lead to complex code, difficult to maintain and expand.
In cloud native architecture, we can use containerization technology to separate database and user services. Specifically, we can create a containerized image called "mysql-container" that contains a MySQL database instance. We can then create a containerized image called "user-service" that contains a cloud-native user service. At runtime, we can associate the "mysql-container" and "user-service" images with each other so that when the "user-service" container runs, it connects to the MySQL database instance already initialized in the container.
The benefits of doing this are as follows:
- Code separation: Separating the database and user services makes the code simpler, easier to maintain and expand.
- Ease of Deployment: Deployment becomes easier and faster thanks to containerization technology.
- Scalability: Due to the separation of database and user services, we can more easily control capacity and load balancing.
- Reliability: Due to containerization technology, containers are isolated from each other, which improves the reliability and security of the system.
Next, let's take a look at how to use Java code to implement data storage as a service. Suppose we have a cloud-native data storage service called "UserRepository", which uses a MySQL database to store user data. In the traditional writing method, we need to manually manage details such as database connections, transactions, and connection pools, which will lead to complex code, difficult to maintain and expand.
In the cloud-native architecture, we can use service technology to service data storage. Specifically, we can create a service called "user-repo" that contains a cloud-native datastore instance. At runtime, we can correlate the "user-repo" service with the "user-service" image so that when the "user-service" container runs, it calls the "user-repo" service to fetch user data.
The benefits of doing this are as follows:
- Code service: Servicing data storage makes the code simpler, easier to maintain and expand.
- Ease of Deployment: Deployment becomes easier and faster due to service-based technology.
- Scalability: We can more easily control capacity and load balancing due to servitization.
- Reliability: Due to servitization, services are isolated from each other, which improves the reliability and security of the system.
In short, the separation and serviceization of database and data storage under cloud native is very important, which can greatly improve the scalability and reliability of applications. Using containerization technology, service-oriented and micro-service architecture can help us better realize cloud-native architecture.