Best AutoGen setup for a hybrid on-prem and Azure deployment

Alright, listen up. I've just spent the last three weeks untangling a so-called "production-ready" AutoGen setup that tried to bridge our dusty on-prem Kubernetes cluster and Azure AKS. It was a mess of timeouts, credential hell, and more network hops than a bad conference call. Everyone wants the shiny AutoGen multi-agent workflows until they realize the agents are trying to talk to each other over a VPN that's held together with legacy scripts and hope.

The core challenge in a hybrid environment isn't the AutoGen code itself—it's the orchestration plane and the network fabric. You can't have your `UserProxyAgent` on-prem waiting for a `GroupChat` manager that's throttling in Azure because someone decided to use the cheapest possible networking tier. Latency will murder your workflows.

Here's the setup that finally stopped making me want to throw my monitor out the window. The key is treating your on-prem and Azure segments as two distinct operational zones with a very clear, minimal bridge.

* **Orchestrator Location:** Run your main AutoGen *orchestrator* (the script that initiates and manages the `GroupChat` or `AssistantAgent` conversations) in Azure, close to your LLM endpoints (like Azure OpenAI). This keeps the high-frequency, chatty logic off your on-prem bottleneck.
* **Specialized On-Prem Agents:** Deploy only the agents that absolutely need direct access to on-prem resources as standalone services *inside* your on-prem network. Think of these as "gateway agents." For example, a `CodeExecutionAgent` that can run tests against a local database, or a `FileRetrievalAgent` that pulls from an internal wiki.
* **Communication Layer:** This is the critical bit. Don't let AutoGen's innate HTTP calls route arbitrarily. We exposed the on-prem agents as internal HTTP endpoints (FastAPI works fine) and used a secured, persistent Azure Service Bus topic for message passing. The on-prem agent listens for its specific topic, performs its local task, and posts the result back to a response topic.

A stripped-down config for the Azure side orchestrator looks something like this. Notice the `llm_config` points to Azure OpenAI, and the `code_execution_config` is **not** used here—that's handled by the on-prem agent.

```python
# Azure Orchestrator (simplified)
from autogen import AssistantAgent, UserProxyAgent, GroupChat, GroupChatManager

# Primary agents in Azure
azure_assistant = AssistantAgent(
name="azure_planner",
llm_config={
"config_list": [{
"model": "gpt-4",
"api_type": "azure",
"api_base": "https://your-openai-endpoint.openai.azure.com/",
"api_key": os.getenv("AZURE_OPENAI_KEY"),
}],
"temperature": 0,
},
system_message="You plan the overall task and delegate to specialists."
)

# This UserProxyAgent doesn't execute code. It passes requests to the Service Bus.
user_proxy = UserProxyAgent(
name="user_proxy",
human_input_mode="NEVER",
code_execution_config=False, # No local execution
max_consecutive_auto_reply=2,
)

# Function to dispatch tasks to on-prem via Service Bus (pseudo-code)
def dispatch_to_on_prem(task, agent_name):
# ... logic to send message to Service Bus topic for 'agent_name'
message_id = service_bus_sender.send_message(Message(body=json.dumps(task)))
# ... wait for and retrieve response from the response topic
return response_message.body

# Register the function with the agent
user_proxy.register_function(
function_map={
"run_onprem_tests": lambda task: dispatch_to_on_prem(task, "onprem_test_agent"),
"query_local_kb": lambda task: dispatch_to_on_prem(task, "onprem_kb_agent"),
}
)
```

On the on-prem side, you have a simple service that subscribes to its topic, runs the actual operation (e.g., executes a `pytest` suite in a controlled container), and fires the result back.

The pitfalls you must avoid:

* Trying to make a single, flat AutoGen agent group span both networks. The internal websocket/http calls will fail.
* Forgetting egress rules from Azure to your on-prem VPN gateway and, more importantly, the *reverse*. Your on-prem nodes need a secure route *out* to Azure Service Bus.
* Assuming your on-prem Docker registry is accessible from Azure. It won't be. Use Azure Container Registry for Azure images, mirror necessary on-prem images up there.
* Not implementing idempotency and proper message de-duplication in your Service Bus handlers. Network glitches *will* cause duplicate messages.

It's more infrastructure work upfront, but it's the only way I've found that doesn't collapse under a real load. The alternative is watching your CI/CD pipeline grind to a halt because an agent is stuck trying to SSH through a firewall it can't see.

fix the pipe