I see what you mean. To some companies, ML Engine's cost as a managed service may be worth it. To others, spinning up a VM with TensorFlow Serving on it is wort

I see what you mean. To some companies, ML Engine's cost as a managed service may be worth it. To others, spinning up a VM with TensorFlow Serving on it is worth the cost savings. If you've taken other approaches to serving TensorFlow models to get around ML Engine's per-prediction cost, I'm curious to hear about them.