Getting Start With gRPC

I want to do a video of IT tutorial, can you arrange the text content of the video tutorial for me according to the content of the website. Let’s start with the gRPC tutorial, and you will give me a list of things to cover.

Of course! The following is a basic gRPC tutorial outline that you can modify and adjust to suit your needs.

1. Introducing gRPC
   • Background and overview of gRPC
   • Advantages and scenarios of gRPC
2. Write gRPC services
   • Write a gRPC definition file
   • Generate gRPC code
   • Implement gRPC server-side logic
3. gRPC communication protocol
   • The protocol and serialization mechanism for gRPC communication
   • The four modes of communication for gRPC
4. gRPC client
   • Write gRPC client code
   • How and considerations for calling gRPC services
5. gRPC security
   • The security mechanism of gRPC uses TLS/SSL for authentication
   • Authentication and authorization for gRPC
6. Practical application of gRPC
   • Implement distributed applications using gRPC
   • A microservices architecture implementation of gRPC

Hope this outline will help you in your video tutorial production.

Please explain in detail the background and overview of gRPC

gRPC is a high-performance, open source, general-purpose RPC (Remote Procedure Call) framework open source by Google, which can be used to build client-side and server-side applications in distributed systems. RPC is a communication protocol for remote procedure calls between clients and servers, and RPC allows applications to communicate with each other on different machines to achieve distributed computing.

Unlike traditional web services frameworks, gRPC is based on the Protobuf (Protocol Buffers) protocol for data transfer and serialization, rather than based on text protocols such as XML or JSON, which gives it significant advantages in terms of performance and efficiency. In addition, gRPC supports multiple programming languages (C++, Java, Python, Go, etc.) that can be used cross-platform, which makes it ideal for building cross-language and cross-platform applications.

gRPC was originally developed as Google’s internal system framework, its predecessor was Stubby, to support service communication within Google, and then after continuous improvement and optimization, it gradually became a general RPC framework, and was officially open sourced in 2015. At present, gRPC has become one of the important components of cloud native application development and microservice architecture, and is widely used in distributed systems and large-scale microservice architectures.

Please explain in detail the advantages and applicable scenarios of gRPC

gRPC has the following advantages:

1. Efficiency: gRPC uses Protocol Buffers to transfer data, which has a smaller size and faster serialization and deserialization than traditional text protocols such as JSON and XML. In addition, gRPC uses the HTTP/2 protocol for communication, which enables multiplexing and flow control, thereby improving network utilization and transmission efficiency.
2. Scalability: gRPC supports multiple streaming modes and multiple languages, which can adapt to different business needs and technology stacks. In addition, gRPC supports multiple communication modes such as server-side flow, client-side flow, and bidirectional flow, which can meet the requirements of different business scenarios.
3. Code automatic generation: gRPC uses ProtoBuf to define RPC interfaces, which can automatically generate client and server-side code, reducing the workload and error rate of manual code writing, and also improving the maintainability and readability of code.
4. Security: gRPC supports security mechanisms such as TLS/SSL encrypted transmission and authentication authorization, which ensures the confidentiality and integrity of data, and also ensures the security and reliability of the system.
5. Cloud native: gRPC is one of the important components of cloud native application development and microservice architecture, tightly integrated with container orchestration tools such as Kubernetes, supports multi-language and cross-platform development, and is easy to deploy and manage.

gRPC is applicable to the following scenarios:

1. High-performance and high-concurrency systems: gRPC uses binary protocol and HTTP/2 protocol for communication, which can achieve fast and efficient data transmission, suitable for high-performance and high-concurrency system development.
2. Large-scale distributed systems: gRPC supports multi-language and cross-platform development, which can meet the needs of large-scale distributed systems.
3. Microservice architecture: gRPC supports multiple communication modes to meet the communication needs between different services in the microservice architecture.
4. Cloud-native application development: gRPC is an important part of cloud-native application development, tightly integrated with container orchestration tools such as Kubernetes, and suitable for building cloud-native applications and microservice architectures.

Please explain in detail how to write a gRPC definition file

gRPC uses ProtoBuf (Protocol Buffers) as a standard format for defining RPC service interfaces and message types. ProtoBuf is a lightweight data exchange format that can describe data structures and relationships between data, supporting multiple programming languages and platforms while having higher performance and smaller size.

The basic steps for writing a gRPC definition file are as follows:

1. Define the message type: In the definition file, you define the message type first, specifying the type, name, and order of each field. For example, here is a ProtoBuf message type that defines student information:

goCopy codemessage Student {
    string name = 1;
    int32 age = 2;
    string gender = 3;
}

2. Define the service interface: Next, define the service interface, specifying the name of each method, the type of input parameters, and output parameters. For example, here is a gRPC service interface that defines querying student information:

javaCopy codeservice StudentService {
    rpc QueryStudentInfo(StudentRequest) returns (StudentResponse) {}
}

message StudentRequest {
    string name = 1;
}

message StudentResponse {
    Student student = 1;
}

3. Compile the ProtoBuf file: After writing the gRPC definition file, you need to generate the corresponding client and server code through the ProtoBuf compiler. You can use the following command line to generate code for the appropriate language:

cssCopy codeprotoc --proto_path=. --grpc_out=. --plugin=protoc-gen-grpc=/usr/local/bin/grpc_cpp_plugin student.proto

where –proto_path specifies the path to the proto file, –grpc_out specifies the directory where the gRPC code is generated, and –plugin specifies the plugin path where the gRPC code is generated.

4. Implement the service interface: According to the generated code, implement the corresponding service interface and method.

The above is the basic writing steps of the gRPC definition file, you need to pay attention to the following points:

• ProtoBuf message types and field numbers must be unique and cannot be duplicated.
• In the gRPC definition file, the service interface name and method name must be unique and cannot be duplicated.
• gRPC supports four data types: double, float, int32, and string.
• gRPC definition files can be nested, for example, one message type can contain another message type.

Writing gRPC definition files requires familiarity with the syntax and rules of ProtoBuf, definition and design according to actual business needs, and attention to the readability and maintainability of code.

Please explain in detail the generated gRPC code

Generating gRPC code is the process of converting gRPC definition files into client-side and server-side code in the corresponding language, which can be done using the ProtoBuf compiler.

Here are the basic steps to generate gRPC code using the ProtoBuf compiler:

1. Download and install the ProtoBuf compiler: You can download the ProtoBuf compiler from the official website https://github.com/protocolbuffers/protobuf/releases and install it according to the installation documentation.
2. Write a gRPC definition file: Define the service interface and message type in the definition file.
3. Generate code using the ProtoBuf compiler: Generate code by executing the following command:

phpCopy codeprotoc --proto_path=<proto文件目录> --grpc_out=<输出目录> --plugin=protoc-gen-grpc=<插件路径> <proto文件>

where –proto_path specifies the directory where the ProtoBuf file is located, –grpc_out specifies the directory where the code is generated, –plugin=protoc-gen-grpc specifies the plugin that generates the gRPC code, and < proto file > specifies the ProtoBuf file to generate the code.

For example, if you want to use gRPC in C++, you can execute the following command:

cssCopy codeprotoc --proto_path=./ --cpp_out=./generated --grpc_out=./generated --plugin=protoc-gen-grpc=/usr/local/bin/grpc_cpp_plugin student.proto

This command compiles the student.proto file into C++ client-side and server-side code, and stores the generated code in the ./generated directory.

4. Implement the server and client code: According to the generated code, implement the logic of the server side and the client.

It should be noted that the generated code is automatically generated according to the gRPC definition file, and usually only contains the definition of interfaces and data types, which need to be supplemented and modified according to the actual situation. In addition, the generated code usually needs to be used with the corresponding language’s gRPC library, for example, in C++, the gRPC C++ library needs to be used to implement the gRPC server and client.

In general, using the ProtoBuf compiler to generate gRPC code is one of the necessary steps to implement gRPC servers and clients, which can greatly simplify the code writing process and improve development efficiency.

How to generate python code for gRPC

To generate Python code for gRPC, you can use the ProtoBuf compiler and the Python gRPC plugin.

Here are the basic steps to generate gRPC Python code using the ProtoBuf compiler:

1. Install the Python gRPC plugin: You can use the pip tool to install the Python gRPC plugin, which can be installed using the following command:

Copy codepip install grpcio-tools

2. 编写gRPC定义文件：在定义文件中定义服务接口和消息类型。
3. 使用ProtoBuf编译器生成代码：通过执行以下命令生成Python代码：

phpCopy codepython -m grpc_tools.protoc --proto_path=<proto文件目录> --python_out=<输出目录> --grpc_python_out=<输出目录> <proto文件>

其中，–proto_path指定ProtoBuf文件所在目录，–python_out指定生成Python代码的目录，–grpc_python_out指定生成gRPC Python代码的目录，<proto文件>指定要生成代码的ProtoBuf文件。

例如，如果要将student.proto文件编译为Python代码，可以执行以下命令：

cssCopy codepython -m grpc_tools.protoc --proto_path=./ --python_out=./generated --grpc_python_out=./generated student.proto

这个命令会将student.proto文件编译成Python语言的客户端和服务端代码，并且将生成的代码存放在./generated目录中。

4. 实现服务端和客户端代码：根据生成的代码，实现服务端和客户端的逻辑。

需要注意的是，生成的代码通常需要与Python gRPC库一起使用，例如在Python中，需要使用grpcio库来实现gRPC服务端和客户端。

总的来说，使用ProtoBuf编译器和Python gRPC插件生成gRPC Python代码是实现gRPC服务端和客户端的必要步骤之一，可以大大简化代码编写过程，提高开发效率。

请详细解释如何基于python实现 gRPC 服务端逻辑

在Python中实现gRPC服务端逻辑需要遵循以下步骤：

1. 定义gRPC服务接口

首先需要在.proto文件中定义gRPC服务接口，其中包括服务方法的输入和输出类型。定义完.proto文件后，可以使用ProtoBuf编译器和Python gRPC插件生成对应的Python代码。

2. 实现服务类

根据生成的Python代码，可以实现服务类，并且在服务类中重写定义的gRPC服务接口方法。在方法实现中，需要处理请求，处理逻辑并且返回响应。

例如，假设在.proto文件中定义了如下的gRPC服务接口：

scssCopy codeservice MyService {
  rpc SayHello (HelloRequest) returns (HelloResponse) {}
}

则生成的Python代码中会包含一个名为MyServiceServicer的服务类，可以在这个类中实现SayHello方法的逻辑。

pythonCopy codeimport grpc
import myservice_pb2
import myservice_pb2_grpc

class MyServiceServicer(myservice_pb2_grpc.MyServiceServicer):
    def SayHello(self, request, context):
        name = request.name
        message = f"Hello, {name}!"
        return myservice_pb2.HelloResponse(message=message)

3. Start the gRPC service

Starting a gRPC service requires creating a gRPC server and registering the implemented service class with the server. You can create a gRPC server using the grpc.server() method, and register the service class with the server using the add_servicer_to_server() method. Finally, use the server.add_insecure_port() method to specify the port on which the server listens, and use the server.start() method to start the server.

pythonCopy codedef serve():
    server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
    myservice_pb2_grpc.add_MyServiceServicer_to_server(MyServiceServicer(), server)
    server.add_insecure_port('[::]:50051')
    server.start()
    server.wait_for_termination()

if __name__ == '__main__':
    serve()

In the above code, a thread pool is created using ThreadPoolExecutor (max_workers=10) that allows the gRPC server to process multiple client requests simultaneously.

Using the above steps, you can implement a gRPC server based on Python, process the client’s request, and return the response.

Please explain in detail the protocol and serialization mechanism for gRPC communication

The gRPC communication protocol and serialization mechanism are the core features of gRPC, and they are the basis for efficient and reliable communication in gRPC. gRPC uses HTTP/2 as the underlying transport protocol and supports multiple serialization mechanisms.

1. Communication protocol

gRPC uses HTTP/2 as the underlying transport protocol. HTTP/2 is a new network protocol, which is an upgraded version of HTTP/1.1, which supports multiplexing, binary frame transmission, server-side push and other functions. HTTP/2 can send multiple requests and responses at the same time on a single TCP connection, thus avoiding the “head of the queue” problem of HTTP/1.1 and improving network transmission efficiency. In addition, gRPC uses TLS/SSL to secure communications.

2. Serialization mechanism

gRPC supports multiple serialization mechanisms, including Protocol Buffers, JSON, and XML. Among them, Protocol Buffers is the default serialization mechanism of gRPC, and it is also the serialization mechanism officially recommended by gRPC.

Protocol Buffers is a lightweight and efficient data exchange format that uses IDL (Interface Description Language) to define data structures and service interfaces, and compiler generates code to serialize and deserialize. Protocol buffers have the following advantages:

• Efficiency: Protocol Buffers are binary encoded and are more compact and efficient than XML and JSON.
• Extensibility: Protocol Buffers supports backward and forward-compatible versioning and can be upgraded without breaking the original data format.
• Ease of use: Protocol Buffers generates code that is easy to use, supports multiple programming languages, and can be easily integrated with existing applications.

In gRPC, the client and server use Protocol Buffers to define and transmit data, define data structures and service interfaces in .proto files, and generate corresponding code through the compiler. The generated code contains data serialization and deserialization functions, which can be easily encoded and decoded.

Please explain in detail the four communication modes of gRPC

gRPC supports four different communication modes: Unary, Server Streaming, Client Streaming, and Bidirectional Streaming. Each mode has different characteristics and applicable scenarios, and can be selected according to specific needs.

1. Unary

Unary is the most basic communication mode of gRPC, which is a simple one-to-one request response pattern. The client sends a request to the server, the server processes the request and returns a response, and then the communication ends. This mode is suitable for scenarios where the amount of request and response data is small and the response time is short.

2. Server Streaming

Server Streaming is a server-side streaming pattern that allows a server to send multiple messages to a client. The client sends a request to the server, and the server can generate multiple messages according to the request parameters and send these messages to the client one by one until completion. This mode is suitable for scenarios where the server needs to transmit a large amount of data to the client, such as video streams and log data.

3. Client Streaming

Client Streaming is a client-side streaming pattern that allows a client to send multiple messages to a server. The client can transmit data by sending messages multiple times, and the server processes all the messages after receiving them and returns a response. This mode is suitable for scenarios where the client needs to pass a large amount of data to the server, such as uploading files and backing up data.

4. Bidirectional Streaming

Bidirectional Streaming is a bidirectional streaming mode that allows multiple simultaneous interactions between the client and the server. The client and server can send multiple messages separately, alternating until completion. This mode is suitable for scenarios that require two-way communication, such as real-time chat, multiplayer games, and so on.

In general, the four communication modes of gRPC provide flexible and efficient communication methods to meet the needs of different scenarios. Developers can choose the appropriate communication mode according to the specific application scenario.

Please explain in detail how to write gRPC client code based on python

To write gRPC client code in Python, you need to become gRPC client code, and then write client logic. The following describes each of these two steps:

1. Generate gRPC client code

The steps to generate gRPC client code are similar to generating server-side code, and need to be generated by protoc tools and Python plugins. The specific steps are as follows:

• Install Python modules for gRPC and protobuf:pip install grpcio protobuf
• Install the protobuf compiler protoc: download the corresponding binaries according to the operating system and CPU architecture, and then extract them into an executable path. The official download address is: https://github.com/protocolbuffers/protobuf/releases
• Install gRPC’s protoc plugin:pip install grpcio-tools
• Write a .proto file of the gRPC service, defining the service interface and message type
• Use the following command to generate the gRPC client code for Python:

cssCopy codepython -m grpc_tools.protoc -I /path/to/proto/files --python_out=. --grpc_python_out=. /path/to/proto/files/service.proto

Among them, /path/to/proto/files is the directory where the .proto file is located, –python_out=.specifies that the generated Python code is stored in the current directory, and –grpc_python_out=.specifies that the generated gRPC code is also stored in the current directory. service.proto is the file name of the .proto file.

2. Write gRPC client logic

After generating the gRPC client code, you can reference the file in the code and call the interface provided by the server through the stub class in it. Here’s a simple example:

pythonCopy codeimport grpc
import my_service_pb2
import my_service_pb2_grpc

# 连接gRPC服务器
channel = grpc.insecure_channel('localhost:50051')

# 创建stub
stub = my_service_pb2_grpc.MyServiceStub(channel)

# 调用服务接口
request = my_service_pb2.MyRequest(name='John')
response = stub.SayHello(request)

# 处理响应
print(response.message)

In the above code, first connect to the gRPC server via the grpc.insecure_channel() method. Then create a stub object and call the service interface through the stub object. Finally, the response result is processed.

It should be noted that in actual use, you may need to add functions such as timeout, authentication, and transmission encryption. These functions can be implemented through the relevant classes provided by grpc.

Explain in detail how to call gRPC services and considerations

There are two main ways to call gRPC services: synchronous and asynchronous. In a synchronous call, the client sends a request and waits for a response; In asynchronous calls, the client can continue to perform other operations after sending the request until it receives a response from the server and then processes the response result.

Here are some things to keep in mind when calling gRPC services:

1. Select the correct mode of communication

gRPC supports four communication modes: Unary, Server Streaming, Client Streaming, and Bidirectional Streaming. When selecting a communication mode, you need to select it based on the specific business scenario and performance requirements.

2. Set the timeout period

When calling the gRPC service, you need to set an appropriate timeout period to avoid waiting too long. It can be done through grpc. The WithTimeout() method sets the timeout period.

3. Handle errors and exceptions

When calling a gRPC service, various errors and exceptions may occur, such as network connection errors, timeouts, and error codes returned by the server. You need to handle these errors and exceptions in your code and handle them accordingly as appropriate.

4. Security considerations

In a production environment, the security of gRPC communication needs to be considered. TLS can be used to encrypt communications, and authentication mechanisms can be used to guarantee the security of communications.

5. Performance optimization

The performance of gRPC is very high, but some performance optimizations are still required in practical use, such as using streaming to reduce network overhead and using caching to improve access speed.

In summary, when calling a gRPC service, you need to select the communication mode, set the timeout period, handle errors and exceptions, consider security, and optimize performance according to specific business scenarios and requirements.

Please explain in detail the security mechanisms of gRPC and authentication using TLS/SSL

gRPC provides a variety of security mechanisms to secure communications, the most common of which is the use of TLS/SSL for authentication.

TLS/SSL is a commonly used secure transport protocol that encrypts data and guarantees the security of communication. When using TLS/SSL for authentication, two-way authentication between the server and the client is often required to ensure that the identity of both parties to the communication is legitimate.

Here’s the general flow for authentication using TLS/SSL:

1. Generate a certificate

When using TLS/SSL for authentication, you first need to generate a certificate. Certificates can be used to verify the identity of the server and client and to encrypt communication data.

2. Configure the server

The server needs to configure TLS/SSL so that the communication data can be encrypted with a certificate and the identity of the client can be verified. You can use tools such as OpenSSL to generate and configure certificates.

3. Configure the client

The client also needs to configure TLS/SSL to be able to encrypt communication data with certificates and verify the identity of the server. You can use tools such as OpenSSL to generate and configure certificates.

4. Authenticate

After a TLS/SSL connection is established, both the client and server need to authenticate. The client can verify the server’s certificate to ensure the legitimacy of the connection, and the server can also verify the client’s certificate to ensure the legitimacy of the connection.

5. Conduct encrypted communication

When authentication is completed, the client and server can start encrypted communication to ensure the security of communication data.

In gRPC, communication data can be encrypted using TLS/SSL and certificates can be used for authentication. TLS/SSL related parameters can be set in the configuration of the gRPC server and client to enable authentication using TLS/SSL.

In short, security is a very important aspect when using gRPC for communication, and security mechanisms such as TLS/SSL can be used to ensure the security of communication data and the legitimacy of identity.

Please explain gRPC authentication and authorization in detail

gRPC provides authentication and authorization mechanisms to ensure the security of communications and the confidentiality of data. Authentication and authorization are very important security mechanisms that can effectively protect data from unauthorized access and theft, while also restricting the use and transmission of data.

There are two main ways to authenticate and authorize gRPC:

1. Authentication token-based authentication and authorization

In this way, the user needs to provide a certain authentication token to access the resources on the server. The server can determine the user’s identity by validating the token and decide whether to allow the user to access resources. Typically, authentication tokens can include information such as usernames and passwords, and cryptography is required to guarantee their security.

2. Digital certificate-based authentication and authorization

In this way, users need to provide certain digital certificates to access the resources of the server. A digital certificate is an electronic certificate issued by a certificate authority that can be used to verify the identity of a user and the identity of the server. The server can verify the identity of the user by validating the digital certificate and decide whether to allow the user to access resources. Typically, digital certificates require the use of cryptography to ensure their security.

gRPC provides a variety of authentication and authorization mechanisms, which can be selected according to actual needs. For example, authentication frameworks such as OAuth 2.0 can be used for authentication and authorization, and digital certificate-based authentication mechanisms can be used to secure communications.

In gRPC, interceptor can be used to implement authentication and authorization mechanisms. Interceptor is an interceptor that intercepts and processes between a request and a response. Interceptor can be used to authenticate and authorize requests, ensuring the security of communication.

In short, gRPC authentication and authorization is a very important security mechanism, which can effectively protect the security of communication data and the legitimacy of identity. You can choose the appropriate authentication and authorization mechanism according to your actual needs, and use interceptor to achieve authentication and authorization.

Please explain in detail the use of gRPC to implement distributed applications

Implementing distributed applications using gRPC can distribute different parts of the application across different computer nodes, resulting in better scalability and reliability. gRPC provides an efficient RPC (Remote Procedure Invocation) mechanism that enables communication between different nodes and is able to support multiple programming languages such as Java, Python, etc.

Here are the general steps to implement a distributed application using gRPC:

1. Write gRPC server programs

First, you need to write a gRPC server program, which exposes one or more RPC methods through which the client can invoke the server’s functions. When writing a server-side program, you need to use the tools provided by gRPC to generate the corresponding code, including service interfaces, data structures, and message definitions.

2. Configure the gRPC server

The server needs to configure the listening port and address, and the security authentication and authorization mechanism of the service. For example, operations such as authentication, data encryption, can be used using TLS/SSL.

3. Write gRPC client programs

The client needs to write a corresponding program to call the RPC method provided by the server, which usually needs to generate the corresponding client code, including the service interface, data structure and message definition.

4. Configure the gRPC client

The client needs to configure the address and port of the server, and need to configure the corresponding security authentication and authorization mechanism, such as using TLS/SSL for authentication and data encryption.

5. Run gRPC server and client

Finally, the gRPC server and client program need to run on the corresponding computer node, and the client can call the RPC method provided by the server to implement various functions of the distributed application.

In short, using gRPC to implement distributed applications requires writing server-side programs, client programs, and configuring corresponding security authentication and authorization mechanisms. The use of gRPC can achieve efficient RPC communication, so that different parts of the distributed application can communicate with each other, improving the reliability and scalability of the application.

Please explain in detail how to implement a microservices architecture using gRPC

gRPC is a high-performance remote procedure call (RPC) framework for building microservices architectures. A microservices architecture decomposes an application into multiple services, each of which is independent and can be deployed, upgraded, and scaled independently. Implementing a microservices architecture using gRPC can make communication between services more efficient and reliable.

Here are the general steps to implement a microservices architecture using gRPC:

1. Define the gRPC service

First, you need to define the gRPC interface of each service, including the methods, request and response types provided by the service. These definitions can be defined using the IDL (Interface Definition Language) provided by gRPC, such as Protocol Buffers.

2. Implement gRPC services

Depending on the definition of the gRPC interface, specific functions of the service need to be implemented, which are usually composed of one or more microservices. When implementing a service, you need to use the tools provided by gRPC to generate the corresponding code, including service interfaces, data structures, and message definitions.

3. Configure the gRPC service

When you configure a gRPC service, you need to specify the listening port and address of the service, and configure the security authentication and authorization mechanism of the service. For example, operations such as authentication, data encryption, can be used using TLS/SSL.

4. Deploy the gRPC service

When deploying gRPC services, various deployment tools and container technologies such as Docker and Kubernetes can be used. These technologies can make services more reliable and efficient, and can be deployed and scaled automatically.

5. Call the gRPC service

When calling a gRPC service, you need to use the corresponding gRPC client program to call the methods provided by the service, and the client program usually needs to generate the corresponding client code, including service interfaces, data structures, and message definitions.

In summary, implementing a microservice architecture using gRPC requires defining a gRPC service interface, implementing service functions, configuring services and deploying services, and using corresponding gRPC clients to invoke services. The use of gRPC can achieve efficient RPC communication, which makes communication between microservices more efficient and reliable, improving the reliability and scalability of applications.

What are the great gRPC-based systems on github

Here are some great gRPC-based systems and projects:

1. Kubernetes: Kubernetes is an open-source container orchestration and management platform that uses gRPC to enable communication between all components.
2. etcd: etcd is a distributed key-value storage system for shared configuration and service discovery. It uses gRPC as a communication protocol between its clients and the cluster.
3. Istio: Istio is an open-source service mesh that uses the gRPC protocol to enable communication and traffic management between services.
4. CockroachDB: CockroachDB is a distributed SQL database that uses gRPC as its communication protocol for efficient distributed transaction processing.
5. Envoy: Envoy is an open-source, high-performance proxy and communications middleware that uses gRPC to enable communication between the proxy and the control plane.
6. Jaeger: Jaeger is an open source distributed tracing system that implements tracking data transmission and queries between services using the gRPC protocol.
7. Vitess: Vitess is an open source distributed database system that implements distributed queries and transactions using the gRPC protocol.

These systems and projects are implemented based on the gRPC protocol, taking advantage of gRPC’s high performance and reliability to provide efficient RPC communication, service discovery, and traffic management. They all have a wide range of application scenarios and have proven their reliability and scalability in practice.