Webapp: As a business leader, you should focus on your core value (your superpowers) and deliver the experience through simple and intuitive user journeys. This is the objective of the Webapp, which serves as the primary user interface for end-users, providing access to the application's core functionalities.
AI Chatbot & Features: An interactive component for users to communicate with the application using natural language, enhancing user engagement and support. Features can include automated responses, personalized assistance, and integration with other services.
Admin App: Your team should have tools and functionality to manage the back office administrative work, such as managing users, making changes on behalf of the user, providing reports to stakeholders, tracking product-led growth, and marketing spend attribution. This is the objective of the Admin app, which serves as an interface for administrators to manage and oversee the application's operations.
API Gateway: This helps scale your backend infrastructure with polyglot teams (node, Java) and provides the needed abstraction for the Webapp. One such technology is GraphQL, which offers a flexible and efficient approach to querying and manipulating data.
Web Sockets: Enables real-time, bidirectional communication between the client and server, facilitating live updates and interactions. This helps provide a real-time user experience like chatbots or live updates in your Webapp. Technologies such as WebSockets in Java (using libraries like Netty, Spring Boot Websocket) and Node.js (using libraries like Socket.IO) are commonly used.
Core Services: Essential services that power the application, such as user account management, access control, user onboarding, notification services, and logging.
Admin Services: Services dedicated to administrative tasks and management, user management, reporting, metrics, content management, etc. (this should be protected behind VPN and use rigid security like MFA with audit logs)
Functional Services: Modular services that handle specific functions within the application, promoting scalability and maintainability. Examples include payment systems, order management, messaging services, inventory management, and customer support.
Data: Represents the various data stores used by the application for storing and retrieving information. This can be self-managed or managed by vendors like Azure, Amazon, or GCP. Examples include PostgreSQL for relational databases, MongoDB for NoSQL databases, and DynamoDB for managed databases.
Vector DB: Specialized database for handling vectorized data, crucial for AI and machine learning tasks. Examples include Pinecone and Milvus, Redis Vector DB, which are designed to store and search through high-dimensional vectors efficiently.
Analytics: Tools and services for tracking and analyzing application usage and performance metrics.
Monitoring: Systems for observing and ensuring the application's health and performance.