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https://github.com/alcestide/system-monitoring-k8s

Cloud-Native Monitoring Application using Python, Plotly, Flask, Docker, K8S and AWS.
https://github.com/alcestide/system-monitoring-k8s

aws cloud deployment devops docker flask iaas k8s kubernetes monitoring plotly python webapp

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Cloud-Native Monitoring Application using Python, Plotly, Flask, Docker, K8S and AWS.

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# Monitoring-K8S-DevOps

This project is a **Flask**-based web application that monitors **system usage** and displays it in a user-friendly interface using **Plotly**. The application can be built using **Docker** and deployed on **Kubernetes**, and it can be hosted on the cloud, specifically on **AWS** (Amazon Web Services).

# Introduction

Monitoring system usage is crucial for maintaining the performance and **stability** of applications running on a server. This project provides a Flask web application that collects **system metrics**, such as **CPU usage**, **memory usage**, and **disk usage**, and presents them in a visually appealing and intuitive dashboard. By leveraging Docker and Kubernetes, you can easily deploy and scale this application to meet your needs. Additionally, hosting the application on AWS allows for reliable and scalable infrastructure.

![2023-07-16_10-35_1](https://github.com/alcestide/monitoring-k8s-devops/assets/106203061/f80c3498-1f9e-4766-a8b5-80a67300d7c9)

# Features

- Flask: A lightweight and extensible web framework for building the application backend.
- Docker: Containerization technology that simplifies application deployment and eliminates environment inconsistencies.
- Kubernetes: An open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications.
- AWS: A cloud computing platform that provides a broad set of services for hosting and managing applications.
- System Monitoring: Collects and displays system metrics, including CPU usage, memory usage, and disk space.

# Prerequisites

Before you begin, ensure you have the following prerequisites:

- Docker installed on your local machine.
- A Kubernetes cluster set up or access to a managed Kubernetes service.
- An AWS account with the necessary credentials and permissions.