Google’s Agent Dev Kit Feels Magical — Until You Try Shipping Something Real With It

 ·

Did you know ADK is amazing for prototyping? But when you start building an actual product — with users, scale, telemetry, and compliance — things break in very unmagical ways.

1. There’s No Built-In Observability — So Good Luck Debugging Anything

In development, you can print to the console and pretend that’s logging. In production, you need structured logs, correlation IDs, error tracking, retries, event tracing, and live debugging.

Here’s what you don’t get with ADK by default:

• No structured logs (just print() or basic logging)
• No tracing across agent tools or nested calls
• No metrics on token usage, model response times, or tool execution stats
• No logging of failed or rejected prompts
• No way to replay conversations easily

This makes postmortems a nightmare. Did the agent hallucinate? Was the tool broken? Did it time out? You’ll never know.

You’re building reasoning systems without visibility into what they’re reasoning about.

2. The Agent Is “Smart” — But It’s Also a State Machine Without Memory Discipline

Google’s ADK gives you a powerful AgentContext object to persist memory and carry context across turns.

Sounds great — until you:

• Accidentally carry user secrets into unrelated tool calls
• Forgot to clear memory between sessions
• Try to implement multi-user workflows without session isolation.

ADK doesn’t enforce any boundaries. And that’s dangerous at scale. Example failure mode:

agent_context = AgentContext()
agent_context.put("customer_email", "alice@example.com")

3. Scaling ADK Agents Feels Like Hacking a Prototype Framework

Let’s say you want to run 10,000 ADK-based agents in a microservice architecture. What do you need?

• Stateless execution
• Dependency-injected tools
• Isolated memory per request
• Async support
• Graceful error handling
• Rate limiting
• Caching

ADK doesn’t give you this. You’ll end up:

• Rewriting the agent loop to run in FastAPI or gRPC
• Wrapping tool execution in retries and error boundaries
• Manually patching in Redis or a vector store for memory
• Using your monitoring to track LLM cost and latency

It’s not unfixable — but it’s not plug-and-play. You’ll build your runtime around ADK.

4. No Real Security Model for Secrets, Tools, or Isolation

Want to ship a SaaS product that talks to CRM, ERP, and finance APIs?

Here’s the checklist ADK doesn’t help with:

• Tool-level permissions (who can call what?)
• Secure vault integration for API keys
• Per-user context separation
• Revoking access tokens at runtime
• Audit logs for compliance

You’re flying blind unless you build your own auth + RBAC + telemetry system on top of the agent.

ADK lets agents call tools. But it doesn’t ask, “Should they?”

This is fine for devs hacking together personal agents. Not fine when you’ve got real users, real data, and real attack surfaces.

5. You Can’t Test Agents in Any Meaningful Way (Yet)

How would you write an automated test for an ADK agent?

• There’s no official test framework.
• No agent mocking system
• No snapshot testing for prompt outputs
• No way to simulate partial tool failures

So your “tests” are basically manual conversations. Until the ADK team gives us tooling, you’ll need to roll your own framework — or your agent will break every time a prompt changes, and nobody will notice.

So, should you still use ADK?

Google ADK is

• Great for fast prototyping
• Solid for internal tools
• Promising for agent-native apps

But it’s not yet battle-tested for:

• Compliance-heavy industries (health, finance, enterprise SaaS)
• High-scale workloads
• Production SLAs

If You’re Going to Use ADK in Production…

Here’s what you must bolt on:

1. Structured logging (OpenTelemetry, Sentry, etc.)

2. Runtime observability for tools and agents

3. Memory isolation + sanitization

4. Auth + RBAC for tool access

5. Secret management (Vault, GCP Secret Manager)

6. Testing harnesses with prompt snapshot validation

7. Cost tracking + LLM usage limits

8. Real CI/CD pipeline integration

Google ADK is magical. Until you try turning that magic into a product. If you’re just exploring, play away. But if you’re building for real users, real problems, and real scale?