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markiskorova/ai-ops-assistant

πŸ› οΈ AI Ops Assistant β€” A Go-based backend system for automated log summarization, ticket triage, and changelog generation. Built with GraphQL, JWT auth, PostgreSQL, and a worker queue architecture for scalable operations.

🧠 AI Ops Assistant

AI Ops Assistant is a cloud-native backend project simulating an AI-powered operational triage and summarization platform. Designed with scalability and team productivity in mind, it showcases engineering patterns applicable to internal tooling, data processing, and privacy-conscious automation.

Built using Go, GraphQL, Docker, and Terraform with secure JWT auth, this system processes logs and tickets asynchronously, summarizes them via OpenAI, and delivers insights via a robust APIβ€”making it ideal for platforms focused on data control, governance, and observability.


βš™οΈ Tech Stack

  • Backend: Go 1.23, GORM (PostgreSQL), GraphQL (graphql-go)
  • AI Integration: OpenAI API for summarization
  • Auth: JWT
  • Infra: Docker, Docker Compose, Terraform (AWS)
  • DevOps: GitHub Actions (CI/CD ready)
  • Observability: Prometheus (metrics), Grafana (dashboards), Alertmanager (alerts)

βœ… Key Features

  • 🧾 Summarizes logs using OpenAI's GPT API.
  • 🏷️ Classifies tickets with pluggable business logic.
  • 🌐 GraphQL API for querying logs, tickets, and changelogs.
  • πŸ”’ JWT-secured authentication and modular user management.
  • 🧡 Cleanly separated microservice-style API and worker processes.
  • πŸ“Š Observability with Prometheus & Grafana:
    • API & Worker metrics exported at /metrics
    • Dashboards for API throughput, latency (P95/P99), error rates
    • Worker throughput, failures, and queue depth
    • Alert rules for error rates, latency, and backlogs
  • πŸ—οΈ Infrastructure-as-Code via Terraform (AWS RDS, ECS, IAM).
  • 🐳 Local development via Docker Compose with minimal setup.

πŸ“ System Design

See the System Design One-Pager for an architecture breakdown.

Architecture Diagram


πŸ§ͺ Run Locally

Core stack

docker-compose up --build

GraphQL API available at:

http://localhost:8080/graphql

With observability stack

docker-compose -f docker-compose.yml -f docker-compose.obsv.yml up -d --build

Provisioned dashboard: AI Ops β€” API & Workers
(Shows API & worker throughput, latency, errors, and queue depth.)


πŸ›£οΈ Project Roadmap

See the Project Plan & Roadmap for phased implementation and future plans.
Observability is part of Phase 3 – Infrastructure & Observability.


πŸ§‘β€πŸ’» Author Notes

This project was created to demonstrate backend leadership and infrastructure fluency aligned with real-world SaaS tooling. Its design prioritizes modularity, secure data handling, observability, and developer productivity.


MIT License