San Franscico, CA, June 26, 2025 –(PR.com)– Bunnyshell has launched its Multi-Agent Containerization System (MACS), an AI-powered platform that transforms raw code repositories into production-ready Docker and Compose assets with zero manual work. Early users report that MACS cuts containerization time from weeks to under an hour.
Alin Dobra, Founder at Bunnyshell, shared, “Teams lose days creating Dockerfiles and configuring environments. MACS removes that burden by letting AI agents collaborate, validate outputs, and deliver production-ready assets automatically.”
MACS offers zero-touch onboarding. Users simply paste a Git repository URL, and the system takes over—analyzing, building, and testing the application automatically. This process is powered by a multi-agent system where dedicated AI agents work in parallel on specialized tasks.
The architecture includes an Orchestrator agent that delegates work to Analyzer, Researcher, and Executor agents. Analyzer agents scan codebases to detect frameworks and services. Researcher agents retrieve external deployment best practices. Executor agents build, test, and validate the final container images. This collaborative system allows agents to run independently while sharing results, enabling rapid and reliable outputs.
MACS automatically verifies each generated image. Containers are built, run, and tested with health checks and validation gates. The Compose files generated by MACS follow best practices, including pinned dependencies, multi-stage builds, health checks, and resource limits.
MACS is now available to all Bunnyshell Cloud Development Environment (CDE) customers. It supports monoliths, microservices, databases, machine learning servers, and static websites. Supported technologies include Node.js, Python, Ruby, PHP, Java, Go, .NET, MySQL, Postgres, MongoDB, Redis, and popular queue systems.
The multi-agent design provides faster results and higher reliability. Agents work in parallel, each applying specialized knowledge. MACS also runs self-correction loops, automatically refining outputs until validation checks pass. This process reduces containerization lead time by more than 95%.
Production safety is a core feature. MACS enforces immutability, pins dependencies, and uses secure base images. Secrets are managed via environment files or orchestrator vaults, never hard-coded. Health checks and restart policies are automatically included to improve resilience.
Powered by GPT-4.1 for orchestration and compact reasoning models for fast tasks, the agents run in isolated Docker sandboxes with strict resource controls. All steps, token usage, and decisions are fully traceable.
Getting started with MACS is simple. Users can run one CLI command with their repository link. Within minutes, MACS provides a docker-compose.yml file ready for deployment.
Users should carefully review all generated files before using them in production, as AI-generated outputs may contain occasional errors.
For more information, visit bunnyshell.com.
