Orchestrating the gRPC based services

As a developer, you can invoke a gRPC service using a workflow application that runs with Quarkus. This document describes how to create a workflow that invokes a running gRPC service and how to configure properties to locate that running gRPC service.

For information about gRPC concepts, see gRPC.

In order to illustrate how gRPC integration works, this Serverless Workflow application is used. This example greets a user in their preferred language by invoking a gRPC service.

Relevant files of the workflow application include:

  • gRPC proto file: This file defines a greeter service, which consists of sayHello methods, each covering a different gRPC scenario:

    • The sayHello method accepts two parameters, including name of the user and an optional language to use in the greeting message (English by default). The sayHello method returns the greeting message in the appropriate language.

    • The SayHelloAllLanguages accepts just the name parameter and streams greetings in all languages supported by the service. This represents the server-side streaming scenario.

    • The SayHelloMultipleLanguagesAtOnce accepts a stream of name-language pairs as parameters and returns corresponding greetings as one block of text after the streaming is finished. This is the client-side streaming scenario.

    • The SayHelloMultipleLanguages accepts a stream of name-language pairs and streams back greetings with a respective name and in a respective language.

// The greeter service definition.
service Greeter {
  // Sends a greeting
  rpc SayHello (HelloRequest) returns (HelloReply) {}
  rpc SayHelloAllLanguages (HelloRequest) returns (stream HelloReply) {}
  rpc SayHelloMultipleLanguagesAtOnce (stream HelloRequest) returns (HelloReply) {}
  rpc SayHelloMultipleLanguages (stream HelloRequest) returns (stream HelloReply) {}
  ...
}

// The request message containing the user's name.
message HelloRequest {
  string name = 1;
  string language=2;
}

// The response message containing the greetings
message HelloReply {
  string message = 1;
}
"functions": [
    {
      "name": "sayHello",
      "type": "rpc",
      "operation": "greeting.proto#Greeter#SayHello"
    }
  ]

In this rpc function, the operation property is composed of three tokens separated by #. The three tokens include:

  • URI of the proto file (greeting.proto)

  • Name of the service (Greeter)

  • Name of the method (SayHello)

Kogito supports three URI schemes, including http, file, and classpath (default). Therefore, in the previous example, the greeting.proto is expected to be found in the project classpath.

The execution of the workflow consists of a single operation state, which is composed of one action.

 {
    "name": "sayHello",
    "functionRef" : {
        "refName": "sayHello",
        "arguments": {
            "name": ".name",
            "language": ".language"
        }
    }
}

In the previous example, the action invokes the sayHello RPC method using two model variables: name and language. These parameters are provided as part of the REST call that starts the workflow. The response of the method execution is mapped to a JSON object and merged with the workflow model.

For the remaining scenarios, see the following workflow definition files:

The only difference to the basic scenario is that workflows with client streaming expect an array of requests as arguments of the gRPC function:

 {
    "name": "SayHelloMultipleLanguagesAtOnce",
    "functionRef" : {
        "refName": "SayHelloMultipleLanguagesAtOnce",
        "arguments": ".helloRequests"
    }
}

The function expects an array of requests which is mapped under the helloRequests key in the workflow model.

In case of server streaming, the response is returned as an array as well and merged with the workflow model. In these examples, because no stateDataFilter is defined, the response is merged under the default response key in the workflow model.

  • Maven POM: The gRPC functionality is included within workflow dependencies, which means you do not need to add specific dependencies for gRPC to work with Serverless Workflow.

This pom.xml file contains the following resource node:

<resource>
 <directory>${project.basedir}/../serverless-workflow-greeting-server-rpc-quarkus/src/main/proto</directory>
 <includes>
   <include>greeting.proto</include>
  </includes>
</resource>

The reason for this snippet to exist is to guarantee that the proto file is included in the classpath. Remember that in the workflow file, the URI for the proto file does not contain any scheme, therefore the proto file is expected to be accessible in the classpath.

The previous, Maven based, approach can be used when the source code of the workflow and the gRPC server are stored in the same repository, but normally this will not be the case. If the proto file can be downloaded from a remote server, you might use the http scheme. If the proto file is not remotely accessible, you will need to manually obtain a copy of it and store in a directory that is included in the classpath (for example src/main/resources). Another possibility is to copy the proto file in a well known absolute path (that might be a shared network file system) and use the file scheme.

  • Application properties: In the application.properties file, you can add the information for the workflow application to locate the gRPC server.

Internally, the workflow implementation uses the same set of properties as Quarkus gRPC client. The client-name used by Kogito is the service name declared in the proto file.

Therefore, since in this example a service called Greeter is invoked, the following code is added to the properties.

quarkus.grpc.clients.Greeter.host=localhost
quarkus.grpc.clients.Greeter.port=50051

In the same GitHub repository as the example application, there is a Maven project which provides a simple implementation of the Greeter service. By default, this gRPC server runs on port 50051. Therefore, the same port is used in the application.properties file.

Running the workflow application

  1. Before running the workflow application, you need to start the gRPC server the workflow invokes. To run the gRPC server, navigate to the serverless-workflow-greeting-server-rpc-quarkus directory in a command terminal and enter the command:

    mvn compile exec:java -Dexec.mainClass="org.kie.kogito.examples.sw.greeting.GreeterService"

  2. Now you need to run the workflow application

    mvn clean quarkus:dev

  3. Once the workflow application is started, you can invoke the workflow instance using any http client, such as curl

Simple gRPC

Example request
curl -X POST -H 'Content-Type:application/json' -H 'Accept:application/json' -d '{"workflowdata" : {"name": "John", "language": "English"}}' http://localhost:8080/jsongreet
Example response
{"id":"4376cc50-42d4-45ef-8a5e-6e403a654a30","workflowdata":{"name":"John","language":"English","message":"Hello from gRPC service John"}}

You can also try greeting in a different language.

curl -X POST -H 'Content-Type:application/json' -H 'Accept:application/json' -d '{"workflowdata" : {"name": "Javi", "language": "Spanish"}}' http://localhost:8080/jsongreet

In response, you will see the greeting in Spanish language.

Server-side streaming gRPC

Example request
curl -X POST -H 'Content-Type:application/json' -H 'Accept:application/json' -d '{"workflowdata" : {"name": "John"}}' http://localhost:8080/jsongreetserverstream
Example response
{"id":"665911c5-36ee-40b7-93dd-a2328f969c73","workflowdata":{"name":"John","response":[{"message":"Hello from gRPC service John"},{"message":"Saludos desde gRPC service John"}]}}

Client-side streaming gRPC

Example request
curl -X POST -H 'Content-Type:application/json' -H 'Accept:application/json' -d '{"workflowdata" : {
                                                                                                    "helloRequests" : [
                                                                                                                        {"name" : "Javierito", "language":"Spanish"},
                                                                                                                        {"name" : "John", "language":"English"},
                                                                                                                        {"name" : "Jan", "language":"Czech"}
                                                                                                                      ]}}' http://localhost:8080/jsongreetclientstream
Example response
{"id":"abece3f9-0797-4c10-a1f5-8f3929724689","workflowdata":{"helloRequests":[{"name":"Javierito","language":"Spanish"},{"name":"John","language":"English"},{"name":"Jan","language":"Czech"}],"message":"Saludos desde gRPC service Javierito\nHello from gRPC service John\nHello from gRPC service Jan"}}

Bidirectional streaming gRPC

Example request
curl -X POST -H 'Content-Type:application/json' -H 'Accept:application/json' -d '{"workflowdata" : {
                                                                                                    "helloRequests" : [
                                                                                                                        {"name" : "Javierito", "language":"Spanish"},
                                                                                                                        {"name" : "John", "language":"English"},
                                                                                                                        {"name" : "Jan", "language":"Czech"}
                                                                                                                      ]}}' http://localhost:8080/jsongreetbidistream
Example response
{"id":"403876ed-0db4-40ca-a19c-158f563fef16","workflowdata":{"helloRequests":[{"name":"Javierito","language":"Spanish"},{"name":"John","language":"English"},{"name":"Jan","language":"Czech"}],"response":[{"message":"Saludos desde gRPC service Javierito"},{"message":"Hello from gRPC service John"},{"message":"Hello from gRPC service Jan"}]}}

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