Microsoft's multi-agent framework on dedicated self-healing NixOS servers.
Watchdog monitors each AutoGen agent independently. Every action audited.
"Show agent status" — OpenClaw gives real-time health for all agents.
AutoGen Hosting for Multi-Agent Production Systems
Deploy AutoGen multi-agent conversations to production on dedicated NixOS servers with sandboxed code execution, watchdog auto-restart, group chat supervision, and tamper-proof audit logging. The production runtime that AutoGen Studio cannot provide. Plans start at $14.99/month.
AutoGen is Microsoft's multi-agent conversation framework that enables LLM-powered agents to collaborate through structured conversations, generate and execute code, and solve complex tasks together. The framework supports conversation patterns ranging from simple two-agent chats to complex group chats with dynamic speaker selection. AutoGen 0.4 introduced a complete architectural redesign based on the actor model for distributed, scalable, event-driven agent systems. However, AutoGen Studio, the low-code UI for building multi-agent workflows, is explicitly a research prototype: it lacks authentication, security features, and production-grade process supervision. Microsoft themselves recommend building your own production infrastructure. osModa fills that gap, providing the dedicated hosting, code execution sandboxing, and process supervision that production AutoGen deployments demand.
TL;DR
- • Deploy AutoGen multi-agent conversations in production -- something AutoGen Studio explicitly cannot do as a research prototype
- • Every conversation pattern supported: two-agent, group chat, sequential, and nested chat with per-agent watchdog supervision
- • Sandboxed code execution with Docker + resource limits prevents LLM-generated code from crashing the server or consuming all resources
- • Supports AutoGen 0.2/AG2, AutoGen 0.4 (actor model), and the Microsoft Agent Framework -- SHA-256 audit logging from $14.99/mo
Why AutoGen Studio Is Not Production-Ready
AutoGen Studio is a valuable prototyping tool, but Microsoft is explicit about its limitations. Understanding these limitations clarifies why production AutoGen deployments need purpose-built hosting.
No Authentication or Security
AutoGen Studio does not implement authentication or security measures required for production deployments. There are no rigorous tests for LLM data access permissions, no jailbreak protections, and no access controls. osModa provides infrastructure-level security: P2P encrypted mesh networking with Noise_XX + ML-KEM-768, secrets management for API keys, and tamper-proof audit logging for every agent action.
Limited Workflow Support
AutoGen Studio only supports two-agent and GroupChat workflows. Other agent types and conversation patterns are not available through the UI. Only serializable properties of the ConversableAgent class are exposed. On osModa, you deploy the full AutoGen framework with no UI limitations, supporting every conversation pattern: two-agent, sequential, group chat, and nested chat.
No Process Supervision
AutoGen Studio does not monitor or restart agent processes. If a multi-agent conversation crashes mid-execution, it is gone. There is no watchdog, no automatic recovery, and no state preservation. osModa's watchdog daemon monitors every AutoGen process and restarts it on failure, preserving conversation state so agents do not start over.
Breaking Changes Expected
AutoGen Studio is under active development with expected breaking changes in upcoming releases. Production systems cannot tolerate unexpected breakage. osModa's NixOS atomic deployments ensure that updates are tested before going live, and instant rollback reverts to the last known-good configuration if anything breaks.
Microsoft recommends using the AutoGen framework directly to build production applications. osModa provides the infrastructure to do exactly that. Learn more on our AI agent hosting page.
AutoGen Conversation Patterns on osModa
AutoGen supports multiple conversation patterns for different multi-agent use cases. osModa provides infrastructure-level support for each pattern.
Two-Agent Chat
The simplest pattern: two agents conversing to solve a task. Common for code generation where an AssistantAgent writes code and a UserProxyAgent executes it. osModa monitors both agents and the code execution process independently, restarting on failure.
Group Chat
Multiple agents contributing to a single conversation thread with shared context, orchestrated by a GroupChatManager that handles dynamic speaker selection. osModa's watchdog monitors every agent in the group and the manager independently. The audit ledger records all speaker selections and agent responses.
Sequential Chat
A sequence of two-agent chats chained by a carryover mechanism that passes summaries between conversations. Useful for multi-stage pipelines. osModa preserves the carryover state across conversations so a crash at stage 3 does not require restarting from stage 1.
Nested Chat
Complex workflows packaged into a single agent using internal sub-conversations. A tool-caller agent starts a nested chat with a tool-executor agent. osModa monitors both the outer and inner conversation processes, ensuring nested failures do not silently propagate to the parent.
Code Execution
AutoGen agents generate and execute Python code as part of conversations. DockerCommandLineCodeExecutor provides sandboxed execution. osModa adds resource limits to prevent LLM-generated code from consuming all CPU or memory, and the audit ledger records every code execution with input and output.
Watchdog + SafeSwitch
osModa's watchdog monitors every AutoGen process with rapid recovery. SafeSwitch handles deployment transitions: new code deploys and health-checks pass before the old version stops. Zero downtime updates, even during active multi-agent conversations.
Deploy AutoGen to Production
Three steps from a local AutoGen prototype to a production multi-agent system.
- 1
Provision at spawn.os.moda
Select a plan based on agent count, conversation complexity, and whether agents execute code. Group chats with code generation need more resources than simple two-agent conversations. Each plan provisions a dedicated Hetzner server with osModa, Python, AutoGen, Docker for code sandboxing, and all dependencies pre-installed.
- 2
Configure your agents
Upload your AutoGen application code or pull from a Git repository. Define agent configurations, conversation patterns, and code execution settings. Configure LLM API keys through the secrets management dashboard. Set health check parameters for your agent processes. The system generates NixOS configuration automatically.
- 3
Run and monitor
Your AutoGen multi-agent system is live. The watchdog supervises every agent process. Code execution is sandboxed with resource limits. The audit ledger records every conversation turn, tool call, and code execution. SSH in anytime. Update deployments near-instantly with NixOS atomic switching.
For a complete deployment walkthrough, read our deployment guide. For pricing details, see hosting pricing.
The AutoGen Ecosystem in 2026
The AutoGen ecosystem has split into three distinct paths, each with different production characteristics. Understanding these paths helps you choose the right framework for your needs.
AG2 (Community Fork)
AG2 is the community-driven fork maintained by AutoGen's original creators, Chi Wang and Qingyun Wu, who departed Microsoft in late 2024. AG2 maintains backward compatibility with AutoGen 0.2, providing stability and a familiar API. The original creators retained control of the PyPI packages and Discord community. However, AG2 lacks a first-party observability platform, meaning you are on your own for logging and tracing in production. osModa's audit ledger fills this observability gap.
AutoGen 0.4 (Microsoft)
AutoGen 0.4 is Microsoft's complete architectural redesign, built on the actor model for distributed, scalable, event-driven agent systems. The layered architecture separates the Core API (actor framework), AgentChat API (high-level task-driven framework), and Extensions (third party integrations). The actor model makes agents inherently distributable and composable, but requires infrastructure that can supervise distributed actor processes. osModa provides this through per-process watchdog monitoring.
Microsoft Agent Framework
Announced in October 2025, the Microsoft Agent Framework merges AutoGen and Semantic Kernel into a unified production-grade platform. AutoGen and Semantic Kernel are now in maintenance mode with only bug fixes and security patches. The Agent Framework targets GA by end of Q1 2026 with stable versioned APIs, production-grade support, and enterprise readiness certification. osModa will support the Agent Framework on GA, and already supports the current preview release.
All three paths run on osModa. For alternative approaches to multi-agent systems, explore CrewAI hosting for crew-based orchestration or OpenAI Agents SDK hosting for lightweight multi-agent workflows.
AutoGen Hosting: osModa vs AutoGen Studio vs Generic VPS
Three ways to run AutoGen in production. Here is how they compare.
| Capability | osModa | AutoGen Studio | Generic VPS |
|---|---|---|---|
| Production-ready | Yes | No (research prototype) | DIY |
| Authentication | Built-in | None | DIY |
| Conversation patterns | All patterns | Two-agent + GroupChat | All patterns |
| Watchdog auto-restart | Per-agent | None | DIY systemd |
| Code execution sandbox | Docker + limits | Docker only | DIY Docker |
| Audit logging | SHA-256 tamper-proof | None | None |
| Atomic rollbacks | NixOS native | None | No |
| Stability | Stable infra | Breaking changes expected | Stable infra |
osModa provides the production infrastructure that AutoGen Studio explicitly does not. Learn more about framework comparisons on our framework hub.
Code Execution Sandboxing for AutoGen
AutoGen agents frequently generate and execute code. This is one of the framework's most powerful features, but also its most dangerous in production. LLM-generated code can contain infinite loops, consume all available memory, make unauthorized network calls, or modify system files.
Docker Sandboxing
AutoGen provides DockerCommandLineCodeExecutor for running code in isolated containers. The framework explicitly warns against using LocalCommandLineCodeExecutor due to the security risks of executing LLM-generated code in the host environment. osModa pre-configures Docker for code execution with appropriate security policies.
Resource Limits
osModa enforces CPU and memory limits on code execution containers. An infinite loop generated by an LLM is killed after consuming its resource quota, not after crashing the entire server. A memory-hungry script is terminated before it triggers OOM kills on the AutoGen process itself.
Execution Auditing
Every code execution is recorded in the SHA-256 hash-chained audit ledger: the generated code, execution environment, resource usage, output, and any errors. This provides a complete, tamper-proof record of what LLM-generated code ran on your server, essential for debugging and compliance.
Network Isolation
Code execution containers can be configured with restricted network access. An LLM-generated script cannot make unauthorized API calls or exfiltrate data through network requests unless explicitly permitted. This is critical for production AutoGen deployments handling sensitive data.
Code execution sandboxing is one of the reasons why production AutoGen deployments need more than a bare VPS. For more on infrastructure security, see our self-healing server documentation.
Frequently Asked Questions
What is AutoGen hosting?
AutoGen hosting is dedicated server infrastructure designed to run Microsoft AutoGen multi-agent systems in production 24/7. AutoGen enables multi-agent conversations where LLM-powered agents collaborate, generate code, and execute tasks. Unlike AutoGen Studio, which is a research prototype not designed for production, AutoGen hosting on osModa provides watchdog supervision for every agent process, sandboxed code execution, tamper-proof audit logging, and dedicated resources. Plans start at $14.99/month.
Is AutoGen Studio production-ready?
No. AutoGen Studio is explicitly described as a research prototype that is not meant to be used in a production environment. It lacks authentication, security features, and only supports two agent and GroupChat workflows. It does not implement rigorous security testing for LLM data access permissions. Microsoft recommends that developers use the AutoGen framework directly and implement their own authentication, security, and production features. osModa provides the production infrastructure that AutoGen Studio does not.
What happened to AutoGen? Is it now AG2 or Microsoft Agent Framework?
In late 2024, AutoGen's original creators departed Microsoft and established AG2 as a community-driven fork maintaining backward compatibility with AutoGen 0.2. Microsoft continued with AutoGen 0.4, a complete architectural redesign based on the actor model. In October 2025, Microsoft announced the Agent Framework, merging AutoGen and Semantic Kernel. AutoGen and Semantic Kernel are now in maintenance mode with bug fixes only, while the Agent Framework targets GA by end of Q1 2026. osModa supports all three: AutoGen 0.2/AG2, AutoGen 0.4, and the Microsoft Agent Framework.
How does osModa handle AutoGen code execution?
AutoGen agents frequently generate and execute Python code as part of multi-agent conversations. The framework provides DockerCommandLineCodeExecutor for sandboxed execution and warns against using LocalCommandLineCodeExecutor due to the risk of running LLM-generated code in the local environment. osModa provides process-level isolation for code execution with resource limits, preventing runaway LLM-generated code from consuming all server resources or affecting other agent processes.
Can I run AutoGen group chats on osModa?
Yes. AutoGen's group chat pattern enables multiple agents to contribute to a single conversation thread with shared context, orchestrated by a GroupChatManager that handles dynamic speaker selection, agent responses, and message broadcasting. On osModa, every agent in the group chat is monitored independently by the watchdog daemon. If any agent crashes during a group chat, it restarts automatically. The audit ledger records every agent message, speaker selection, and tool call.
How does AutoGen 0.4's actor model work on osModa?
AutoGen 0.4 uses the actor model for distributed, event-driven agentic systems. Each agent is an actor that receives and sends messages asynchronously. This architecture is inherently distributed and benefits from dedicated server resources without shared-tenant contention. osModa's process supervision layer monitors each actor independently, and the audit ledger records inter-actor message passing for debugging distributed agent interactions.
What are the resource requirements for AutoGen?
AutoGen resource requirements depend on the number of concurrent agents, the LLMs used, and whether agents generate and execute code. A basic two-agent conversation needs minimal resources, but group chats with code execution, multiple LLM calls, and Docker containers need 4+ CPU cores and 8-16 GB RAM. osModa plans provide dedicated resources sized for production AutoGen workloads.
How much does AutoGen hosting cost on osModa?
osModa plans start at $14.99/month for a dedicated server with all features included. Every plan includes watchdog supervision, code execution sandboxing, audit logging, P2P mesh networking, secrets management, and all built-in tools. There are no per-agent charges, no per-conversation surcharges, and no usage caps. Run as many agents and group chats as your server resources support.
Your AutoGen Agents Deserve Production-Grade Infrastructure
Stop using a research prototype for production workloads. Stop running LLM-generated code without sandboxing or audit trails. osModa provides the production runtime that AutoGen demands. Dedicated servers, watchdog supervision, code sandboxing, tamper-proof audit. From $14.99/month.
Last updated: March 2026