In this project, we build a practical AI-powered DevOps Agent that monitors Kubernetes cluster, collects logs from pods, stores knowledge in a vector DB, and uses an AI Agent to diagnose the issues…

What is an AI Agent?

A basic Express.js server that responds with "Hello, World!" on port 3000

The shared library contains reusable Groovy code for the pipeline stages (build, test, deploy).

In this project, we give a practical, end-to-end MLOps project that detects data / concept drift, exports drift metrics to Prometheus, visualizes & alerts in Grafana, Alertmanager, and Slack.

In this video, we walk you through a detailed tutorial on setting up a Jenkins Master using Docker and integrating it with a Docker container that serves as a Jenkins Build Agent. If you're looking…

In this project, we present a complete and practical DevOps project that shows how to run self-hosted GitHub Actions runners as Kubernetes pods that spin up on demand, execute a CI job, then termin…

In this project, we will build a practical intelligent document processing system that automatically extracts data from forms, invoices, receipts, contracts, etc. We will utilize Python, Amazon Tex…

In this video, we look at the importance of analyzing and measuring Time and Space Complexity for ML and AI Engineering.

In this project, we will build a secure system that uses HashiCorp Vault to dynamically generate secrets (e.g., database credentials), runs services in Docker and applies Zero Trust principles. We …

In this hands-on MLOps project, we will walk you through how to detect data drift in a machine learning model using Alibi Detect and automatically retrain the model using Apache Airflow.

In this project, we illustrate how the Kolmogorov Smirnov (KS) statistical test works, and why it is commonly used in Machine Learning (ML), Deep Learning (DL) and Artificial Intelligence (AI).

In this hands-on DevOps tutorial, we’ll walk through building a full-fledged Jenkins CI/CD pipeline to deploy a Java application to Microsoft Azure Container Instance using industry-standard tools …

In this project, we build, deploy, and manage a Kubernetes cluster using RKE2 (Rancher Kubernetes Engine v2) using Cloud VMs (on Google Cloud Platform), enhance it with Rancher UI for web-based clu…

In this project, we deploy Machine Learning Models A (Logistic Regression) and B (Random Forest) to a simple Flask-based API behind an Nginx Reverse Proxy that routes traffic 50/50 to each model, s…

In this demo, we build an End-to-End Retrieval-Augmented Generation (RAG) AI System using LangChain for RAG framework, FAISS for vector store, Hugging Face model as LLM and Gradio for frontend UI.

In this tutorial, we'll show you how to monitor your Application Metrics on Kubernetes cluster effectively using Prometheus and Grafana.

In this video, we’ll walk you through building a powerful machine learning model using Kubeflow and deploying it seamlessly to KServe with InferenceService!

In this step-by-step tutorial, learn how to build, visualize, and deploy a Scikit-learn machine learning model using Streamlit for the UI, Docker for containerization, and Kubernetes (Minikube) for…

This demo demonstrates penetration testing and CIS Benchmark scanning techniques on a Kubernetes cluster using kube-hunter for security assessment of the cluster to identify vulnerabilities, and ku…

In this project, we build an Apache Airflow pipeline to load, train, and evaluate a ML model, store it, and use it for inferencing by deploying the model with a sleek Streamlit UI, Docker, and auto…

In this end-to-end CI/CD pipeline, we will automate the process from code commit to production deployment with security and quality checks of a NodeJS Application.

In this video, we take DevOps to the next level by building a complete GitOps-driven CI/CD pipeline using GitHub Actions and ArgoCD, deployed on Kubernetes! 💥

In this hands-on DevOps tutorial, we’ll walk through building a full-fledged Jenkins CI/CD pipeline to build, test, store, and deploy a Java application to Google Cloud Run using industry-standard…

In this project, we build a practical MLOps project that demonstrates a local feature store with Parquet file offline feature store and Redis online feature store to serve features for the training…

In this project, we use the Iris dataset to demonstrate a basic ML pipeline with DVC and Git for data and model versioning

In this project, we investigate how to fine-tune an LLm model on a custom data from IMDb (Internet Movie Database) and use it to make predictions. We will also package our application to generate a…