Building Microservices on .Net 7 platforms which used Asp.Net Web API, SqlServer, gRPC, Ocelot API Gateway, MongoDB, Redis, RabbitMQ, PostgreSQL, Docker

The objective of we will create architecture Microservices on .Net platforms that used Asp.Net Web API, Docker, RabbitMQ, gRPC, Ocelot API Gateway, MongoDB, Redis, PostgreSQL, SqlServer, Entity Framework Core, Dapper, CQRS, and Clean Architecture implementation.

Introduction

Microservices Architecture is an approach to building software systems that emphasizes the creation of small, independent services that work together to provide a complete application. This approach is often used in large, complex systems where the traditional monolithic architecture may become difficult to manage.

The Ideas of the final architecture of the system :

Microservice vs Monolithic

Microservices architecture and monolithic architecture are two approaches to building software systems. Here are some differences between them:

• Size and complexity: A monolithic application is a single, large codebase that handles all functions and services of an application. In contrast, a microservices architecture is composed of small, independent services that work together to provide a complete application. This makes microservices easier to develop and maintain over time as each service has a smaller codebase and a clear responsibility.
• Scalability: Monolithic applications can be difficult to scale as the entire application needs to be replicated and deployed to handle increased traffic. Microservices architecture allows for individual services to be scaled independently, making them more flexible and efficient.
• Technology stack: Monolithic applications typically use a single technology stack for the entire application, while microservices architecture allows for different services to use different technologies as needed.
• Maintenance and deployment: Monolithic applications can be difficult to maintain and deploy as changes to one part of the application can affect other parts of the application. In contrast, microservices architecture allows for independent deployment of each service, making it easier to make changes and update individual services without affecting the rest of the application.
• Resilience and fault tolerance: Microservices architecture is typically more resilient and fault-tolerant than monolithic applications. If one service fails, it doesn’t necessarily mean that the entire application will fail. In contrast, a failure in a monolithic application can bring down the entire application.

In summary, microservices architecture offers several benefits over monolithic architecture, including increased flexibility, scalability, maintainability, and resilience. However, it also comes with added complexity and requires careful planning and management.

To build microservices in .NET, you can follow these general steps:

• Define the services: Identify the services that your application requires and define their responsibilities and boundaries.
• Choose a framework: Choose a .NET framework that supports building microservices, such as ASP.NET Core.
• Design the APIs: Design the APIs for each service, which should be simple, consistent, and easy to use. Consider using RESTful APIs.
• Implement the services: Implement the services using the chosen framework and programming language.
• Use containers: Use containers, such as Docker, to package the services, which will simplify deployment and make it easier to manage the application.
• Use a service registry: Use a service registry, such as Consul or Eureka, to keep track of the location and status of each service.
• Use a load balancer: Use a load balancer, such as Nginx or HAProxy, to distribute the traffic across the services
• Use a message broker: Use a message broker, such as RabbitMQ or Apache Kafka, to facilitate communication between the services.
• Use a database per service: Use a separate database for each service, which will make it easier to scale and maintain the application.
• Monitor and log: Use tools, such as Prometheus and Grafana, to monitor the application’s performance and logs.
• These steps are general and can be adapted to your specific needs and requirements. Also, it’s important to keep in mind the principles of microservices architecture, such as loose coupling, bounded context, autonomy, and fault tolerance, among others.

ASP.NET Web API

ASP.NET Web API is a framework that is used to build RESTful web services using . NET. It is a part of the ASP.NET framework and can be used with ASP.NET Core or the traditional .NET Framework.

Web API allows developers to create HTTP services that can be consumed by a wide range of clients, such as web browsers, mobile devices, and desktop applications. It supports various HTTP methods, such as GET, POST, PUT, DELETE, and PATCH.

To create a Web API application, you can follow these general steps:

• Create a new ASP.NET Web API project using Visual Studio or a command-line interface.
• Define the model and data access layer of the application, which can be done using Entity Framework or any other data access framework.
• Create the controllers, which will define the actions and the corresponding HTTP methods that the API will support.
• Implement the actions, which will perform the desired operations on the model and return the results as JSON or XML.
• Test the API using a web browser or a tool such as Postman or Fiddler.
• Deploy the API to a web server or a cloud service, such as Azure or AWS.

Web API supports various features, such as authentication and authorization, content negotiation, caching, and exception handling. It also provides a rich set of tools for testing and debugging the API, such as Swagger and Web API Test Client.

Web API is a powerful framework that can be used to build scalable and reliable RESTful services, and it is widely used in various industries and applications, such as e-commerce, social media, and IoT.

Docker

Docker is an open-source containerization platform that allows developers to package their applications and their dependencies into portable containers. Containers are lightweight, standalone, and executable packages that contain everything that is required to run an application, including the code, the runtime, the libraries, and the system tools.

A container is an isolated environment that runs on top of the host operating system but has its own filesystem, network interfaces, and process space. This allows multiple containers to run on the same host, without interfering with each other or with the host system. Containers can be easily moved across different environments, such as development, testing, and production, and can be deployed on any infrastructure that supports Docker.

Containers are designed to be immutable, which means that they can be easily replaced or upgraded without affecting the underlying infrastructure. They are also highly scalable, as multiple instances of the same container can be created and managed using tools such as Docker Compose or Kubernetes.

Docker provides a simple and efficient way to create, share, and deploy containers, using a command-line interface or a graphical user interface. It also provides a registry, called Docker Hub, where developers can store and share their container images with others.

In summary, Docker is a powerful platform that enables developers to build, package, and deploy applications using containers, which provide a lightweight, secure, and portable way to run applications in any environment.

RabbitMQ

RabbitMQ is an open-source message broker that is used to facilitate communication between distributed systems. It is based on the Advanced Message Queuing Protocol (AMQP), which is a standardized protocol for message-oriented middleware.

RabbitMQ provides a flexible and reliable way to exchange messages between different applications and services, using a variety of messaging patterns, such as publish/subscribe, request/response, and work queues. It supports various message formats, such as JSON, XML, and binary data, and provides advanced features, such as message routing, priority queues, and dead-letter queues.

The core concepts of RabbitMQ are producers, consumers, exchanges, and queues. Producers are applications that send messages to RabbitMQ, while consumers are applications that receive messages from RabbitMQ. Exchanges are routing agents that receive messages from producers and route them to the appropriate queue or queues, based on their routing key and exchange type. Queues are storage units that hold messages until they are consumed by a consumer.

RabbitMQ provides a variety of client libraries for different programming languages, such as .NET, Java, Python, and Ruby, as well as a web-based management interface, called RabbitMQ Management Console, which allows developers to monitor and manage their RabbitMQ instances.

RabbitMQ is widely used in various industries and applications, such as finance, e-commerce, and IoT, and is known for its high performance, scalability, and reliability. It can be deployed on-premise or in the cloud and can be integrated with various other technologies, such as Kubernetes, Docker, and Apache Spark.

gRPC

gRPC is an open-source high-performance remote procedure call (RPC) framework that is used to build distributed systems. It was developed by Google and is based on the Protocol Buffers serialization format.

gRPC allows developers to define services and messages using a simple IDL (Interface Definition Language), and generates client and server code in multiple programming languages, such as C++, Java, Python, and Go. It supports various types of RPCs, such as unary, server streaming, client streaming, and bidirectional streaming, and provides advanced features, such as flow control, deadline propagation, and service discovery.

The core concept of gRPC is the service definition, which is defined in a proto file using the Protocol Buffers syntax. A service definition defines the methods that can be called remotely, along with their input and output messages. Once the service definition is defined, gRPC can generate client and server stubs, which can be used to invoke remote methods as if they were local method calls.

gRPC is known for its high performance and low latency, as it uses HTTP/2 as the underlying protocol, which allows for multiplexing, header compression, and stream prioritization. It also provides support for SSL/TLS encryption and authentication, which ensures that communication between the client and server is secure.

gRPC is widely used in various industries and applications, such as microservices, cloud-native applications, and IoT. It can be integrated with various other technologies, such as Kubernetes, Istio, and Envoy, and can be deployed on-premise or in the cloud.

Ocelot API Gateway

Ocelot API Gateway is an open-source API gateway that is used to manage and route HTTP requests between microservices or between clients and microservices. It is built using the .NET Core platform and is designed to work seamlessly with ASP.NET Core.

Ocelot allows developers to define routes and policies using a simple configuration file and provides advanced features such as load balancing, caching rate limiting, and authentication/authorization. It supports various types of upstream services, such as HTTP, HTTPS, and TCP, and can integrate with various authentication providers, such as OAuth 2.0 and JWT.

The core concept of Ocelot is the route definition, which is defined in a configuration file using the JSON or YAML syntax. A route definition defines the matching criteria, the upstream service, and the policies that should be applied to the incoming requests. Once the route definition is defined, Ocelot can route the incoming requests to the appropriate upstream service, based on the defined criteria.

Ocelot is known for its flexibility, extensibility, and ease of use. It can be integrated with various other technologies, such as Kubernetes, Docker, and Consul, and can be deployed on-premise or in the cloud. It also provides a rich set of APIs and hooks, which allow developers to customize and extend its behavior as needed.

MongoDB

MongoDB is an open-source NoSQL document-oriented database that is designed for scalability, performance, and ease of use. It is built using the BSON (Binary JSON) format and is known for its flexibility, high availability, and horizontal scalability.

MongoDB allows developers to store and retrieve data in a flexible, schema-free manner, using documents that are organized into collections. It supports various types of data, such as strings, numbers, arrays, and embedded documents, and provides advanced features such as indexing, replication, sharding, and geospatial queries.

The core concept of MongoDB is the document, which is similar to a row in a traditional relational database, but with more flexibility and nested data structures. A document can contain multiple fields, each with its own data type and value, and can be indexed for faster query performance.

MongoDB provides a rich set of APIs and drivers for various programming languages, such as .NET, Java, Python, and Node.js, as well as a web-based management interface, called MongoDB Compass, which allows developers to interact with their MongoDB instances visually.

MongoDB is widely used in various industries and applications, such as e-commerce, social media, and IoT, and is known for its high performance, scalability, and availability. It can be deployed on-premise or in the cloud and can be integrated with various other technologies, such as Kubernetes, Docker, and Apache Spark.

MongoDB is an open-source NoSQL document-oriented database that is designed for scalability, performance, and ease of use. It is built using the BSON (Binary JSON) format and is known for its flexibility, high availability, and horizontal scalability.

MongoDB allows developers to store and retrieve data in a flexible, schema-free manner, using documents that are organized into collections. It supports various types of data, such as strings, numbers, arrays, and embedded documents, and provides advanced features such as indexing, replication, sharding, and geospatial queries.

The core concept of MongoDB is the document, which is similar to a row in a traditional relational database, but with more flexibility and nested data structures. A document can contain multiple fields, each with its own data type and value, and can be indexed for faster query performance.

MongoDB provides a rich set of APIs and drivers for various programming languages, such as .NET, Java, Python, and Node.js, as well as a web-based management interface, called MongoDB Compass, which allows developers to interact with their MongoDB instances visually.

MongoDB is widely used in various industries and applications, such as e-commerce, social media, and IoT, and is known for its high performance, scalability, and availability. It can be deployed on-premise or in the cloud and can be integrated with various other technologies, such as Kubernetes, Docker, and Apache Spark.

Redis

Redis (Remote Dictionary Server) is an open-source, in-memory data structure store that is used as a database, cache, and message broker. It is designed for high performance, scalability, and flexibility, and is known for its fast read and write speeds and low latency.

Redis supports various data structures, such as strings, lists, sets, sorted sets, and hashes, and provides advanced features such as transactions, pub/sub messaging, Lua scripting, and cluster support. It can be used as a standalone database, or as a cache layer in front of a relational or NoSQL database, to improve application performance and reduce database load.

The core concept of Redis is the key-value store, which is similar to a dictionary or hash table, but with support for advanced data structures and operations. A key in Redis can be associated with multiple values and can be manipulated using various operations, such as set, get, delete, increment, and decrement.

Redis provides a rich set of APIs and drivers for various programming languages, such as .NET, Java, Python, and Node.js, as well as a web-based management interface, called RedisInsight, which allows developers to interact with their Redis instances visually.

Redis is widely used in various industries and applications, such as e-commerce, gaming, and real-time analytics, and is known for its high performance, scalability, and versatility. It can be deployed on-premise or in the cloud and can be integrated with various other technologies, such as Docker, Kubernetes, and Apache Kafka.

PostgreSQL

PostgreSQL (often referred to as Postgres) is an open-source object-relational database management system (ORDBMS) that is designed for scalability, reliability, and data integrity. It is built on a proven SQL database model and is known for its robustness, extensibility, and support for advanced features.

PostgreSQL supports various types of data, such as strings, numbers, arrays, and JSON, and provides advanced features such as transactions, concurrency control, triggers, views, and stored procedures. It also supports various indexing and search algorithms, such as B-tree, GiST, and GIN, for fast and efficient data retrieval.

The core concept of PostgreSQL is the table, which is organized into columns and rows and can be manipulated using SQL commands. A table can be associated with constraints, such as primary key, foreign key, and unique key constraints, to ensure data integrity and consistency.

PostgreSQL provides a rich set of APIs and drivers for various programming languages, such as .NET, Java, Python, and Node.js, as well as a web-based management interface, called pgAdmin, which allows developers to interact with their PostgreSQL instances visually.

PostgreSQL is widely used in various industries and applications, such as e-commerce, finance, and healthcare, and is known for its reliability, scalability, and extensibility. It can be deployed on-premise or in the cloud and can be integrated with various other technologies, such as Docker, Kubernetes, and Apache Spark.

SqlServer

SQL Server is a relational database management system (RDBMS) developed by Microsoft. It is designed to store and manage large volumes of data in a secure and scalable way and provides advanced features for data management, business intelligence, and application development.

SQL Server supports various types of data, such as strings, numbers, dates, and binary data, and provides advanced features such as transactions, concurrency control, triggers, views, and stored procedures. It also supports various indexing and search algorithms, such as B-tree and full-text search, for fast and efficient data retrieval.

The core concept of SQL Server is the table, which is organized into columns and rows and can be manipulated using SQL commands. A table can be associated with constraints, such as primary key, foreign key, and unique key constraints, to ensure data integrity and consistency.

SQL Server provides a rich set of APIs and drivers for various programming languages, such as .NET, Java, Python, and Node.js, as well as a web-based management interface, called SQL Server Management Studio, which allows developers to interact with their SQL Server instances visually.

SQL Server is widely used in various industries and applications, such as finance, healthcare, and manufacturing, and is known for its scalability, reliability, and integration with other Microsoft products, such as Azure and Power BI. It can be deployed on-premise or in the cloud and can be integrated with various other technologies, such as Docker, Kubernetes, and Apache Spark.

Entity Framework Core

Entity Framework Core (EF Core) is an open-source, lightweight, and cross-platform object-relational mapping (ORM) framework developed by Microsoft. It is designed to simplify the process of accessing and manipulating data from a database in .NET applications and provides a high-level, object-oriented programming interface to interact with the database.

EF Core supports various database management systems, such as SQL Server, PostgreSQL, MySQL, SQLite, and Oracle, and provides a flexible and extensible approach to mapping data between the database and the application. It also provides advanced features, such as query optimization, caching, and change tracking, for efficient data access and manipulation.

The core concept of EF Core is the entity, which is a representation of a database table in the application. An entity is associated with a set of properties, which map to columns in the table, and can be manipulated using CRUD (create, read, update, delete) operations through a context object, which represents a database session.

EF Core provides a rich set of APIs and features for querying, filtering, and projecting data, as well as for handling relationships between entities, such as one-to-one, one-to-many, and many-to-many relationships. It also supports various data access patterns, such as lazy loading, eager loading, and explicit loading, to optimize performance and reduce the complexity of data access.

EF Core can be integrated with various other .NET technologies, such as ASP.NET Core, Blazor, and Xamarin, and can be used in various types of applications, such as web, desktop, and mobile. It also provides a Code-First approach, which allows developers to define the database schema using C# or VB.NET code and generate the database schema automatically.

Clean Architecture implementation.

Clean Architecture is a software design pattern that emphasizes the separation of concerns and modularity, with a focus on creating maintainable, testable, and scalable applications. The core idea of Clean Architecture is to design software systems that are independent of any specific framework, database, or user interface and can be easily adapted to changing business requirements.

Clean Architecture consists of several layers, each with a specific responsibility and set of rules:

Domain layer: This layer contains the core business logic and entities of the application, and is independent of any specific infrastructure or technology. It defines the rules and behaviors of the application and encapsulates the business domain concepts and rules.

Application layer: This layer implements the use cases and business logic of the application, and orchestrates the interaction between the domain layer and the infrastructure layer. It defines the application-specific logic and rules and exposes the API that the clients use to interact with the system.

Infrastructure layer: This layer provides the implementation details and tools for the application to interact with the external world, such as databases, web services, or messaging systems. It includes data access, networking, configuration, and other infrastructure-related components.

To implement Clean Architecture, developers should follow some best practices and guidelines:

Separation of concerns: Each layer should have a clear and distinct responsibility, and should not depend on other layers.

Dependency inversion: The higher-level layers should depend on abstractions and interfaces defined in the lower-level layers, rather than concrete implementations.

Testability: The code should be designed in a way that makes it easy to write automated tests, such as unit tests or integration tests.

Flexibility: The architecture should be designed to accommodate changes and evolution in the business requirements, without affecting the core business logic.

Simplicity: The architecture should be simple and easy to understand, with a minimal amount of complexity and unnecessary abstractions.

Implementing Clean Architecture can be done using various programming languages and frameworks, but the core principles remain the same. Some popular frameworks that support Clean Architecture include ASP.NET Core, Spring Boot, and Laravel.

part 2

https://medium.com/@fasa.kemal/building-microservices-service-using-asp-net-core-7-0-mongodb-and-docker-container-2b6d9ab2af8d