Helm plugin that identifies the configuration that has drifted from the Helm chart

📊 This Project demonstrates a GitOps-driven CI/CD pipeline using Jenkins, Helm, and ArgoCD. It ensures reproducible deployments, reduces configuration drift, and automates the build, test, and deployment workflows across multiple environments.

helm-snoop can detect drift between the values.yaml file and the helm template files. Making sure the documentation matches the implementation and protecting from typos.

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End-to-end MLOps: training → MLflow → containerized FastAPI → Helm+HPA → Prom/Grafana → drift checks → CI/CD with GitHub Actions

Zero-Config. Ultra-Lightweight. Drift-Aware. A single binary/container that runs inside your Kubernetes cluster and immediately shows you how your installed Helm charts differ from their latest upstream versions. No configuration files. No controllers. Just deploy and see the drift.

An AI-native agentic platform for Kubernetes observability. It surfaces "underwater" unmanaged Helm deployments, performs real-time drift analysis against live release data, and generates proactive GitOps migration paths. Built with NestJS and LangGraph.

Local GitOps training platform using ArgoCD, Helm, Terraform, and Kubernetes on Minikube. Learn deployment automation, drift detection, CI/CD with GitHub Actions, and observability with Prometheus and Grafana. Progressive exercises teach production SRE practices entirely on macOS.

Helm Drift Detect

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Automated Helm Drift Detection for Kubernetes HPA and Service Ports powered by Bash, yq, and GitHub Actions to detect changes made in live cluster before one commits again to same file as well as useful for PRs along with saving the logs of changes with timestamps, changes made and editor's name in CSV format in a single file in same repo.

No description available

No description available

No description available

Automated Helm Drift Detection for Kubernetes HPA and Service Ports powered by Bash, yq, and GitHub Actions to detect changes made in live cluster before one commits again to same file as well as useful for PRs along with saving the logs of changes with timestamps, changes made and editor's name in CSV format in a single file in same repo.

Helm chart repository for testing Helm deployment drift detection with ArgoCD

Continuous Kubernetes drift detection + auto-remediation PRs for clusters managed by Helm/Kustomize/GitOps.

An AI agent that continuously detects and reconciles configuration drift between my IaC (Terraform + Helm) and live infrastructure.

Production-grade demand forecasting system with drift detection, automated retraining, and monitoring dashboard. Deployed on Kubernetes via Helm with CI/CD through GitHub Actions.

An AWS machine learning platform that simulates streaming data ingestion, detects data drift, and automatically retrains and serves anomaly detection models. Utilizes EKS, Helm, Terraform, Python, and Flask. Project built for learning purposes.

ObservaGuard is an AI-powered DevOps platform that detects Kubernetes configuration drift and secret leaks. It combines FastAPI, React, Go, and an IsolationForest ML model, with Docker, Helm, and Prometheus integration, offering a full microservices stack deployable locally or on K8s.