The incredible HULL - Helm Uniform Layer Library - is a Helm library chart to improve Helm chart based workflows.
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Updated
May 13, 2026 - Python
The incredible HULL - Helm Uniform Layer Library - is a Helm library chart to improve Helm chart based workflows.
Real-time diagnostics dashboard for MongoDB Search (mongot) on Kubernetes — SRE checks, index inspector, log analysis, and cluster health reports.
A sample ML app that trains a model and we deploy it to k8s
This project automates the deployment of a YOLO Object Detection API using Helm, Kubernetes, and implements logging and monitoring with the ELK stack (Elasticsearch, Logstash, Kibana) and Prometheus & Grafana.
A simple flask app, stores/retrieves joson in/from mongodb.
A beginner-friendly MLOps project that covers model training, FastAPI deployment, Dockerization, and Kubernetes deployment using a Random Forest model to predict diabetes based on health metrics.
Swami - Sample cloud-first application with 10 microservices showcasing Kubernetes, Istio, and gRPC.
Celsiusify is a benchmark project focused on DevOps and MLOps, featuring a FastAPI web app, Docker containerization, Kubernetes deployment using Helm, performance testing with Locust, CI/CD integration via GitHub Actions, and TensorFlow model serving. It aims to streamline the development and deployment processes for machine learning apps.
The goal of this project is to build a Python-based application and deploy it to a k8s cluster using Jenkins. The application image is stored in a repository such as Amazon Elastic Container Registry (ECR).
This project is used to monitor and alerting implementation on minikube cluster k8 by using docker (for contarization ), promethesus and grafana (for monitoring and data visualization)
Wrapper REST API for Telia Multi SMS API
A django-graphql microservice to model simple store operations
Minimal configuration with managed edge cases to deploy mariadb galera cluster in kubernetes cluster
Python application to test cookies on openshift 4.8
This project implements a machine learning pipeline to detect fraudulent credit card transactions. It uses logistic regression on a highly imbalanced dataset, applying SMOTE to balance classes.
Generic ArgoCD ApplicationSet plugin that fetches JSON from a URL and applies JSONPath or jq filtering. Helm chart: https://github.com/cmehat/argocd-applicationset-json-plugin-chart
Use Case of deploing kubernetes cluster on AWS EC2
Book-API-app
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