Specification of a container for serving predictions. Some fields in this message correspond to fields in the Kubernetes Container v1 core specification .
imageUri 
 
  string 
 
Required. Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry. Learn more about the container publishing requirements , including permissions requirements for the Vertex AI service Agent.
The container image is ingested upon  ModelService.UploadModel 
 
, stored internally, and this original path is afterwards not used.
To learn about the requirements for the Docker image itself, see Custom container requirements .
You can use the URI to one of Vertex AI's pre-built container images for prediction in this field.
command[] 
 
  string 
 
Immutable. Specifies the command that runs when the container starts. This overrides the container's ENTRYPOINT 
. Specify this field as an array of executable and arguments, similar to a Docker ENTRYPOINT 
's "exec" form, not its "shell" form.
If you do not specify this field, then the container's ENTRYPOINT 
runs, in conjunction with the  args 
 
field or the container's  CMD 
 
, if either exists. If this field is not specified and the container does not have an ENTRYPOINT 
, then refer to the Docker documentation about how CMD 
and ENTRYPOINT 
interact 
.
If you specify this field, then you can also specify the args 
field to provide additional arguments for this command. However, if you specify this field, then the container's CMD 
is ignored. See the Kubernetes documentation about how the command 
and args 
fields interact with a container's ENTRYPOINT 
and CMD 
 
.
In this field, you can reference environment variables set by Vertex AI 
and environment variables set in the  env 
 
field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax:
 $( VARIABLE_NAME 
) 
Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with $$ 
; for example:
 $$( VARIABLE_NAME 
) 
This field corresponds to the command 
field of the Kubernetes Containers v1 core API 
.
args[] 
 
  string 
 
Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's  CMD 
 
. Specify this field as an array of executable and arguments, similar to a Docker CMD 
's "default parameters" form.
If you don't specify this field but do specify the  command 
 
field, then the command from the command 
field runs without any additional arguments. See the Kubernetes documentation about how the command 
and args 
fields interact with a container's ENTRYPOINT 
and CMD 
 
.
If you don't specify this field and don't specify the command 
field, then the container's  ENTRYPOINT 
 
and CMD 
determine what runs based on their default behavior. See the Docker documentation about how CMD 
and ENTRYPOINT 
interact 
.
In this field, you can reference environment variables set by Vertex AI 
and environment variables set in the  env 
 
field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax:
 $( VARIABLE_NAME 
) 
Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with $$ 
; for example:
 $$( VARIABLE_NAME 
) 
This field corresponds to the args 
field of the Kubernetes Containers v1 core API 
.
env[] 
 
  object (  EnvVar 
 
) 
 
Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables.
Additionally, the  command 
 
and  args 
 
fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable VAR_2 
to have the value foo bar 
:
 [
  {
    "name": "VAR_1",
    "value": "foo"
  },
  {
    "name": "VAR_2",
    "value": "$(VAR_1) bar"
  }
] 
 
If you switch the order of the variables in the example, then the expansion does not occur.
This field corresponds to the env 
field of the Kubernetes Containers v1 core API 
.
ports[] 
 
  object (  Port 
 
) 
 
Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port.
If you do not specify this field, it defaults to following value:
 [
  {
    "containerPort": 8080
  }
] 
 
Vertex AI does not use ports other than the first one listed. This field corresponds to the ports 
field of the Kubernetes Containers v1 core API 
.
predictRoute 
 
  string 
 
Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using  projects.locations.endpoints.predict 
 
to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response.
For example, if you set this field to /foo 
, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the /foo 
path on the port of your container specified by the first value of this ModelContainerSpec 
's  ports 
 
field.
If you don't specify this field, it defaults to the following value when you  deploy this Model to an Endpoint 
 
:
 /v1/endpoints/ ENDPOINT 
/deployedModels/ DEPLOYED_MODEL 
:predict 
The placeholders in this value are replaced as follows:
-  ENDPOINT : The last segment (following endpoints/)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as theAIP_ENDPOINT_IDenvironment variable .)
-  DEPLOYED_MODEL : DeployedModel.idof theDeployedModel. (Vertex AI makes this value available to your container code as theAIP_DEPLOYED_MODEL_IDenvironment variable .)
healthRoute 
 
  string 
 
Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about health checks .
For example, if you set this field to /bar 
, then Vertex AI intermittently sends a GET request to the /bar 
path on the port of your container specified by the first value of this ModelContainerSpec 
's  ports 
 
field.
If you don't specify this field, it defaults to the following value when you  deploy this Model to an Endpoint 
 
:
 /v1/endpoints/ ENDPOINT 
/deployedModels/ DEPLOYED_MODEL 
:predict 
The placeholders in this value are replaced as follows:
-  ENDPOINT : The last segment (following endpoints/)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as theAIP_ENDPOINT_IDenvironment variable .)
-  DEPLOYED_MODEL : DeployedModel.idof theDeployedModel. (Vertex AI makes this value available to your container code as theAIP_DEPLOYED_MODEL_IDenvironment variable .)
invokeRoutePrefix 
 
  string 
 
Immutable. Invoke route prefix for the custom container. "/*" is the only supported value right now. By setting this field, any non-root route on this model will be accessible with invoke http call eg: "/invoke/foo/bar", however the [PredictionService.Invoke] RPC is not supported yet.
Only one of predictRoute 
or invokeRoutePrefix 
can be set, and we default to using predictRoute 
if this field is not set. If this field is set, the Model can only be deployed to dedicated endpoint.
grpcPorts[] 
 
  object (  Port 
 
) 
 
Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port.
If you do not specify this field, gRPC requests to the container will be disabled.
Vertex AI does not use ports other than the first one listed. This field corresponds to the ports 
field of the Kubernetes Containers v1 core API.
deploymentTimeout 
 
  string (  Duration 
 
format) 
 
Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.
A duration in seconds with up to nine fractional digits, ending with ' s 
'. Example: "3.5s" 
.
startupProbe 
 
  object (  Probe 
 
) 
 
Immutable. Specification for Kubernetes startup probe.
healthProbe 
 
  object (  Probe 
 
) 
 
Immutable. Specification for Kubernetes readiness probe.
livenessProbe 
 
  object (  Probe 
 
) 
 
Immutable. Specification for Kubernetes liveness probe.
| JSON representation | 
|---|
| { "imageUri" : string , "command" : [ string ] , "args" : [ string ] , "env" : [ { object ( | 
Port
Represents a network port in a container.
containerPort 
 
  integer 
 
The number of the port to expose on the pod's IP address. Must be a valid port number, between 1 and 65535 inclusive.
| JSON representation | 
|---|
| { "containerPort" : integer } | 
Probe
Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.
periodSeconds 
 
  integer 
 
How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. Must be less than timeoutSeconds.
Maps to Kubernetes probe argument 'periodSeconds'.
timeoutSeconds 
 
  integer 
 
Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. Must be greater or equal to periodSeconds.
Maps to Kubernetes probe argument 'timeoutSeconds'.
failureThreshold 
 
  integer 
 
Number of consecutive failures before the probe is considered failed. Defaults to 3. Minimum value is 1.
Maps to Kubernetes probe argument 'failureThreshold'.
successThreshold 
 
  integer 
 
Number of consecutive successes before the probe is considered successful. Defaults to 1. Minimum value is 1.
Maps to Kubernetes probe argument 'successThreshold'.
initialDelaySeconds 
 
  integer 
 
Number of seconds to wait before starting the probe. Defaults to 0. Minimum value is 0.
Maps to Kubernetes probe argument 'initialDelaySeconds'.
probe_type 
 
  Union type 
 
 probe_type 
can be only one of the following:exec 
 
  object (  ExecAction 
 
) 
 
ExecAction probes the health of a container by executing a command.
httpGet 
 
  object (  HttpGetAction 
 
) 
 
HttpGetAction probes the health of a container by sending an HTTP GET request.
grpc 
 
  object (  GrpcAction 
 
) 
 
GrpcAction probes the health of a container by sending a gRPC request.
tcpSocket 
 
  object (  TcpSocketAction 
 
) 
 
TcpSocketAction probes the health of a container by opening a TCP socket connection.
| JSON representation | 
|---|
| { "periodSeconds" : integer , "timeoutSeconds" : integer , "failureThreshold" : integer , "successThreshold" : integer , "initialDelaySeconds" : integer , // probe_type "exec" : { object ( | 
ExecAction
ExecAction specifies a command to execute.
command[] 
 
  string 
 
Command is the command line to execute inside the container, the working directory for the command is root ('/') in the container's filesystem. The command is simply exec'd, it is not run inside a shell, so traditional shell instructions ('|', etc) won't work. To use a shell, you need to explicitly call out to that shell. Exit status of 0 is treated as live/healthy and non-zero is unhealthy.
| JSON representation | 
|---|
| { "command" : [ string ] } | 
HttpGetAction
HttpGetAction describes an action based on HTTP Get requests.
path 
 
  string 
 
Path to access on the HTTP server.
port 
 
  integer 
 
Number of the port to access on the container. Number must be in the range 1 to 65535.
host 
 
  string 
 
host name to connect to, defaults to the model serving container's IP. You probably want to set "host" in httpHeaders instead.
scheme 
 
  string 
 
Scheme to use for connecting to the host. Defaults to HTTP. Acceptable values are "HTTP" or "HTTPS".
httpHeaders[] 
 
  object (  HttpHeader 
 
) 
 
Custom headers to set in the request. HTTP allows repeated headers.
| JSON representation | 
|---|
|  { 
 "path" 
 : 
 string 
 , 
 "port" 
 : 
 integer 
 , 
 "host" 
 : 
 string 
 , 
 "scheme" 
 : 
 string 
 , 
 "httpHeaders" 
 : 
 [ 
 { 
 object (  | 
HttpHeader
HttpHeader describes a custom header to be used in HTTP probes
name 
 
  string 
 
The header field name. This will be canonicalized upon output, so case-variant names will be understood as the same header.
value 
 
  string 
 
The header field value
| JSON representation | 
|---|
| { "name" : string , "value" : string } | 
GrpcAction
GrpcAction checks the health of a container using a gRPC service.
port 
 
  integer 
 
Port number of the gRPC service. Number must be in the range 1 to 65535.
service 
 
  string 
 
service is the name of the service to place in the gRPC HealthCheckRequest. See https://github.com/grpc/grpc/blob/master/doc/health-checking.md .
If this is not specified, the default behavior is defined by gRPC.
| JSON representation | 
|---|
| { "port" : integer , "service" : string } | 
TcpSocketAction
TcpSocketAction probes the health of a container by opening a TCP socket connection.
port 
 
  integer 
 
Number of the port to access on the container. Number must be in the range 1 to 65535.
host 
 
  string 
 
Optional: host name to connect to, defaults to the model serving container's IP.
| JSON representation | 
|---|
| { "port" : integer , "host" : string } | 

