function serving deployment failed

Question

Here, I'm attaching actual error showed. im using mlrun with docker. specifically mlrun 1.2.0.

--------------------------------------------------------------------------
RunError                                  Traceback (most recent call last)
<ipython-input-20-aab97e08b914> in <module>
      1 serving_fn.with_code(body=" ") # adds the serving wrapper, not required with MLRun >= 1.0.3
----> 2 project.deploy_function(serving_fn)

/opt/conda/lib/python3.8/site-packages/mlrun/projects/project.py in deploy_function(self, function, dashboard, models, env, tag, verbose, builder_env, mock)
   2307         :param mock:        deploy mock server vs a real Nuclio function (for local simulations)
   2308         """
-> 2309         return deploy_function(
   2310             function,
   2311             dashboard=dashboard,

/opt/conda/lib/python3.8/site-packages/mlrun/projects/operations.py in deploy_function(function, dashboard, models, env, tag, verbose, builder_env, project_object, mock)
    344             )
    345 
--> 346         address = function.deploy(
    347             dashboard=dashboard, tag=tag, verbose=verbose, builder_env=builder_env
    348         )

/opt/conda/lib/python3.8/site-packages/mlrun/runtimes/serving.py in deploy(self, dashboard, project, tag, verbose, auth_info, builder_env)
    621             logger.info(f"deploy root function {self.metadata.name} ...")
    622 
--> 623         return super().deploy(
    624             dashboard, project, tag, verbose, auth_info, builder_env=builder_env
    625         )

/opt/conda/lib/python3.8/site-packages/mlrun/runtimes/function.py in deploy(self, dashboard, project, tag, verbose, auth_info, builder_env)
    550             self.status = data["data"].get("status")
    551             self._update_credentials_from_remote_build(data["data"])
--> 552             self._wait_for_function_deployment(db, verbose=verbose)
    553 
    554             # NOTE: on older mlrun versions & nuclio versions, function are exposed via NodePort

/opt/conda/lib/python3.8/site-packages/mlrun/runtimes/function.py in _wait_for_function_deployment(self, db, verbose)
    620         if state != "ready":
    621             logger.error("Nuclio function failed to deploy", function_state=state)
--> 622             raise RunError(f"function {self.metadata.name} deployment failed")
    623 
    624     @min_nuclio_versions("1.5.20", "1.6.10")

RunError: function serving deployment failed

I don't have any idea what is the reason behind this error. as I'm new bee here. so someone pls help me to resolve this error.

Answer 1

I see two steps, how to solve the issue:

1. Relevant installation

The MLRun Community Edition in desktop docker has to be install under relevant HOST_IP (not with localhost or 127.0.0.1, but with stable IP address, see ipconfig) and with relevant SHARED_DIR. See relevant command line (from OS windows):

set HOST_IP=192.168.0.150
set SHARED_DIR=c:\Apps\mlrun-data
set TAG=1.2.0

mkdir %SHARED_DIR%

docker-compose -f "c:\Apps\Desktop Docker Tools\compose.with-jupyter.yaml" up

BTW: YAML file see https://docs.mlrun.org/en/latest/install/local-docker.html

2. Access to the port

In case of call serving_fn.invoke you have to open relevant port (from deploy_function) on your IP address (based on setting of HOST_IP, see the first point).

Typically this port can be blocked based on your firewall policy or your local antivirus. It means, you have to open access to this port before invoke call.

BTW: You can see focus on the issue https://github.com/mlrun/mlrun/issues/2102