Popular GitHub Repositories for Prometheus

A ChatGPT bot for Kubernetes issues.

Anomaly detection

Create custom DevOps AI agents that understand and manage your infrastructure.

Maternal Health Risk prediction MLOps pipeline

This sample shows how to create two AKS-hosted chat applications that use OpenAI, LangChain, ChromaDB, and Chainlit using Python and deploy them to an AKS environment built in Terraform.

Security Analytics Engine - Anomaly Detection in Web Traffic

? A scalable, production-ready data pipeline for real-time streaming & batch processing, integrating Kafka, Spark, Airflow, AWS, Kubernetes, and MLflow. Supports end-to-end data ingestion, transformation, storage, monitoring, and AI/ML serving with CI/CD automation using Terraform & GitHub Actions.

Kafka variant of the MLOps Level 1 stack

Deep Learning model monitoring

Python SDK for vishwa.ai

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Model Monitoring using Prometheus and Grafana

A modular, multi-agent AI research and report generation platform. Enter any topic, and PolyAgent Research Intelligence orchestrates multiple AI agents to retrieve literature, analyze data, and generate a polished report. Built for researchers and AI/ML engineers, leveraging LangChain, FastAPI, PostgreSQL, advanced LLMs, and a Next.js front-end.

A comprehensive platform that integrates various ai-powered tools and useful websites

Talk to your metrics.

Big ML Project with infrastructure (MLflow, Minio, Grafana), backend (FastAPI, Catboost) and frontend (React, Maplibre)

Testing out SeaweedFS for s3 storage. Particularly for MLOps purposes.

Built a pipeline to manage real-time environmental data using DVC, developed a time-series model (LSTM) with MLflow to predict pollution trends, and deployed the best model as an API using Flask. Implemented live data testing with continuous monitoring using Grafana and Prometheus, enabling real-time performance tracking and system optimization.

? Run LLM inference locally for various downstream applications.

A pipeline using Kedro to orchestrate the deployment of a deep learning transformer model for classifying toxic comments. This project integrates data preprocessing, model training, and deployment into a streamlined and reproducible workflow, enabling efficient handling of the toxic comment classification problem in NLP.