gRPC is increasingly recognized for its high-performance capabilities in building scalable APIs that support efficient communication between services. Its use of HTTP/2 for transport and Protocol Buffers as its interface description language allows for robust, low-latency service interactions.
In this article we are going to describe a step-by-step guide to implement it in the context of an existing Spring Boot application.
In some of our projects which included embedded systems that produce events in real-time, we've decided to use gRPC due to its efficiency in terms of communication. In this case, we needed to add gRPC functionality to an existing Spring Boot application with a RESTful API in order to not disrupt the existing architecture while enhancing communication protocols. The steps that we needed to perform were the following.
Step 1: Setting Up gRPC in Spring Boot
First, we needed to add the necessary dependencies to your Spring Boot project. This involves including gRPC and Protocol Buffers in your pom.xml:
Step 2: Define Service and Messages using Protocol Buffers
As a second step, we need to create a .proto file where you define your service and the message structure - this file acts as a contract between your client and server. In our case, we use it to send the object detection results in images.
Step 3: Implement the Service in Spring Boot
For the client-side, we've decided to use StreamObserver, which is crucial for handling the stream of data in gRPC. This approach allows the server to process incoming messages as they arrive, providing immediate responses and enabling real-time communication. The non-blocking nature of StreamObserver ensures efficient communication and better resource utilization by allowing the server to handle multiple streams concurrently without being blocked by individual stream operations.
In the piece of code below, we implement the client in Java that will receive the TaskResults (object detection events) and will (1) register it
Testing the client side with Python
Now that we've built the server side that processes the event messages, on the other side (embedded system, already implemented in Python) we needed to implement the message sending. The approach was similar to what we did in Java.
Step 1: Install gRPC and gRPC Tools
First, we need to ensure that gRPC and the Protocol Buffers compiler are installed in your Python environment:
Step 2: Generate Python gRPC Code
Then, we needed to use the Protocol Buffers compiler to generate Python gRPC code from your .proto file. This is typically done via a script or manually in the command line:
Step 3: Implement the Client
Last step is to create a Python script to implement the client that sends streaming requests:
The client connects to a gRPC server and streams task results to it. Summarizing the code above, the ObjectDetectorClient class initializes with the server address and sets up a gRPC channel and stub. The send_task_result method streams task results (including image files) to the server. The method sends an initial task result message followed by chunks of the image file until the entire file is transmitted. This implementation demonstrates how a client can stream a request to a gRPC service.
Adding gRPC to an existing Spring Boot application facilitates the efficient transfer of real-time events, enhancing the application's responsiveness and performance. This guide provided a basic walkthrough of integrating gRPC with a focus on streaming data using StreamObserver with Java on the server-side and the same for Python on the client end. Future articles will delve into deployment considerations on AWS, ensuring a seamless transition and scalable deployment.
