Knowledge Factory

The image showcases an architectural pattern for Command Query Responsibility Segregation (CQRS) . It demonstrates the segregation of the write operations (commands) and read operations (queries) into separate services and components for enhanced scalability, maintainability, and performance in microservices. Here are the key components illustrated in the diagram: Microservices : Order Microservice : Handles commands and queries related to orders. Customer Microservice : Manages commands and queries related to customers. Command and Query Segregation : Each microservice has: A Command Endpoint for write operations (e.g., creating, updating data). A Query Endpoint for read operations. Separate Command Service and Query Service with their respective models ( Command Model and Query Model ). Event-Driven Architecture : Event Publishers and Event Consumers facilitate communication between services using an Event Store . Events are relayed through a Messaging System for asynchrono...

Here’s a step-by-step explanation of the sequence diagram for message flow: 1. User Sends a Request The user initiates the process by sending a POST request to the Ktor server at the endpoint /kafka/send . This request contains the message payload that the user wants to send. 2. Ktor Server Processes the Request Upon receiving the request, the Ktor server calls the method sendMessage("my-topic", message) . The method is responsible for sending the user's message to the specified Kafka topic ( my-topic ). 3. Kafka Producer Sends the Message The Kafka Producer, configured within the Ktor server, takes the message and sends it to the Kafka Broker. The Kafka Producer ensures that the message is sent to the topic "my-topic" on the Kafka cluster. 4. Kafka Broker Receives the Message The Kafka Broker receives the message from the Kafka Producer. The Kafka Broker stores the message in the appropriate partition of the topic "my-topic" , making it available fo...

Sending bulk emails on a scheduled time can be a crucial feature for many applications. Using Azure Functions along with SendGrid can help you automate this process with ease. In this guide, we will walk you through the steps to send bulk emails asynchronously at a scheduled time using Java , Azure , and SendGrid . Prerequisites Before we dive into the implementation, ensure you have the following prerequisites: Azure Account : Sign up for an Azure account if you don’t have one already. SendGrid Account : Create an account and obtain your SendGrid API Key . Java Development Environment : Make sure you have an IDE such as IntelliJ IDEA or Eclipse set up with a Maven/Gradle project. Azure Functions Core Tools : If you’re developing locally, you need to install the Azure Functions Core Tools. Step 1: Install Required Dependencies Set up Maven Dependencies : Add the following dependencies to your pom.xml file to integrate Azure Functions and SendGrid into your Java project. < depen...

Here's an example of how to use Amazon Simple Email Service (SES) with a Spring Boot application for sending transactional emails. Here’s a step-by-step explanation of the workflow depicted in our diagram: User Sends HTTP Request The user makes an HTTP POST request to the Spring Boot application at the endpoint /api/emails/send with the required parameters ( from , to , subject , body ). REST Controller Triggers Email Sending The EmailController in the Spring Boot application receives the request and triggers the sendEmail() method. EmailController Calls EmailService The EmailController delegates the task of sending the email to the EmailService by invoking its sendEmail(from, to, subject, body) method. EmailService Sends Request to Amazon SES The EmailService creates a SendEmailRequest containing the email details ( From , To , Subject , Body ) and sends it to Amazon Simple Email Service (SES) for processing. Amazon SES Processes Email Amazon SES processes the email reque...

Here's an end-to-end example that demonstrates how to simulate an IoT device sending telemetry data to Azure IoT Hub, receive a Cloud-to-Device (C2D) message from the IoT Hub back to the device, and use an Azure Function to process and handle the data in Python. The diagram represents a sequence of interactions between an IoT Device(Simulated), Azure IoT Hub, and an Azure Function. Here's a breakdown: IoT Device(Simulated) to Azure IoT Hub: The IoT Device sends telemetry data (in JSON format) to the Azure IoT Hub. Azure IoT Hub to Azure Function: The Azure IoT Hub triggers an Azure Function to process the incoming telemetry data. Azure Function Processing: The Azure Function processes the telemetry data. Azure Function to IoT Device: After processing, the Azure Function sends an acknowledgment or result (in JSON format) back to the IoT Hub, which forwards it as a cloud-to-device message to the IoT Device. Prerequisites: An Azure subscription. An IoT Hub created in Azure. The Az...

Here’s an example of how to send an SMS using the Vonage (formerly Nexmo) SMS API in a Spring Boot application: 1. Create a Vonage Account Before integrating Vonage into your Spring Boot application, you need to create an account and get your API credentials. Sign up for a Vonage account at https://dashboard.nexmo.com/ . After signing up, obtain your API key and API secret from the Vonage dashboard. 2. Add Dependencies To use the Vonage SDK in your Spring Boot project, include the following dependency in your pom.xml file.  <dependency> <groupId> com.vonage </groupId> <artifactId> server-sdk </artifactId> <version> 8.15.1 </version> </dependency> Note : If you’re using the client artifact (previously com.vonage.client ), replace the artifact with the updated server-sdk version as per the migration. 3. Vonage API Configuration Next, create a configuration class to set up the Vonage client with your API credential...