Mock Cloud Data Generator
Eliminate vendor lock-in during early-stage R&D. The MCD engine synthetically generates hyper-realistic cloud infrastructure payloads for secure, offline testing.
MCD Generator
The Mock Cloud Data (MCD) Generator. A complete closed-loop engine for simulating cloud infrastructure footprints, detecting zombie servers, and training enterprise FinOps agents safely.
1. Infrastructure Sprawl
Simulate realistic cloud environments with unoptimized runtimes and orphaned storage volumes to stress-test your monitoring tools without risking production data.
2. Zombie Server Detection
Feed MCD data directly into the m4 Cloud Risk Agent via RAG protocols to automatically identify and eliminate inactive compute instances draining the budget.
3. Green Footprinting
Utilize Human-in-the-Loop (HITL) workflows to track inefficiencies and reduce your cloud carbon footprint by terminating resource waste.
Developer Installation Guide
Deploy the MCD Generator locally to begin simulating your cloud FinOps data.
Prerequisites
Ensure you have Python 3.10+ installed and an active virtual environment. A basic understanding of JSON RAG structures is recommended.
Installing via Pip
You can install the MCD generator directly into your project via pip, or clone the repository to run it as a standalone server.
# Or run via python directly
python3 -m mcd_generator –mode=simulate –instances=100
Connecting to the m4 Risk Agent
To pass the generated mock data to your local LLM or the m4 Risk Agent, configure your environment variables to point to the MCD output directory:
eridu-agent run –target=m4 –analyze-sprawl