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/*
 * Copyright 2019-2024 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 * 
 * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with
 * the License. A copy of the License is located at
 * 
 * http://aws.amazon.com/apache2.0
 * 
 * or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
 * CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
 * and limitations under the License.
 */
package com.amazonaws.services.sagemaker.model;

import java.io.Serializable;
import javax.annotation.Generated;

/**
 * 
 * @see AWS API Documentation
 */
@Generated("com.amazonaws:aws-java-sdk-code-generator")
public class GetScalingConfigurationRecommendationResult extends com.amazonaws.AmazonWebServiceResult implements Serializable,
        Cloneable {

    /**
     * 

* The name of a previously completed Inference Recommender job. *

*/ private String inferenceRecommendationsJobName; /** *

* The recommendation ID of a previously completed inference recommendation. *

*/ private String recommendationId; /** *

* The name of an endpoint benchmarked during a previously completed Inference Recommender job. *

*/ private String endpointName; /** *

* The percentage of how much utilization you want an instance to use before autoscaling, which you specified in the * request. The default value is 50%. *

*/ private Integer targetCpuUtilizationPerCore; /** *

* An object representing the anticipated traffic pattern for an endpoint that you specified in the request. *

*/ private ScalingPolicyObjective scalingPolicyObjective; /** *

* An object with a list of metrics that were benchmarked during the previously completed Inference Recommender job. *

*/ private ScalingPolicyMetric metric; /** *

* An object with the recommended values for you to specify when creating an autoscaling policy. *

*/ private DynamicScalingConfiguration dynamicScalingConfiguration; /** *

* The name of a previously completed Inference Recommender job. *

* * @param inferenceRecommendationsJobName * The name of a previously completed Inference Recommender job. */ public void setInferenceRecommendationsJobName(String inferenceRecommendationsJobName) { this.inferenceRecommendationsJobName = inferenceRecommendationsJobName; } /** *

* The name of a previously completed Inference Recommender job. *

* * @return The name of a previously completed Inference Recommender job. */ public String getInferenceRecommendationsJobName() { return this.inferenceRecommendationsJobName; } /** *

* The name of a previously completed Inference Recommender job. *

* * @param inferenceRecommendationsJobName * The name of a previously completed Inference Recommender job. * @return Returns a reference to this object so that method calls can be chained together. */ public GetScalingConfigurationRecommendationResult withInferenceRecommendationsJobName(String inferenceRecommendationsJobName) { setInferenceRecommendationsJobName(inferenceRecommendationsJobName); return this; } /** *

* The recommendation ID of a previously completed inference recommendation. *

* * @param recommendationId * The recommendation ID of a previously completed inference recommendation. */ public void setRecommendationId(String recommendationId) { this.recommendationId = recommendationId; } /** *

* The recommendation ID of a previously completed inference recommendation. *

* * @return The recommendation ID of a previously completed inference recommendation. */ public String getRecommendationId() { return this.recommendationId; } /** *

* The recommendation ID of a previously completed inference recommendation. *

* * @param recommendationId * The recommendation ID of a previously completed inference recommendation. * @return Returns a reference to this object so that method calls can be chained together. */ public GetScalingConfigurationRecommendationResult withRecommendationId(String recommendationId) { setRecommendationId(recommendationId); return this; } /** *

* The name of an endpoint benchmarked during a previously completed Inference Recommender job. *

* * @param endpointName * The name of an endpoint benchmarked during a previously completed Inference Recommender job. */ public void setEndpointName(String endpointName) { this.endpointName = endpointName; } /** *

* The name of an endpoint benchmarked during a previously completed Inference Recommender job. *

* * @return The name of an endpoint benchmarked during a previously completed Inference Recommender job. */ public String getEndpointName() { return this.endpointName; } /** *

* The name of an endpoint benchmarked during a previously completed Inference Recommender job. *

* * @param endpointName * The name of an endpoint benchmarked during a previously completed Inference Recommender job. * @return Returns a reference to this object so that method calls can be chained together. */ public GetScalingConfigurationRecommendationResult withEndpointName(String endpointName) { setEndpointName(endpointName); return this; } /** *

* The percentage of how much utilization you want an instance to use before autoscaling, which you specified in the * request. The default value is 50%. *

* * @param targetCpuUtilizationPerCore * The percentage of how much utilization you want an instance to use before autoscaling, which you specified * in the request. The default value is 50%. */ public void setTargetCpuUtilizationPerCore(Integer targetCpuUtilizationPerCore) { this.targetCpuUtilizationPerCore = targetCpuUtilizationPerCore; } /** *

* The percentage of how much utilization you want an instance to use before autoscaling, which you specified in the * request. The default value is 50%. *

* * @return The percentage of how much utilization you want an instance to use before autoscaling, which you * specified in the request. The default value is 50%. */ public Integer getTargetCpuUtilizationPerCore() { return this.targetCpuUtilizationPerCore; } /** *

* The percentage of how much utilization you want an instance to use before autoscaling, which you specified in the * request. The default value is 50%. *

* * @param targetCpuUtilizationPerCore * The percentage of how much utilization you want an instance to use before autoscaling, which you specified * in the request. The default value is 50%. * @return Returns a reference to this object so that method calls can be chained together. */ public GetScalingConfigurationRecommendationResult withTargetCpuUtilizationPerCore(Integer targetCpuUtilizationPerCore) { setTargetCpuUtilizationPerCore(targetCpuUtilizationPerCore); return this; } /** *

* An object representing the anticipated traffic pattern for an endpoint that you specified in the request. *

* * @param scalingPolicyObjective * An object representing the anticipated traffic pattern for an endpoint that you specified in the request. */ public void setScalingPolicyObjective(ScalingPolicyObjective scalingPolicyObjective) { this.scalingPolicyObjective = scalingPolicyObjective; } /** *

* An object representing the anticipated traffic pattern for an endpoint that you specified in the request. *

* * @return An object representing the anticipated traffic pattern for an endpoint that you specified in the request. */ public ScalingPolicyObjective getScalingPolicyObjective() { return this.scalingPolicyObjective; } /** *

* An object representing the anticipated traffic pattern for an endpoint that you specified in the request. *

* * @param scalingPolicyObjective * An object representing the anticipated traffic pattern for an endpoint that you specified in the request. * @return Returns a reference to this object so that method calls can be chained together. */ public GetScalingConfigurationRecommendationResult withScalingPolicyObjective(ScalingPolicyObjective scalingPolicyObjective) { setScalingPolicyObjective(scalingPolicyObjective); return this; } /** *

* An object with a list of metrics that were benchmarked during the previously completed Inference Recommender job. *

* * @param metric * An object with a list of metrics that were benchmarked during the previously completed Inference * Recommender job. */ public void setMetric(ScalingPolicyMetric metric) { this.metric = metric; } /** *

* An object with a list of metrics that were benchmarked during the previously completed Inference Recommender job. *

* * @return An object with a list of metrics that were benchmarked during the previously completed Inference * Recommender job. */ public ScalingPolicyMetric getMetric() { return this.metric; } /** *

* An object with a list of metrics that were benchmarked during the previously completed Inference Recommender job. *

* * @param metric * An object with a list of metrics that were benchmarked during the previously completed Inference * Recommender job. * @return Returns a reference to this object so that method calls can be chained together. */ public GetScalingConfigurationRecommendationResult withMetric(ScalingPolicyMetric metric) { setMetric(metric); return this; } /** *

* An object with the recommended values for you to specify when creating an autoscaling policy. *

* * @param dynamicScalingConfiguration * An object with the recommended values for you to specify when creating an autoscaling policy. */ public void setDynamicScalingConfiguration(DynamicScalingConfiguration dynamicScalingConfiguration) { this.dynamicScalingConfiguration = dynamicScalingConfiguration; } /** *

* An object with the recommended values for you to specify when creating an autoscaling policy. *

* * @return An object with the recommended values for you to specify when creating an autoscaling policy. */ public DynamicScalingConfiguration getDynamicScalingConfiguration() { return this.dynamicScalingConfiguration; } /** *

* An object with the recommended values for you to specify when creating an autoscaling policy. *

* * @param dynamicScalingConfiguration * An object with the recommended values for you to specify when creating an autoscaling policy. * @return Returns a reference to this object so that method calls can be chained together. */ public GetScalingConfigurationRecommendationResult withDynamicScalingConfiguration(DynamicScalingConfiguration dynamicScalingConfiguration) { setDynamicScalingConfiguration(dynamicScalingConfiguration); return this; } /** * Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be * redacted from this string using a placeholder value. * * @return A string representation of this object. * * @see java.lang.Object#toString() */ @Override public String toString() { StringBuilder sb = new StringBuilder(); sb.append("{"); if (getInferenceRecommendationsJobName() != null) sb.append("InferenceRecommendationsJobName: ").append(getInferenceRecommendationsJobName()).append(","); if (getRecommendationId() != null) sb.append("RecommendationId: ").append(getRecommendationId()).append(","); if (getEndpointName() != null) sb.append("EndpointName: ").append(getEndpointName()).append(","); if (getTargetCpuUtilizationPerCore() != null) sb.append("TargetCpuUtilizationPerCore: ").append(getTargetCpuUtilizationPerCore()).append(","); if (getScalingPolicyObjective() != null) sb.append("ScalingPolicyObjective: ").append(getScalingPolicyObjective()).append(","); if (getMetric() != null) sb.append("Metric: ").append(getMetric()).append(","); if (getDynamicScalingConfiguration() != null) sb.append("DynamicScalingConfiguration: ").append(getDynamicScalingConfiguration()); sb.append("}"); return sb.toString(); } @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (obj instanceof GetScalingConfigurationRecommendationResult == false) return false; GetScalingConfigurationRecommendationResult other = (GetScalingConfigurationRecommendationResult) obj; if (other.getInferenceRecommendationsJobName() == null ^ this.getInferenceRecommendationsJobName() == null) return false; if (other.getInferenceRecommendationsJobName() != null && other.getInferenceRecommendationsJobName().equals(this.getInferenceRecommendationsJobName()) == false) return false; if (other.getRecommendationId() == null ^ this.getRecommendationId() == null) return false; if (other.getRecommendationId() != null && other.getRecommendationId().equals(this.getRecommendationId()) == false) return false; if (other.getEndpointName() == null ^ this.getEndpointName() == null) return false; if (other.getEndpointName() != null && other.getEndpointName().equals(this.getEndpointName()) == false) return false; if (other.getTargetCpuUtilizationPerCore() == null ^ this.getTargetCpuUtilizationPerCore() == null) return false; if (other.getTargetCpuUtilizationPerCore() != null && other.getTargetCpuUtilizationPerCore().equals(this.getTargetCpuUtilizationPerCore()) == false) return false; if (other.getScalingPolicyObjective() == null ^ this.getScalingPolicyObjective() == null) return false; if (other.getScalingPolicyObjective() != null && other.getScalingPolicyObjective().equals(this.getScalingPolicyObjective()) == false) return false; if (other.getMetric() == null ^ this.getMetric() == null) return false; if (other.getMetric() != null && other.getMetric().equals(this.getMetric()) == false) return false; if (other.getDynamicScalingConfiguration() == null ^ this.getDynamicScalingConfiguration() == null) return false; if (other.getDynamicScalingConfiguration() != null && other.getDynamicScalingConfiguration().equals(this.getDynamicScalingConfiguration()) == false) return false; return true; } @Override public int hashCode() { final int prime = 31; int hashCode = 1; hashCode = prime * hashCode + ((getInferenceRecommendationsJobName() == null) ? 0 : getInferenceRecommendationsJobName().hashCode()); hashCode = prime * hashCode + ((getRecommendationId() == null) ? 0 : getRecommendationId().hashCode()); hashCode = prime * hashCode + ((getEndpointName() == null) ? 0 : getEndpointName().hashCode()); hashCode = prime * hashCode + ((getTargetCpuUtilizationPerCore() == null) ? 0 : getTargetCpuUtilizationPerCore().hashCode()); hashCode = prime * hashCode + ((getScalingPolicyObjective() == null) ? 0 : getScalingPolicyObjective().hashCode()); hashCode = prime * hashCode + ((getMetric() == null) ? 0 : getMetric().hashCode()); hashCode = prime * hashCode + ((getDynamicScalingConfiguration() == null) ? 0 : getDynamicScalingConfiguration().hashCode()); return hashCode; } @Override public GetScalingConfigurationRecommendationResult clone() { try { return (GetScalingConfigurationRecommendationResult) super.clone(); } catch (CloneNotSupportedException e) { throw new IllegalStateException("Got a CloneNotSupportedException from Object.clone() " + "even though we're Cloneable!", e); } } }




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