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Refresh doesn't actually run your pulumi program, so that might explain some fo the difference in behavior you're seeing. Pulumi programs use a couple of local gRPC servers to orchestrate different processes. I would not expect this to be a problem, but perhaps there is some sort of network policy blocking these services from networking together?

Great thoughts. Thanks for taking a look. I've opened all network traffic (temporarily) for troubleshooting which didn't make a difference, so not feeling like that's the issue. It looks like it actually is throwing on the gRPC call as you suggested after digging deeper.

/home/node/app/node_modules/@grpc/grpc-js/src/call.ts:81
  return Object.assign(new Error(message), status);
                       ^
Error: Resource monitor is terminating
    at Object.callErrorFromStatus (/home/node/app/node_modules/@grpc/grpc-js/src/call.ts:81:24)
    at Object.onReceiveStatus (/home/node/app/node_modules/@grpc/grpc-js/src/client.ts:338:36)
    at Object.onReceiveStatus (/home/node/app/node_modules/@grpc/grpc-js/src/client-interceptors.ts:426:34)
    at Object.onReceiveStatus (/home/node/app/node_modules/@grpc/grpc-js/src/client-interceptors.ts:389:48)
    at /home/node/app/node_modules/@grpc/grpc-js/src/call-stream.ts:276:24
    at processTicksAndRejections (node:internal/process/task_queues:77:11)

I'll bump the specs to see if that makes a difference. Not sure where this would leave me if traffic is open and specs don't work though.

Copy code

Resource monitor is terminating

This typically indicates resource exhaustion in my experience. Glad to hear you're unblocked partypus 8bit

@few-carpenter-12885 I'd like to ask some follow up questions, if you don't mind. I'm keenly interested in improving our memory consumption to enable higher-scale use of automation API. Could you let me know here or via DM how much memory did the Fargate instance have available initially, and what providers were being used (AWS, GCP, etc)?

Initially, Fargate was provisioned with .5 CPU and 2GB RAM. I bumped it to 1 CPU and 8GB, and the issue was resolved. Not sure where the sweet spot between there might be.