Neighborly Webapp Deployment and Microservice Automation
Containers, K8s
Project details
Project Description:
My task was to develop and deploy an application called "Neighborly". This web application, powered by Python Flask, aimed to connect neighbors by allowing them to post advertisements for services and products they can offer. The project encompassed creating both the client-side front-end application and the server-side back-end API endpoints. The deployment process was streamlined using Azure services, including Azure Function App, Cosmos DB, Azure Registry, Kubernetes, Event Hubs, and Logic App.
Problem Statement:
The goal was to create a user-friendly platform that enables neighbors to easily share information about their services and products with the local community. Additionally, the application deployment and automation process needed to be efficient, scalable, and reliable.
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.
Key Takeaways
In conclusion, the "Neighborly Web Application Deployment and Automation" project underscored my capability to develop,
deploy, and automate applications using a range of Azure services. By successfully executing each part of the project, I
demonstrated my proficiency in creating comprehensive, user-centered solutions while efficiently managing the deployment
and automation aspects of modern web applications.
Summary
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.
Services
Python Flask
Python Flask was the framework of choice for building the Neighborly web application. It allowed for the efficient development of both the client-side and server-side components. Flask's simplicity and versatility were instrumental in creating a user-friendly platform.
Azure Function App
I set up an Azure Function App with a Linux environment and Python runtime. This service provided a serverless compute platform for running code in response to various events, ensuring efficient handling of Neighborly's functionalities.
Cosmos DB
Azure Cosmos DB was used to manage data within the application. I established a Cosmos DB Account and created a MongoDB Database within Cosmos DB to store and retrieve information about services and products.
Azure Registry
Azure Registry played a crucial role in Dockerizing the Azure Functions. It served as a container registry for storing Docker images, ensuring easy deployment and scaling. served as the central CI/CD platform for automating various
stages of the deployment pipeline, including
building, testing, and deployment.
CircleCI's automation capabilities played a pivotal role in enhancing the project's
efficiency and reliability.
Kubernetes
Kubernetes served as the deployment orchestrator for the Neighborly application. I set up a Kubernetes cluster and deployed the application, ensuring scalability and reliability.
Event Hubs
Event Hubs was utilized to manage event streams within the application. It facilitated event-driven actions and notifications.
Logic App
I developed a Logic App that monitored HTTP triggers and sent email notifications when necessary. Logic App streamlined communication and automation within the project.
6+
Years Experience
126
Completed Projects
114
Happy Customers
20+