Performance of REST and gRPC in Microservices: Java Blocking vs. Python Non-Blocking I/O

The selection of communication protocols and underlying concurrency models profoundly impacts the performance and resource efficiency of microservice architectures. While existing studies frequently compare protocols like REST and gRPC, they often overlook the compounded effects of language-specific I/O paradigms during complex service chaining, as well as system behavior under edge-case failures. This study evaluates the performance disparities between Blocking I/O (Java Spring Boot) and Non-Blocking I/O (Python FastAPI) architectures utilizing REST and gRPC protocols. A containerized educational platform, simulating a three-tier service chain, was developed and subjected to rigorous load testing and fault injection scenarios. System performance was measured across varying payload sizes (1 KB, 50 KB, and 1 MB) to capture P99 latency, request throughput, CPU utilization, and memory footprint. The empirical findings indicate that while gRPC over HTTP/2 significantly enhances throughput, its efficiency is heavily modulated by the host language's thread management and serialization libraries. Furthermore, we identify the exact payload crossover threshold where multi-threaded blocking models outperform asynchronous event loops and analyze system resilience during simulated network partitions. The findings provide reproducible guidelines for software architects in selecting optimal protocol-language combinations, balancing raw performance with cognitive burden and fault tolerance.

Concurrency Model, gRPC, Microservices, REST, Service Chaining, Blocking I/O, Event Loop.

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