My Contributions:The Neighborly project was divided into four distinct parts, each focusing on a specific aspect of development, deployment, and automation:
Creating an Azure Function App:I set up an Azure Function App with a Linux environment and Python runtime. Alongside that, I established a Cosmos DB Account and created a MongoDB Database within CosmosDB to manage data.
Deploying the Client-Side Flask Web Application:I deployed the client-side Flask web application, built in Python, ensuring it was accessible to users for viewing, creating, editing, and deleting community advertisements.
CI/CD Deployment:I created an Azure Registry and Dockerized the Azure Functions. I then established a Kubernetes cluster, deployed the application to Kubernetes, and verified the successful deployment.
Event Hubs and Logic App:I developed a Logic App that monitored an HTTP trigger. When the HTTP request was triggered, the Logic App sent email notifications. Additionally, I set up a namespace for Event Hub to manage event streams.
Outcome of the Project:
User-Friendly Platform:The Neighborly application provided an intuitive interface for neighbors to share services and products within their community.
Efficient Deployment:By leveraging Azure services such as Function App, Cosmos DB, Azure Registry, Kubernetes, and Logic App, the project demonstrated streamlined deployment and automation processes.
Scalability and Reliability:The utilization of Kubernetes and Azure services ensured that the application could scale according to demand and maintain a high level of reliability.
End-to-End Solution:From building the application to deployment and automation, the project showcased my ability to handle the entire software development lifecycle.
Problem-Solving:Each part of the project highlighted my problem-solving skills, from setting up Docker containers to creating Logic Apps for event-driven actions.
In the "Neighborly Web Application Deployment and Automation" project, I was tasked with developing and deploying the Neighborly web application. This application, built with Python Flask, aimed to connect neighbors by enabling them to post advertisements for their services and products. The project involved both the client-side front-end and the server-side back-end API development.