A SeldonDeployment is defined as a custom resource definition within Kubernetes.
The Seldon Deployment Custom Resource is defined using Proto Buffers.
syntax = "proto2";
package seldon.protos;
import "k8s.io/apimachinery/pkg/apis/meta/v1/generated.proto";
import "v1.proto";
option java_package = "io.seldon.protos";
option java_outer_classname = "DeploymentProtos";
message SeldonDeployment {
required string apiVersion = 1;
required string kind = 2;
optional k8s.io.apimachinery.pkg.apis.meta.v1.ObjectMeta metadata = 3;
required DeploymentSpec spec = 4;
optional DeploymentStatus status = 5;
}
/**
* Status for seldon deployment
*/
message DeploymentStatus {
optional string state = 1; // A short status value for the deployment.
optional string description = 2; // A longer description describing the current state.
repeated PredictorStatus predictorStatus = 3; // A list of individual statuses for each running predictor.
}
message PredictorStatus {
required string name = 1; // The name of the predictor.
optional string status = 2; // A short status value.
optional string description = 3; // A longer description of the current status.
optional int32 replicas = 4; // The number of replicas requested.
optional int32 replicasAvailable = 5; // The number of replicas available.
}
message DeploymentSpec {
optional string name = 1; // A unique name within the namespace.
repeated PredictorSpec predictors = 2; // A list of 1 or more predictors describing runtime machine learning deployment graphs.
optional string oauth_key = 3; // The oauth key for external users to use this deployment via an API.
optional string oauth_secret = 4; // The oauth secret for external users to use this deployment via an API.
map<string,string> annotations = 5; // Arbitrary annotations.
}
message PredictorSpec {
required string name = 1; // A unique name not used by any other predictor in the deployment.
required PredictiveUnit graph = 2; // A graph describing how the predictive units are connected together.
repeated k8s.io.api.core.v1.PodTemplateSpec componentSpecs = 3; // A description of the set of containers used by the graph. One for each microservice defined in the graph. Can be split over 1 or more PodTemplateSpecs.
optional int32 replicas = 4; // The number of replicas of the predictor to create.
map<string,string> annotations = 5; // Arbitrary annotations.
optional k8s.io.api.core.v1.ResourceRequirements engineResources = 6 [deprecated=true]; // Optional set of resources for the Seldon engine which is added to each Predictor graph to manage the request/response flow
map<string,string> labels = 7; // labels to be attached to entry deplyment for this predictor
optional SvcOrchSpec svcOrchSpec = 8; // Service Orchestrator configuration
}
message SvcOrchSpec {
optional k8s.io.api.core.v1.ResourceRequirements resources = 1;
repeated k8s.io.api.core.v1.EnvVar env = 2;
}
/**
* Represents a unit in a runtime prediction graph that performs a piece of functionality within the prediction request/response calls.
*/
message PredictiveUnit {
/**
* The main type of the predictive unit. Routers decide where requests are sent, e.g. AB Tests and Multi-Armed Bandits. Combiners ensemble responses from their children. Models are leaft nodes in the predictive tree and provide request/reponse functionality encapsulating a machine learning model. Transformers alter the request features.
*/
enum PredictiveUnitType {
// Each one of these defines a default combination of Predictive Unit Methods
UNKNOWN_TYPE = 0;
ROUTER = 1; // Route + send feedback
COMBINER = 2; // Aggregate
MODEL = 3; // Transform input
TRANSFORMER = 4; // Transform input (alias)
OUTPUT_TRANSFORMER = 5; // Transform output
}
enum PredictiveUnitImplementation {
// Each one of these are hardcoded in the engine, no microservice is used
UNKNOWN_IMPLEMENTATION = 0; // No implementation (microservice used)
SIMPLE_MODEL = 1; // An internal model stub for testing.
SIMPLE_ROUTER = 2; // An internal router for testing.
RANDOM_ABTEST = 3; // A A-B test that sends traffic 50% to each child randomly.
AVERAGE_COMBINER = 4; // A default combiner that returns the average of its children responses.
}
enum PredictiveUnitMethod {
TRANSFORM_INPUT = 0;
TRANSFORM_OUTPUT = 1;
ROUTE = 2;
AGGREGATE = 3;
SEND_FEEDBACK = 4;
}
required string name = 1; //must match container name of component if no implementation
repeated PredictiveUnit children = 2; // The child predictive units.
optional PredictiveUnitType type = 3;
optional PredictiveUnitImplementation implementation = 4;
repeated PredictiveUnitMethod methods = 5;
optional Endpoint endpoint = 6; // The exposed endpoint for this unit.
repeated Parameter parameters = 7; // Customer parameter to pass to the unit.
}
message Endpoint {
enum EndpointType {
REST = 0; // REST endpoints with JSON payloads
GRPC = 1; // gRPC endpoints
}
optional string service_host = 1; // Hostname for endpoint.
optional int32 service_port = 2; // The port to connect to the service.
optional EndpointType type = 3; // The protocol handled by the endpoint.
}
message Parameter {
enum ParameterType {
INT = 0;
FLOAT = 1;
DOUBLE = 2;
STRING = 3;
BOOL = 4;
}
required string name = 1;
required string value = 2;
required ParameterType type = 3;
}
- The model is contained in the image
seldonio/mock_classifier:1.0 - The model requests 1 MB of memory
- The model defines oauth key and secret for use with seldon-core's built in API gateway.
- The model supports a REST API
{
"apiVersion": "machinelearning.seldon.io/v1alpha2",
"kind": "SeldonDeployment",
"metadata": {
"labels": {
"app": "seldon"
},
"name": "seldon-deployment-example"
},
"spec": {
"annotations": {
"project_name": "FX Market Prediction",
"deployment_version": "v1"
},
"name": "test-deployment",
"oauth_key": "oauth-key",
"oauth_secret": "oauth-secret",
"predictors": [
{
"componentSpecs": [{
"spec": {
"containers": [
{
"image": "seldonio/mock_classifier:1.0",
"imagePullPolicy": "IfNotPresent",
"name": "classifier",
"resources": {
"requests": {
"memory": "1Mi"
}
}
}
],
"terminationGracePeriodSeconds": 20
}
}],
"graph": {
"children": [],
"name": "classifier",
"endpoint": {
"type" : "REST"
},
"type": "MODEL"
},
"name": "fx-market-predictor",
"replicas": 1,
"annotations": {
"predictor_version" : "v1"
}
}
]
}
}