A sample cloud-native e-commerce application built with 11 microservices to demonstrate Kubernetes, Istio, and gRPC best practices.
Online Boutique is a sample cloud-native microservices application that simulates an e-commerce platform. It demonstrates how to build, deploy, and manage a distributed system using modern technologies like Kubernetes, gRPC, and service meshes. The project solves the need for a realistic, hands-on example to learn microservices architecture and cloud-native development practices.
Cloud engineers, DevOps practitioners, and developers learning to design, deploy, and operate microservices-based applications on Kubernetes. It's also valuable for teams evaluating Google Cloud services or implementing service mesh technologies like Istio.
Developers choose Online Boutique because it provides a production-like, multi-language microservices application with complete deployment configurations. Its integration with real cloud services and support for various deployment scenarios make it an excellent educational tool and reference architecture.
Sample cloud-first application with 10 microservices showcasing Kubernetes, Istio, and gRPC.
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Includes 11 microservices written in Go, Node.js, Python, Java, and C#, providing a realistic example of multi-language architecture for hands-on learning.
Services interact via gRPC with protocol buffers, demonstrating efficient, type-safe RPC calls as shown in the protos directory.
Designed for any Kubernetes cluster with provided manifests, supporting deployments on GKE, Minikube, Kind, and via Terraform for easy setup.
Comes with a load generator service that simulates realistic user shopping flows, useful for performance and scalability testing.
Shows integration with Google Cloud services like Spanner and Memorystore, aiding in learning cloud-native patterns and best practices.
Missing essential production elements like user authentication, secure payment processing, and comprehensive error handling, as it's designed for educational purposes only.
Requires knowledge of Kubernetes, gRPC, and cloud tools, making deployment challenging for those new to these technologies, despite detailed instructions.
While cluster-agnostic, documentation and examples heavily favor Google Cloud services, potentially limiting portability and requiring adaptations for other clouds.