How to Fix 'deployment crash in production' in AutoGen (TypeScript)

A deployment crash in production in AutoGen TypeScript usually means your agent process is starting, reaching a runtime failure, and then dying before it can complete the first tool call or model turn. In practice, this shows up when the app works locally but crashes in Docker, on a server, or after deployment to Vercel, Azure, ECS, or Kubernetes.

Most of the time, the issue is not AutoGen itself. It’s a bad runtime assumption: missing env vars, an unsupported model/client config, an unhandled async error, or a tool that throws during agent execution.

The Most Common Cause

The #1 cause is misconfigured model client setup. In AutoGen TypeScript, people often wire OpenAIChatCompletionClient with missing credentials, wrong model names, or a provider mismatch that only fails once the agent starts talking to the model.

Typical runtime symptoms include:

• •OpenAI API key is missing
• •401 Unauthorized
• •Model not found
• •Error: deployment crash in production
• •AgentRuntimeError: failed to create chat completion

Here’s the broken pattern versus the fixed pattern:

// Broken
import { OpenAIChatCompletionClient } from "@autogenai/core";

const client = new OpenAIChatCompletionClient({
  apiKey: process.env.OPENAI_API_KEY,
  model: process.env.OPENAI_MODEL!, // may be undefined in prod
});

const response = await client.create({
  messages: [{ role: "user", content: "Hello" }],
});

// Fixed
import { OpenAIChatCompletionClient } from "@autogenai/core";

function requireEnv(name: string): string {
  const value = process.env[name];
  if (!value) throw new Error(`Missing required env var: ${name}`);
  return value;
}

const client = new OpenAIChatCompletionClient({
  apiKey: requireEnv("OPENAI_API_KEY"),
  model: requireEnv("OPENAI_MODEL"),
});

async function main() {
  const response = await client.create({
    messages: [{ role: "user", content: "Hello" }],
  });

  console.log(response);
}

main().catch((err) => {
  console.error("Startup failed:", err);
  process.exit(1);
});

In production, this matters because containerized deployments often inject env vars differently than local .env files. If OPENAI_MODEL is empty or points to a non-existent deployment name, the app may crash only after the first request.

Other Possible Causes

1. Tool function throws and kills the agent run

If you register a tool that throws synchronously or returns invalid data, AutoGen can fail mid-run.

// Broken
const tools = [
  {
    name: "lookupCustomer",
    description: "Fetch customer data",
    execute: async () => {
      throw new Error("DB connection failed");
    },
  },
];

Fix it by catching and returning structured failures:

// Fixed
const tools = [
  {
    name: "lookupCustomer",
    description: "Fetch customer data",
    execute: async () => {
      try {
        return await db.getCustomer();
      } catch (err) {
        return { ok: false, error: "DB connection failed" };
      }
    },
  },
];

2. Wrong message schema passed into the agent

AutoGen expects valid message objects. A malformed payload can trigger runtime exceptions like:

• •Invalid message format
• •Cannot read properties of undefined
• •messages[0].role is required

// Broken
await client.create({
  messages: [{ text: "Summarize this" }], // missing role/content
});

// Fixed
await client.create({
  messages: [{ role: "user", content: "Summarize this" }],
});

3. Node version mismatch in production

AutoGen TypeScript apps can behave differently across Node versions. If your local machine runs Node 20 but production runs Node 16 or an older Alpine image, you may see startup crashes.

Check your runtime:

{
  "engines": {
    "node": ">=18"
  }
}

And in Docker:

FROM node:20-alpine

4. Missing network access or blocked outbound calls

If your deployment environment blocks egress traffic to OpenAI/Azure/OpenRouter endpoints, the agent will fail on its first API call.

Common symptoms:

• •fetch failed
• •ETIMEDOUT
• •ECONNRESET
• •socket hang up

This is not an AutoGen bug. It’s usually a VPC/NAT/security group issue.

How to Debug It

1. •

   Check startup logs before the first agent call

   • •If the app dies before logging “agent ready,” it’s usually config or import-time failure.
   • •Add logs around client creation and agent initialization.
2. •

   Validate all env vars at boot

   • •Print whether each required variable exists.
   • •Do not log secrets; just log presence and length.
3. •

   Run the same container/image locally

   • •Build the exact Docker image used in production.
   • •If it fails there too, you’ve isolated it to runtime/config rather than infra.
4. •

   Wrap tool execution and model calls with try/catch

   • •Capture the original stack trace.
   • •Look for whether failure happens in:
     • •model client creation
     • •first completion request
     • •tool execution
     • •message parsing

Example diagnostic wrapper:

try {
  const result = await agent.run("Process claim #12345");
  console.log(result);
} catch (err) {
  console.error("Agent crashed:", err);
}

Prevention

• •

  Validate config at process startup with explicit checks for:

  • •API keys
  • •model/deployment names
  • •base URLs
  • •feature flags
• •

  Keep tool functions deterministic and defensive:

  • •catch DB/API errors
  • •return structured error objects
  • •avoid throwing from deep inside tool code
• •

  Pin your runtime:

  • •Node version in package.json
  • •Docker base image
  • •exact AutoGen package versions

If you’re seeing deployment crash in production with AutoGen TypeScript, start with env validation and model client setup. That’s where most real-world failures come from, and it’s also where you get the fastest fix.

Keep learning

• •The complete AI Agents Roadmap — my full 8-step breakdown
• •Free: The AI Agent Starter Kit — PDF checklist + starter code
• •Work with me — I build AI for banks and insurance companies

By Cyprian Aarons, AI Consultant at Topiax.