Knowledge Factory

Here's a brief explanation of the diagram's flow: Actors: User (U): Represents the end user interacting with the application. LoginComponent (LC): The component in the frontend (Vue.js) where the user enters login credentials. AuthService (AS): A service in the frontend responsible for handling authentication, such as calling the backend to log in and storing the JWT token and user roles in local storage. LocalStorage (LS): A storage mechanism for saving the JWT token and user roles in the frontend. AuthController (AC): The backend controller responsible for handling authentication requests (e.g., login). JwtTokenUtil (JTU): A utility in the backend that generates and validates JWT tokens. UserController (UC): A backend controller that handles user-related routes. SecurityConfig (SC): A backend configuration that defines security rules and role-based access control. Flow: User Login: The User enters their credentials into the LoginComponent (LC). The LoginComponent sends the cr...

Explanation of Flow: User Registration : The user submits the registration form in the Angular frontend, which sends the details to the AuthService . The AuthService then communicates with the Flask backend to register the user and receives a success response. User Login : The user submits the login form, and the Angular frontend calls the AuthService with the login credentials. The AuthService sends these credentials to the Flask backend, where they are verified against the UserModel . If successful, Flask generates a JWT token using JWTManager , sends it back to the AuthService , which stores the token in localStorage . Accessing Protected Route : The user tries to access a protected route. Angular checks if the user is authenticated by verifying the JWT token stored in localStorage . Angular sends the token in the request to Flask. Flask verifies the token using JWTManager and, if valid, returns the protected content to Angular, which then displays it to the user. This sequence ...

User interacts with the Spring Boot Application . The Spring Boot Application sends telemetry data (such as requests and exceptions) to Azure Application Insights . Azure Application Insights forwards telemetry data (logs, metrics) to Azure Log Analytics . Azure Log Analytics stores and analyzes the telemetry data, enabling querying and visualization. Azure Monitor provides additional insights, visualizations, and alerting for the metrics. User can visualize metrics and logs via Azure Monitor or Log Analytics. To monitor a Spring Boot 3.x application using Azure Application Insights and Log Analytics , you need to set up Application Insights using the Java Agent (since the applicationinsights-spring-boot-starter is not compatible with Spring Boot 3.x). Here’s an end-to-end guide for setting up Application Insights and Log Analytics for your Spring Boot 3.x application. Prerequisites: Azure Subscription with access to Azure Application Insights and Azure Log Analytics . A...

Description User : Triggers message sending by interacting with the Spring Boot application, e.g., via REST API. MessageSenderService : Business service responsible for sending messages. JmsTemplate : Facilitates communication with Azure Service Bus. Azure Service Bus Queue : Holds messages until processed. MessageReceiver : Processes messages received from the queue. Dead-letter queue : Handles messages that fail after retries. Azure Service Bus is a fully managed enterprise messaging service that enables communication between distributed systems. This guide will walk you through the process of integrating a Spring Boot application with Azure Service Bus for reliable messaging. 1. Prerequisites Before you begin, ensure you have the following: Azure Account : An active Azure subscription. If you don’t have one, create a free account at Azure Free Account . Azure Service Bus Namespace : Create a namespace in the Azure portal. Navigate to Service Bus in the Azure portal. Click + Create ...