Monitoring Agent Platform
Microservice Engineer
A dual-service microservice architecture designed to ingest agent events and simulate realistic monitoring data using Groq (Llama 3.1). Engineered for seamless containerized deployment on AWS EC2.
30 Events
Window
Docker / EC2
Availability
Groq / TS
Core Stack
The Challenge
Needed a robust way to ingest agent events and monitor them via a Prometheus-style interface. The goal was to build a functional prototype to test LLM-driven event simulations in real-time.
My Approach
Built a dual-service architecture. Service A handles ingestion and metrics, while Service B uses Groq (Llama 3.1) to generate realistic monitoring data. Deployed the entire stack using Docker for easy replication on AWS EC2.
Core Technical Accomplishments
Dual-Service REST API
Built a Node.js API with a rolling memory buffer to track the last 30 events, providing a live Prometheus metrics endpoint for monitoring.
Groq/Llama Simulation
Integrated Groq with Llama 3.1 to dispatch realistic agent events every 60 seconds, replacing static test data with dynamic, production-like payloads.
Docker & AWS EC2
Containerized both services with Docker Compose for a 'one-command' setup on an AWS EC2 instance, including pre-configured security groups for metric access.
Results & Impact
- Successfully integrated Groq with Llama 3.1 for high-fidelity LLM event simulation
- Deployed a containerized stack to AWS EC2 with a functional Prometheus metrics endpoint
- Achieved zero-record loss within the 30-event rolling window tracking logic
- Implemented a dual-service architecture for clean separation of concerns and scalability