GoogleCloudPlatform/microservices-demo

Features

• Kubernetes Cluster Orchestration - Uses Kubernetes manifests to define the automated deployment and scaling of microservices across a cluster.
• Demo Environments - Provides a functional online storefront as a reference demo for testing service mesh and observability in cloud environments.
• E-commerce and Shopping - Ships a functional web-based storefront for browsing product catalogs and managing shopping carts.
• Order Lifecycle Orchestration - Coordinates the end-to-end purchase process including cart retrieval, payment, shipping, and notifications.
• Payment Processing - Provides a system for validating credit card information and executing financial transactions.
• Product Catalogs - Provides a system for managing product metadata and serving available item lists.
• Shopping Carts - Manages the state and item logic for user shopping carts during a session.
• In-Memory Session Stores - Uses a high-performance in-memory store to manage user shopping cart state with low latency.
• Service Mesh - Integrates a service mesh to manage traffic routing, security, and observability between distributed microservices.
• Cloud-Native Microservices - Implements a reference architecture for containerized microservices deployed and orchestrated on Kubernetes.
• Cloud Native Infrastructure - Provides orchestration manifests and patterns for deploying scalable services in a cloud-native environment.
• Performance Testbeds - Serves as a distributed systems testbed to evaluate backend performance using simulated user traffic.
• E-commerce System Architectures - Implements a complete distributed architecture for an e-commerce system with integrated catalogs and payment workflows.
• Microservice Architectures - Showcases a reference architecture of loosely coupled, independently deployable microservices.
• Service Meshes - Implements a service mesh to manage traffic routing, security, and observability between microservices.
• Container-Based Isolation - Encapsulates each functional component in separate containers to ensure independent scaling and deployment.
• RESTful Services - Implements stateless RESTful communication to maintain loose coupling between diverse functional modules.
• AI Assistants - Provides a generative AI assistant that analyzes images to suggest relevant products for purchase.
• AI Model Inference - Implements asynchronous AI model inference to provide product recommendations via external API calls.
• Generative AI Integration Patterns - Demonstrates the integration of generative AI for image analysis and product recommendations within a microservices architecture.
• Recommendation Engines - Analyzes shopping cart contents to suggest related or complementary products.
• gRPC Service Implementations - Showcases a polyglot implementation of independent services communicating via high-performance gRPC calls.
• Polyglot Microservices - Demonstrates interoperability in a distributed system by implementing different services in various programming languages.
• Synthetic Traffic Generators - Includes a synthetic request generator to simulate user traffic and test system stability under load.
• Kubernetes and Orchestration - Provides a sample gRPC-based ecommerce microservices architecture.
• Microservice Reference Implementations - Polyglot cloud-native e-commerce demonstration application.

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