Learn RPC Concepts and Patterns | Foundations of API Design

To understand RPC, begin by picturing a system where a client wants to execute a function that actually runs on a server, possibly on another machine or even in another data center. In the RPC communication model, the client does not need to know how the server implements the function; it only needs to know the function's name, the arguments it expects, and the result it returns. The client packages up its request, sends it to the server, and waits for a response. The server receives the request, unpacks it, executes the function, packages up the result, and sends it back. This model abstracts away the details of network communication, making remote calls appear almost like local function calls.

The core steps in an RPC interaction include:

The client serializes the function name and arguments into a message;
The message is transmitted over the network to the server;
The server deserializes the message, locates the function, and executes it with the provided arguments;
The server serializes the result and sends it back to the client;
The client receives and deserializes the response, obtaining the result as if the function had been called locally.

This approach allows systems to be modular, distributing functionality and scaling workloads across multiple machines. However, it also introduces challenges such as network latency, partial failures, and the need for careful error handling.


              123456789101112131415161718192021222324252627282930313233343536
            
# Simulating an RPC call in Python

import json

# Server-side function
def add(x, y):
    return x + y

# Client serializes the request
request = {
    "method": "add",
    "params": [5, 3]
}
serialized_request = json.dumps(request)

# Simulated network transmission...
# Server receives the request and deserializes it
received_request = json.loads(serialized_request)
method = received_request["method"]
params = received_request["params"]

# Server invokes the requested method
if method == "add":
    result = add(*params)
else:
    result = None

# Server serializes the response
response = {
    "result": result
}
serialized_response = json.dumps(response)

# Client receives the response and deserializes it
final_response = json.loads(serialized_response)
print("RPC result:", final_response["result"])  # Output: RPC result: 8

When designing RPC systems, you must decide whether remote calls should be synchronous or asynchronous. In a synchronous RPC, the client sends a request and waits for the server to respond before continuing. This is simple and intuitive but can cause the client to block if the server is slow or unresponsive, potentially leading to performance bottlenecks.

In contrast, asynchronous RPC allows the client to send a request and continue processing without waiting for the response. The response can be handled later, often through callbacks or event loops. This pattern is useful for improving throughput and responsiveness, especially in systems where network delays are unpredictable or where multiple requests can be made in parallel.

Choosing between synchronous and asynchronous RPC has important implications for system design:

Synchronous RPC is easier to reason about but can reduce scalability due to blocking;
Asynchronous RPC increases complexity but allows for greater concurrency and resilience to latency;
The right choice depends on your application's requirements, expected load, and tolerance for complexity.


              123456789101112131415161718192021222324252627
            
# Synchronous and asynchronous function calls in Python

import time
import threading

def slow_add(x, y):
    time.sleep(2)  # Simulate network delay
    return x + y

# Synchronous call (blocks until done)
result_sync = slow_add(2, 4)
print("Synchronous RPC result:", result_sync)

# Asynchronous call using threading
def async_add(x, y, callback):
    def run():
        result = slow_add(x, y)
        callback(result)
    thread = threading.Thread(target=run)
    thread.start()

def print_result(result):
    print("Asynchronous RPC result:", result)

async_add(10, 5, print_result)
print("Asynchronous call made; main thread continues...")
time.sleep(3)  # Wait for async call to complete

1. Which of the following are characteristics of RPC?

2. Which statement best describes the difference between synchronous and asynchronous RPC?

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 3

Ask AI

Ask anything or try one of the suggested questions to begin our chat

Suggested prompts:

What are the main differences between RPC and REST?

Can you explain more about how serialization works in RPC?

What are some real-world use cases for RPC?

Swipe to show menu