![]() ![]() Support only client requesting servers model.Resource / CRUD operations based and not API centric.While it is human readable and easy to understand, it is considerably heavy and slow due to JSON payloads and HTTP1.1 that has not evolved sincr 1997!.However, the limitations become pronounced when there is a requirement is for high-performance. REST APIs using JSON payloads have worked well in many situations and continue to do so. Handling error patterns in a consistent manner across Microservices. How to reduce Chatty I/O between Microservices?ĭ. How to reduce Network congestion and Latency in communication?Ĭ. How to standardize communication across Microservices developed by independent teams using different technology stack?ī. While finalizing the design for data exchange, there are a few key considerations we need to be aware of:Ī. Building robust communications between numerous Microservices, being the first. While the benefits are plenty, Microservices also come with a set of challenges. This style of architecture presents companies with a number of business benefits including independently deployable and scalable Microservices, democratization of technology, where each team owning the Microservice can develop services in a stack that is suitable, based on its characteristics, fault isolation, scalability, data isolation and so on. Each Microservice delivers a specific piece of business functionality as determined by the well accepted DDD (Domain Driven Design). Unlike legacy monoliths, Microservices, as their name suggests, comprises of small, loosely coupled and fully self-contained Microservices. Several have moved to the cloud, and have adopted Microservices architecture. Microservices and communication using REST/JSONĬompanies have begun to modernize their legacy systems. In this blog, I’d like to discuss traditional architectures using REST & JSON, their pros and cons, how a combination of gRPC, Protobuf and HTTP/2 helps us build performance efficient services, and how you can operationalize them like many prominent technology companies. GRPC over HTTP/2 using Protobuf has emerged as a high performance alternative that provides orders of magnitude improvement, and is fast becoming the go-to standard for most inter-service communications. It also lacks the inherent support for payloads like streaming data. It is therefore not performance-efficient. While REST / JSON-based communication have several benefits and is widely supported across languages and providers, it suffers from a heavy payload size because of JSON. ![]() Especially in Microservices architecture. So far, REST-based APIs have been the preferred go-to architecture for most inter-service communications, instead of HTTP1.1 using JSON payload.
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