Support private registry in PAI, Kubeflow and FrameworkController mode (#1354)

docs/en_US/TrainingService/KubeflowMode.md

@@ -198,6 +198,8 @@ Trial configuration in kubeflow mode have the following configuration keys:
   * image
     * Required key. In kubeflow mode, your trial program will be scheduled by Kubernetes to run in [Pod](https://kubernetes.io/docs/concepts/workloads/pods/pod/). This key is used to specify the Docker image used to create the pod where your trail program will run.
     * We already build a docker image [msranni/nni](https://hub.docker.com/r/msranni/nni/) on [Docker Hub](https://hub.docker.com/). It contains NNI python packages, Node modules and javascript artifact files required to start experiment, and all of NNI dependencies. The docker file used to build this image can be found at [here](https://github.com/Microsoft/nni/tree/master/deployment/docker/Dockerfile). You can either use this image directly in your config file, or build your own image based on it.
+  * privateRegistryAuthPath
+    * Optional field, specify `config.json` file path that holds an authorization token of docker registry, used to pull image from private registry. [Refer](https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/).
   * apiVersion
     * Required key. The API version of your Kubeflow.
 * ps (optional). This config section is used to configure Tensorflow parameter server role.

docs/en_US/TrainingService/PaiMode.md

@@ -53,6 +53,8 @@ Compared with [LocalMode](LocalMode.md) and [RemoteMachineMode](RemoteMachineMod
     * Optional key. Set the virtualCluster of OpenPAI. If omitted, the job will run on default virtual cluster.
 * shmMB
     * Optional key. Set the shmMB configuration of OpenPAI, it set the shared memory for one task in the task role.
+* authFile
+    * Optional key, Set the auth file path for private registry while using PAI mode, [Refer](https://github.com/microsoft/pai/blob/2ea69b45faa018662bc164ed7733f6fdbb4c42b3/docs/faq.md#q-how-to-use-private-docker-registry-job-image-when-submitting-an-openpai-job).
 
 Once complete to fill NNI experiment config file and save (for example, save as exp_pai.yml), then run the following command
 ```

src/nni_manager/rest_server/restValidationSchemas.ts

@@ -51,10 +51,12 @@ export namespace ValidationSchemas {
                 command: joi.string().min(1),
                 virtualCluster: joi.string(),
                 shmMB: joi.number(),
+                authFile: joi.string(),
                 nasMode: joi.string().valid('classic_mode', 'enas_mode', 'oneshot_mode'),
                 worker: joi.object({
                     replicas: joi.number().min(1).required(),
                     image: joi.string().min(1),
+                    privateRegistryAuthPath: joi.string().min(1),
                     outputDir: joi.string(),
                     cpuNum: joi.number().min(1),
                     memoryMB: joi.number().min(100),
@@ -64,6 +66,7 @@ export namespace ValidationSchemas {
                 ps: joi.object({
                         replicas: joi.number().min(1).required(),
                         image: joi.string().min(1),
+                        privateRegistryAuthPath: joi.string().min(1),
                         outputDir: joi.string(),
                         cpuNum: joi.number().min(1),
                         memoryMB: joi.number().min(100),
@@ -73,6 +76,7 @@ export namespace ValidationSchemas {
                 master: joi.object({
                     replicas: joi.number().min(1).required(),
                     image: joi.string().min(1),
+                    privateRegistryAuthPath: joi.string().min(1),
                     outputDir: joi.string(),
                     cpuNum: joi.number().min(1),
                     memoryMB: joi.number().min(100),
@@ -83,6 +87,7 @@ export namespace ValidationSchemas {
                     name: joi.string().min(1),
                     taskNum: joi.number().min(1).required(),
                     image: joi.string().min(1),
+                    privateRegistryAuthPath: joi.string().min(1),
                     outputDir: joi.string(),
                     cpuNum: joi.number().min(1),
                     memoryMB: joi.number().min(100),

src/nni_manager/training_service/kubernetes/frameworkcontroller/frameworkcontrollerConfig.ts

@@ -43,8 +43,8 @@ export class FrameworkControllerTrialConfigTemplate extends KubernetesTrialConfi
     public readonly taskNum: number;
     constructor(taskNum: number, command : string, gpuNum : number,
                 cpuNum: number, memoryMB: number, image: string,
-                frameworkAttemptCompletionPolicy: FrameworkAttemptCompletionPolicy) {
-        super(command, gpuNum, cpuNum, memoryMB, image);
+                frameworkAttemptCompletionPolicy: FrameworkAttemptCompletionPolicy, privateRegistryFilePath?: string | undefined) {
+        super(command, gpuNum, cpuNum, memoryMB, image, privateRegistryFilePath);
         this.frameworkAttemptCompletionPolicy = frameworkAttemptCompletionPolicy;
         this.name = name;
         this.taskNum = taskNum;

src/nni_manager/training_service/kubernetes/frameworkcontroller/frameworkcontrollerTrainingService.ts

@@ -305,7 +305,7 @@ class FrameworkControllerTrainingService extends KubernetesTrainingService imple
         }
         // Generate frameworkcontroller job resource config object
         const frameworkcontrollerJobConfig: any =
-          this.generateFrameworkControllerJobConfig(trialJobId, trialWorkingFolder, frameworkcontrollerJobName, podResources);
+          await this.generateFrameworkControllerJobConfig(trialJobId, trialWorkingFolder, frameworkcontrollerJobName, podResources);
 
         return Promise.resolve(frameworkcontrollerJobConfig);
     }
@@ -329,8 +329,8 @@ class FrameworkControllerTrainingService extends KubernetesTrainingService imple
      * @param frameworkcontrollerJobName job name
      * @param podResources  pod template
      */
-    private generateFrameworkControllerJobConfig(trialJobId: string, trialWorkingFolder: string,
-                                                 frameworkcontrollerJobName : string, podResources : any) : any {
+    private async generateFrameworkControllerJobConfig(trialJobId: string, trialWorkingFolder: string,
+                                                 frameworkcontrollerJobName : string, podResources : any) : Promise<any> {
         if (this.fcClusterConfig === undefined) {
             throw new Error('frameworkcontroller Cluster config is not initialized');
         }
@@ -345,12 +345,14 @@ class FrameworkControllerTrainingService extends KubernetesTrainingService imple
             if (containerPort === undefined) {
                 throw new Error('Container port is not initialized');
             }
+            
             const taskRole: any = this.generateTaskRoleConfig(
                 trialWorkingFolder,
                 this.fcTrialConfig.taskRoles[index].image,
                 `run_${this.fcTrialConfig.taskRoles[index].name}.sh`,
                 podResources[index],
-                containerPort
+                containerPort,
+                await this.createRegistrySecret(this.fcTrialConfig.taskRoles[index].privateRegistryAuthPath)
             );
             taskRoles.push({
                 name: this.fcTrialConfig.taskRoles[index].name,
@@ -363,7 +365,7 @@ class FrameworkControllerTrainingService extends KubernetesTrainingService imple
             });
         }
 
-        return {
+        return Promise.resolve({
             apiVersion: `frameworkcontroller.microsoft.com/v1`,
             kind: 'Framework',
             metadata: {
@@ -379,11 +381,11 @@ class FrameworkControllerTrainingService extends KubernetesTrainingService imple
                 executionType: 'Start',
                 taskRoles: taskRoles
             }
-        };
+        });
     }
 
-    private generateTaskRoleConfig(trialWorkingFolder: string, replicaImage: string, runScriptFile: string,
-                                   podResources: any, containerPort: number): any {
+    private  generateTaskRoleConfig(trialWorkingFolder: string, replicaImage: string, runScriptFile: string,
+                                   podResources: any, containerPort: number, privateRegistrySecretName: string | undefined): any {
         if (this.fcClusterConfig === undefined) {
             throw new Error('frameworkcontroller Cluster config is not initialized');
         }
@@ -451,13 +453,22 @@ class FrameworkControllerTrainingService extends KubernetesTrainingService imple
                     mountPath: '/mnt/frameworkbarrier'
                 }]
         }];
-        const spec: any = {
-                containers: containers,
-                initContainers: initContainers,
-                restartPolicy: 'OnFailure',
-                volumes: volumeSpecMap.get('nniVolumes'),
-                hostNetwork: false
+        
+        let spec: any = {
+            containers: containers,
+            initContainers: initContainers,
+            restartPolicy: 'OnFailure',
+            volumes: volumeSpecMap.get('nniVolumes'),
+            hostNetwork: false
         };
+        if(privateRegistrySecretName) {
+            spec.imagePullSecrets = [
+                {
+                    name: privateRegistrySecretName 
+                }
+             ]
+        }
+
         if (this.fcClusterConfig.serviceAccountName !== undefined) {
             spec.serviceAccountName = this.fcClusterConfig.serviceAccountName;
         }

src/nni_manager/training_service/kubernetes/kubeflow/kubeflowConfig.ts

@@ -135,8 +135,8 @@ export class KubeflowTrialConfig extends KubernetesTrialConfig {
 export class KubeflowTrialConfigTemplate extends KubernetesTrialConfigTemplate {
     public readonly replicas: number;
     constructor(replicas: number, command : string, gpuNum : number,
-                cpuNum: number, memoryMB: number, image: string) {
-        super(command, gpuNum, cpuNum, memoryMB, image);
+                cpuNum: number, memoryMB: number, image: string, privateRegistryAuthPath?: string) {
+        super(command, gpuNum, cpuNum, memoryMB, image, privateRegistryAuthPath);
         this.replicas = replicas;
     }
 }

src/nni_manager/training_service/kubernetes/kubeflow/kubeflowTrainingService.ts

@@ -347,7 +347,7 @@ class KubeflowTrainingService extends KubernetesTrainingService implements Kuber
         }
 
         // Generate kubeflow job resource config object
-        const kubeflowJobConfig: any = this.generateKubeflowJobConfig(trialJobId, trialWorkingFolder, kubeflowJobName, workerPodResources,
+        const kubeflowJobConfig: any = await this.generateKubeflowJobConfig(trialJobId, trialWorkingFolder, kubeflowJobName, workerPodResources,
                                                                       nonWorkerResources);
 
         return Promise.resolve(kubeflowJobConfig);
@@ -361,8 +361,8 @@ class KubeflowTrainingService extends KubernetesTrainingService implements Kuber
      * @param workerPodResources worker pod template
      * @param nonWorkerPodResources non-worker pod template, like ps or master
      */
-    private generateKubeflowJobConfig(trialJobId: string, trialWorkingFolder: string, kubeflowJobName : string, workerPodResources : any,
-                                      nonWorkerPodResources?: any) : any {
+    private async generateKubeflowJobConfig(trialJobId: string, trialWorkingFolder: string, kubeflowJobName : string, workerPodResources : any,
+                                            nonWorkerPodResources?: any) : Promise<any> {
         if (this.kubeflowClusterConfig === undefined) {
             throw new Error('Kubeflow Cluster config is not initialized');
         }
@@ -377,29 +377,32 @@ class KubeflowTrainingService extends KubernetesTrainingService implements Kuber
 
         const replicaSpecsObj: any = {};
         const replicaSpecsObjMap: Map<string, object> = new Map<string, object>();
-
         if (this.kubeflowTrialConfig.operatorType === 'tf-operator') {
             const tensorflowTrialConfig: KubeflowTrialConfigTensorflow = <KubeflowTrialConfigTensorflow>this.kubeflowTrialConfig;
+            let privateRegistrySecretName = await this.createRegistrySecret(tensorflowTrialConfig.worker.privateRegistryAuthPath);
             replicaSpecsObj.Worker = this.generateReplicaConfig(trialWorkingFolder, tensorflowTrialConfig.worker.replicas,
-                                                                tensorflowTrialConfig.worker.image, 'run_worker.sh', workerPodResources);
+                                                                tensorflowTrialConfig.worker.image, 'run_worker.sh', workerPodResources, privateRegistrySecretName);
             if (tensorflowTrialConfig.ps !== undefined) {
+                let privateRegistrySecretName: string | undefined = await this.createRegistrySecret(tensorflowTrialConfig.ps.privateRegistryAuthPath);
                 replicaSpecsObj.Ps = this.generateReplicaConfig(trialWorkingFolder, tensorflowTrialConfig.ps.replicas,
-                                                                tensorflowTrialConfig.ps.image, 'run_ps.sh', nonWorkerPodResources);
+                                                                tensorflowTrialConfig.ps.image, 'run_ps.sh', nonWorkerPodResources, privateRegistrySecretName);
             }
             replicaSpecsObjMap.set(this.kubernetesCRDClient.jobKind, {tfReplicaSpecs: replicaSpecsObj});
         } else if (this.kubeflowTrialConfig.operatorType === 'pytorch-operator') {
             const pytorchTrialConfig: KubeflowTrialConfigPytorch = <KubeflowTrialConfigPytorch>this.kubeflowTrialConfig;
             if (pytorchTrialConfig.worker !== undefined) {
+                let privateRegistrySecretName: string | undefined = await this.createRegistrySecret(pytorchTrialConfig.worker.privateRegistryAuthPath);
                 replicaSpecsObj.Worker = this.generateReplicaConfig(trialWorkingFolder, pytorchTrialConfig.worker.replicas,
-                                                                    pytorchTrialConfig.worker.image, 'run_worker.sh', workerPodResources);
+                                                                    pytorchTrialConfig.worker.image, 'run_worker.sh', workerPodResources, privateRegistrySecretName);
             }
+            let privateRegistrySecretName: string | undefined = await this.createRegistrySecret(pytorchTrialConfig.master.privateRegistryAuthPath);
             replicaSpecsObj.Master = this.generateReplicaConfig(trialWorkingFolder, pytorchTrialConfig.master.replicas,
-                                                                pytorchTrialConfig.master.image, 'run_master.sh', nonWorkerPodResources);
+                                                                pytorchTrialConfig.master.image, 'run_master.sh', nonWorkerPodResources, privateRegistrySecretName);
 
             replicaSpecsObjMap.set(this.kubernetesCRDClient.jobKind, {pytorchReplicaSpecs: replicaSpecsObj});
         }
 
-        return {
+        return Promise.resolve({
             apiVersion: `kubeflow.org/${this.kubernetesCRDClient.apiVersion}`,
             kind: this.kubernetesCRDClient.jobKind,
             metadata: {
@@ -412,7 +415,7 @@ class KubeflowTrainingService extends KubernetesTrainingService implements Kuber
                 }
             },
             spec: replicaSpecsObjMap.get(this.kubernetesCRDClient.jobKind)
-        };
+        });
     }
 
     /**
@@ -424,7 +427,7 @@ class KubeflowTrainingService extends KubernetesTrainingService implements Kuber
      * @param podResources pod resource config section
      */
     private generateReplicaConfig(trialWorkingFolder: string, replicaNumber: number, replicaImage: string, runScriptFile: string,
-                                  podResources: any): any {
+                                  podResources: any, privateRegistrySecretName: string | undefined): any {
         if (this.kubeflowClusterConfig === undefined) {
             throw new Error('Kubeflow Cluster config is not initialized');
         }
@@ -436,7 +439,7 @@ class KubeflowTrainingService extends KubernetesTrainingService implements Kuber
         if (this.kubernetesCRDClient === undefined) {
             throw new Error('Kubeflow operator client is not initialized');
         }
-
+        // The config spec for volume field
         const volumeSpecMap: Map<string, object> = new Map<string, object>();
         if (this.kubeflowClusterConfig.storageType === 'azureStorage') {
             volumeSpecMap.set('nniVolumes', [
@@ -459,7 +462,34 @@ class KubeflowTrainingService extends KubernetesTrainingService implements Kuber
                 }
             }]);
         }
-
+        // The config spec for container field
+        const containersSpecMap: Map<string, object> = new Map<string, object>(); 
+        containersSpecMap.set('containers', [
+        {
+                // Kubeflow tensorflow operator requires that containers' name must be tensorflow
+                // TODO: change the name based on operator's type
+                name: this.kubernetesCRDClient.containerName,
+                image: replicaImage,
+                args: ['sh', `${path.join(trialWorkingFolder, runScriptFile)}`],
+                volumeMounts: [
+                {
+                    name: 'nni-vol',
+                    mountPath: this.CONTAINER_MOUNT_PATH
+                }],
+                resources: podResources
+            }
+        ]);
+        let spec: any = {
+            containers: containersSpecMap.get('containers'),
+            restartPolicy: 'ExitCode',
+            volumes: volumeSpecMap.get('nniVolumes')
+        }
+        if (privateRegistrySecretName) {
+            spec.imagePullSecrets = [
+                {
+                    name: privateRegistrySecretName
+                }]
+        }
         return {
             replicas: replicaNumber,
             template: {
@@ -467,26 +497,9 @@ class KubeflowTrainingService extends KubernetesTrainingService implements Kuber
                     // tslint:disable-next-line:no-null-keyword
                     creationTimestamp: null
                 },
-                spec: {
-                    containers: [
-                    {
-                        // Kubeflow tensorflow operator requires that containers' name must be tensorflow
-                        // TODO: change the name based on operator's type
-                        name: this.kubernetesCRDClient.containerName,
-                        image: replicaImage,
-                        args: ['sh', `${path.join(trialWorkingFolder, runScriptFile)}`],
-                        volumeMounts: [
-                        {
-                            name: 'nni-vol',
-                            mountPath: this.CONTAINER_MOUNT_PATH
-                        }],
-                        resources: podResources
-                    }],
-                    restartPolicy: 'ExitCode',
-                    volumes: volumeSpecMap.get('nniVolumes')
-                }
+                spec: spec
             }
-        };
+        }
     }
 }
 // tslint:enable: no-unsafe-any no-any

src/nni_manager/training_service/kubernetes/kubernetesConfig.ts

@@ -179,6 +179,9 @@ export class KubernetesTrialConfigTemplate {
     // Docker image
     public readonly image: string;
 
+    // Private registry config file path to download docker iamge
+    public readonly privateRegistryAuthPath?: string;
+
     // Trail command
     public readonly command : string;
 
@@ -186,12 +189,13 @@ export class KubernetesTrialConfigTemplate {
     public readonly gpuNum : number;
 
     constructor(command : string, gpuNum : number,
-                cpuNum: number, memoryMB: number, image: string) {
+                cpuNum: number, memoryMB: number, image: string, privateRegistryAuthPath?: string) {
         this.command = command;
         this.gpuNum = gpuNum;
         this.cpuNum = cpuNum;
         this.memoryMB = memoryMB;
         this.image = image;
+        this.privateRegistryAuthPath = privateRegistryAuthPath;
     }
 }
 

src/nni_manager/training_service/kubernetes/kubernetesTrainingService.ts

@@ -38,6 +38,8 @@ import { KubernetesClusterConfig } from './kubernetesConfig';
 import { kubernetesScriptFormat, KubernetesTrialJobDetail } from './kubernetesData';
 import { KubernetesJobRestServer } from './kubernetesJobRestServer';
 
+var fs = require('fs');
+
 /**
  * Training Service implementation for Kubernetes
  */
@@ -327,5 +329,34 @@ abstract class KubernetesTrainingService {
 
         return Promise.resolve();
     }
+
+    protected async createRegistrySecret(filePath: string | undefined): Promise<string | undefined> {
+        if(filePath === undefined || filePath === '') {
+            return undefined;
+        }
+        let body = fs.readFileSync(filePath).toString('base64');
+        let registrySecretName = String.Format('nni-secret-{0}', uniqueString(8)
+                                                                            .toLowerCase());
+        await this.genericK8sClient.createSecret(
+            {
+                apiVersion: 'v1',
+                kind: 'Secret',
+                metadata: {
+                    name: registrySecretName,
+                    namespace: 'default',
+                    labels: {
+                        app: this.NNI_KUBERNETES_TRIAL_LABEL,
+                        expId: getExperimentId()
+                    }
+                },
+                type: 'kubernetes.io/dockerconfigjson',
+                data: {
+                    '.dockerconfigjson': body
+                }
+            }
+        );
+        return registrySecretName;
+    }
+     
 }
 export { KubernetesTrainingService };

src/nni_manager/training_service/pai/paiConfig.ts

@@ -71,6 +71,8 @@ export class PAIJobConfig {
     public readonly image: string;
     // Code directory on HDFS
     public readonly codeDir: string;
+    //authentication file used for private Docker registry 
+    public readonly authFile?: string;
 
     // List of taskRole, one task role at least
     public taskRoles: PAITaskRole[];
@@ -87,12 +89,13 @@ export class PAIJobConfig {
      * @param taskRoles List of taskRole, one task role at least
      */
     constructor(jobName: string, image : string, codeDir : string,
-                taskRoles : PAITaskRole[], virtualCluster: string) {
+                taskRoles : PAITaskRole[], virtualCluster: string, authFile?: string) {
         this.jobName = jobName;
         this.image = image;
         this.codeDir = codeDir;
         this.taskRoles = taskRoles;
         this.virtualCluster = virtualCluster;
+        this.authFile = authFile;
     }
 }
 
@@ -129,14 +132,17 @@ export class NNIPAITrialConfig extends TrialConfig {
     public virtualCluster?: string;
     //Shared memory for one task in the task role
     public shmMB?: number;
+    //authentication file used for private Docker registry 
+    public authFile?: string;
 
     constructor(command : string, codeDir : string, gpuNum : number, cpuNum: number, memoryMB: number,
-                image: string, virtualCluster?: string, shmMB?: number) {
+                image: string, virtualCluster?: string, shmMB?: number, authFile?: string) {
         super(command, codeDir, gpuNum);
         this.cpuNum = cpuNum;
         this.memoryMB = memoryMB;
         this.image = image;
         this.virtualCluster = virtualCluster;
         this.shmMB = shmMB;
+        this.authFile = authFile;
     }
 }

src/nni_manager/training_service/pai/paiTrainingService.ts

@@ -442,7 +442,7 @@ class PAITrainingService implements TrainingService {
                 // Task command
                 nniPaiTrialCommand,
                 // Task shared memory
-                this.paiTrialConfig.shmMB
+                this.paiTrialConfig.shmMB,
             )
         ];
 
@@ -456,7 +456,9 @@ class PAITrainingService implements TrainingService {
             // PAI Task roles
             paiTaskRoles,
             // Add Virutal Cluster
-            this.paiTrialConfig.virtualCluster === undefined ? 'default' : this.paiTrialConfig.virtualCluster.toString()
+            this.paiTrialConfig.virtualCluster === undefined ? 'default' : this.paiTrialConfig.virtualCluster.toString(),
+            //Task auth File
+            this.paiTrialConfig.authFile
         );
 
         // Step 2. Upload code files in codeDir onto HDFS

tools/nni_cmd/config_schema.py

@@ -233,6 +233,8 @@ pai_trial_schema = {
     'cpuNum': setNumberRange('cpuNum', int, 0, 99999),
     'memoryMB': setType('memoryMB', int),
     'image': setType('image', str),
+    Optional('authFile'): And(Regex(r'hdfs://(([0-9]{1,3}.){3}[0-9]{1,3})(:[0-9]{2,5})?(/.*)?'),\
+                         error='ERROR: authFile format error, authFile format is hdfs://xxx.xxx.xxx.xxx:xxx'),
     Optional('shmMB'): setType('shmMB', int),
     Optional('dataDir'): And(Regex(r'hdfs://(([0-9]{1,3}.){3}[0-9]{1,3})(:[0-9]{2,5})?(/.*)?'),\
                          error='ERROR: dataDir format error, dataDir format is hdfs://xxx.xxx.xxx.xxx:xxx'),
@@ -261,7 +263,8 @@ kubeflow_trial_schema = {
             'gpuNum': setNumberRange('gpuNum', int, 0, 99999),
             'cpuNum': setNumberRange('cpuNum', int, 0, 99999),
             'memoryMB': setType('memoryMB', int),
-            'image': setType('image', str)
+            'image': setType('image', str),
+            Optional('privateRegistryAuthPath'): And(os.path.exists, error=SCHEMA_PATH_ERROR % 'privateRegistryAuthPath')
         },
         Optional('master'): {
             'replicas': setType('replicas', int),
@@ -269,7 +272,8 @@ kubeflow_trial_schema = {
             'gpuNum': setNumberRange('gpuNum', int, 0, 99999),
             'cpuNum': setNumberRange('cpuNum', int, 0, 99999),
             'memoryMB': setType('memoryMB', int),
-            'image': setType('image', str)
+            'image': setType('image', str),
+            Optional('privateRegistryAuthPath'): And(os.path.exists, error=SCHEMA_PATH_ERROR % 'privateRegistryAuthPath')
         },
         Optional('worker'):{
             'replicas': setType('replicas', int),
@@ -277,7 +281,8 @@ kubeflow_trial_schema = {
             'gpuNum': setNumberRange('gpuNum', int, 0, 99999),
             'cpuNum': setNumberRange('cpuNum', int, 0, 99999),
             'memoryMB': setType('memoryMB', int),
-            'image': setType('image', str)
+            'image': setType('image', str),
+            Optional('privateRegistryAuthPath'): And(os.path.exists, error=SCHEMA_PATH_ERROR % 'privateRegistryAuthPath')
         }
     }
 }
@@ -324,7 +329,8 @@ frameworkcontroller_trial_schema = {
             'gpuNum': setNumberRange('gpuNum', int, 0, 99999),
             'cpuNum': setNumberRange('cpuNum', int, 0, 99999),
             'memoryMB': setType('memoryMB', int),
-            'image': setType('image', str)
+            'image': setType('image', str),
+            Optional('privateRegistryAuthPath'): And(os.path.exists, error=SCHEMA_PATH_ERROR % 'privateRegistryAuthPath')
         }]
     }
 }