diff --git a/pkg/globalmanager/controllers/federatedlearning/federatedlearningjob.go b/pkg/globalmanager/controllers/federatedlearning/federatedlearningjob.go
index 28fdf7104..b775b089b 100644
--- a/pkg/globalmanager/controllers/federatedlearning/federatedlearningjob.go
+++ b/pkg/globalmanager/controllers/federatedlearning/federatedlearningjob.go
@@ -424,9 +424,9 @@ func (c *Controller) createPod(job *sednav1.FederatedLearningJob) (active int32,
 	// deliver pod for aggregation worker
 	aggWorker := job.Spec.AggregationWorker
 
-	// Configure container mounting and Env information by initial runtime.WorkerParam
+	// Configure aggregation worker's mounts and envs
 	var aggPort int32 = 7363
-	aggWorkerParam := new(runtime.WorkerParam)
+	var aggWorkerParam runtime.WorkerParam
 	aggWorkerParam.Env = map[string]string{
 		"NAMESPACE":   job.Namespace,
 		"WORKER_NAME": "aggworker-" + utilrand.String(5),
@@ -451,9 +451,9 @@ func (c *Controller) createPod(job *sednav1.FederatedLearningJob) (active int32,
 	)
 
 	// create aggpod based on configured parameters
-	_, err = runtime.CreatePodWithTemplate(c.kubeClient, job, &aggWorker.Template, aggWorkerParam)
+	_, err = runtime.CreatePodWithTemplate(c.kubeClient, job, &aggWorker.Template, &aggWorkerParam)
 	if err != nil {
-		return active, err
+		return active, fmt.Errorf("failed to create aggregation worker: %w", err)
 	}
 	active++
 
@@ -463,13 +463,17 @@ func (c *Controller) createPod(job *sednav1.FederatedLearningJob) (active int32,
 	// FIXME(llhuii): only the case that Spec.NodeName specified is support,
 	// will support Spec.NodeSelector.
 	appIP, err = runtime.GetNodeIPByName(c.kubeClient, job.Spec.AggregationWorker.Template.Spec.NodeName)
+	if err != nil {
+		return active, err
+	}
 
 	aggServicePort, err = runtime.CreateKubernetesService(c.kubeClient, job, jobStageAgg, aggPort, appIP)
 	if err != nil {
 		return active, err
 	}
+
 	// deliver pod for training worker
-	for _, trainingWorker := range job.Spec.TrainingWorkers {
+	for i, trainingWorker := range job.Spec.TrainingWorkers {
 		// get dataseturl through parsing crd of dataset
 		datasetName := trainingWorker.Dataset.Name
 		dataset, err := c.client.Datasets(job.Namespace).Get(ctx, datasetName, metav1.GetOptions{})
@@ -484,9 +488,8 @@ func (c *Controller) createPod(job *sednav1.FederatedLearningJob) (active int32,
 			datasetSecret, _ = c.kubeClient.CoreV1().Secrets(job.Namespace).Get(context.TODO(), secretName, metav1.GetOptions{})
 		}
 
-		// Configure container mounting and env information
-		workerParam := new(runtime.WorkerParam)
-
+		// Configure training worker's mounts and envs
+		var workerParam runtime.WorkerParam
 		workerParam.Mounts = append(workerParam.Mounts,
 			runtime.WorkerMount{
 				URL: &runtime.MountURL{
@@ -520,10 +523,11 @@ func (c *Controller) createPod(job *sednav1.FederatedLearningJob) (active int32,
 		workerParam.WorkerType = runtime.TrainPodType
 		workerParam.HostNetwork = true
 		workerParam.RestartPolicy = v1.RestartPolicyOnFailure
-		// create train pod based on configured parameters
-		_, err = runtime.CreatePodWithTemplate(c.kubeClient, job, &trainingWorker.Template, workerParam)
+
+		// create training worker based on configured parameters
+		_, err = runtime.CreatePodWithTemplate(c.kubeClient, job, &trainingWorker.Template, &workerParam)
 		if err != nil {
-			return active, err
+			return active, fmt.Errorf("failed to create %dth training worker: %w", i, err)
 		}
 		active++
 	}
@@ -554,17 +558,27 @@ func New(cc *runtime.ControllerContext) (runtime.FeatureControllerI, error) {
 	jobInformer.Informer().AddEventHandler(cache.ResourceEventHandlerFuncs{
 		AddFunc: func(obj interface{}) {
 			fc.enqueueController(obj, true)
+
+			// when a federated learning job is added,
+			// send it to edge's LC.
 			fc.syncToEdge(watch.Added, obj)
 		},
 		UpdateFunc: func(old, cur interface{}) {
 			fc.enqueueController(cur, true)
+
+			// when a federated learning job is updated,
+			// send it to edge's LC as Added event.
 			fc.syncToEdge(watch.Added, cur)
 		},
 		DeleteFunc: func(obj interface{}) {
 			fc.enqueueController(obj, true)
+
+			// when a federated learning job is deleted,
+			// send it to edge's LC.
 			fc.syncToEdge(watch.Deleted, obj)
 		},
 	})
+
 	fc.jobLister = jobInformer.Lister()
 	fc.jobStoreSynced = jobInformer.Informer().HasSynced
 
diff --git a/pkg/globalmanager/controllers/incrementallearning/incrementallearningjob.go b/pkg/globalmanager/controllers/incrementallearning/incrementallearningjob.go
index 95432d14b..b7dfb667a 100644
--- a/pkg/globalmanager/controllers/incrementallearning/incrementallearningjob.go
+++ b/pkg/globalmanager/controllers/incrementallearning/incrementallearningjob.go
@@ -619,13 +619,14 @@ func (c *Controller) createPod(job *sednav1.IncrementalLearningJob, podtype sedn
 		originalDataURLOrIndex = dataset.Spec.URL
 	}
 
-	var workerParam *runtime.WorkerParam = new(runtime.WorkerParam)
+	var workerParam runtime.WorkerParam
+
 	if podtype == sednav1.ILJobTrain {
 		workerParam.WorkerType = runtime.TrainPodType
 
 		podTemplate = &job.Spec.TrainSpec.Template
-		// Env parameters for train
 
+		// Env parameters for train
 		workerParam.Env = map[string]string{
 			"NAMESPACE":   job.Namespace,
 			"JOB_NAME":    job.Name,
@@ -688,10 +689,10 @@ func (c *Controller) createPod(job *sednav1.IncrementalLearningJob, podtype sedn
 			},
 		)
 	} else {
+		// Configure eval worker's mounts and envs
 		podTemplate = &job.Spec.EvalSpec.Template
 		workerParam.WorkerType = "Eval"
 
-		// Configure Env information for eval by initial WorkerParam
 		workerParam.Env = map[string]string{
 			"NAMESPACE":   job.Namespace,
 			"JOB_NAME":    job.Name,
@@ -757,7 +758,7 @@ func (c *Controller) createPod(job *sednav1.IncrementalLearningJob, podtype sedn
 	workerParam.HostNetwork = true
 
 	// create pod based on podtype
-	_, err = runtime.CreatePodWithTemplate(c.kubeClient, job, podTemplate, workerParam)
+	_, err = runtime.CreatePodWithTemplate(c.kubeClient, job, podTemplate, &workerParam)
 	return
 }
 
@@ -771,17 +772,16 @@ func (c *Controller) createInferPod(job *sednav1.IncrementalLearningJob) error {
 
 	inferModelURL := inferModel.Spec.URL
 
-	// Env parameters for edge
 	HEMParameterJSON, _ := json.Marshal(job.Spec.DeploySpec.HardExampleMining.Parameters)
 	HEMParameterString := string(HEMParameterJSON)
 
-	// Configure container mounting and Env information by initial runtime.WorkerParam
 	modelSecret, err := c.getSecret(
 		job.Namespace,
 		inferModel.Spec.CredentialName,
 		fmt.Sprintf("model %s", inferModel.Name),
 	)
 
+	// Configure inference worker's mounts and envs
 	var workerParam runtime.WorkerParam
 	workerParam.Mounts = append(workerParam.Mounts,
 		runtime.WorkerMount{
@@ -809,7 +809,7 @@ func (c *Controller) createInferPod(job *sednav1.IncrementalLearningJob) error {
 	workerParam.WorkerType = runtime.InferencePodType
 	workerParam.HostNetwork = true
 
-	// create edge pod
+	// create the inference worker
 	_, err = runtime.CreatePodWithTemplate(c.kubeClient, job, &job.Spec.DeploySpec.Template, &workerParam)
 	return err
 }