Name: Salman Malik
Type: User
Company: TecBrix Cloud
Bio: DevOps Engineer | CKA | Cloud Native | System Administrator | Docker & Kubernetes | AWS & Terraform Practitioner | Helm & Kustomize | Python | Ansible | GitOps
Location: Karachi, Pakistan
Blog: https://tecbrix.com/
Salman Malik's Projects
AWS Cloud Watch in combination with AWS Lambda to govern the resources and make sure it is in compliance with the organisational policies.
Basics of data visualisation, exploratory data analysis, ggplot2 and case study.
Running a web server Nginx inside a Docker container and hosting a basic website.
Using shell script and a few command-line arguments, you can obtain data from GitHub and perform various operations programmatically.
The Unified Machine Learning Framework
End-to-end CI/CD pipeline for a Java application using Jenkins, SonarQube, Argo CD, and Kubernetes. Automates the entire process from code checkout, build, test, code quality analysis, to deployment in different environments
Linear Regression Model on Airbnb prices of Seattle using Dash and Python
Welcome to the Linux basics course for beginners, covering all the important concepts and commands. This course is for those who wish to pursue a career in DevOps, SRE and System Administration.
MLOps End-to-End Example using Amazon SageMaker Pipeline, AWS CodePipeline and AWS CDK
This project demonstrates how to deploy MongoDB and Mongo-Express in a local Kubernetes cluster set up with Minikube. MongoDB is a popular, document-based NoSQL database, and Mongo-Express is a web-based MongoDB admin interface written with Node.js, Express.js. Both applications are containerised using Docker images and managed by Kubernetes.
This project automates the fetching of Shopify data, appending it to a Google Sheet, and sending notifications to a Slack channel.
The project includes setting up a VPC with private subnets, EC2 instances, RDS, and S3, along with Docker containers for application deployment. It also features a CI/CD pipeline with AWS CodeDeploy and CodePipeline. Live data visualisation using Metabase BI tool.
Python-based microservice application on AWS Elastic Kubernetes Service (EKS).
The project successfully developed a machine learning model using Streamlit for predicting Airbnb listing prices. The model demonstrated promising predictive capabilities and highlighted the significance of feature selection, model tuning, and interpretability techniques in improving performance and understanding model behavior.