cloud watch alarm continues in the state if 'In Alarm' even after the instances come down to zero.

I have an aws asynchronous endpoint with auto scaling attached to it. The expected behavior is to scale in the instance count to zero when there are no requests and scale up when at least one request comes. Its working as expected. However when I check the cloud watch alarms , I could see that the alarm for scale in remain in the state of 'in Alarm' even after the instance count reduces to zero. Is this the normal behavior? How to make its state ok once the instance count reaches 0? I doubt this is delaying the scale out action when a new request comes. My autoscaling configuration is as follows:

# application-autoscaling client
asg_client = boto3.client("application-autoscaling")

# This is the format in which application autoscaling references the endpoint
resource_id = f"endpoint/{async_predictor.endpoint_name}/variant/AllTraffic"

# Configure Autoscaling on asynchronous endpoint down to zero instances
response = asg_client.register_scalable_target(
    ServiceNamespace="sagemaker",
    ResourceId=resource_id,
    ScalableDimension="sagemaker:variant:DesiredInstanceCount",
    MinCapacity=0,
    MaxCapacity=5,
)

response = asg_client.put_scaling_policy(
    PolicyName = f'HasBacklogWithoutCapacity-ScalingPolicy-{async_predictor.endpoint_name}',
    ServiceNamespace="sagemaker",  # The namespace of the service that provides the resource.
    ResourceId=resource_id,  # Endpoint name
    ScalableDimension="sagemaker:variant:DesiredInstanceCount",  # SageMaker supports only Instance Count
    PolicyType="StepScaling",  # 'StepScaling' or 'TargetTrackingScaling'
    StepScalingPolicyConfiguration={
        "AdjustmentType": "ChangeInCapacity", # Specifies whether the ScalingAdjustment value in the StepAdjustment property is an absolute number or a percentage of the current capacity. 
        "MetricAggregationType": "Average", # The aggregation type for the CloudWatch metrics.
        "Cooldown": 300, # The amount of time, in seconds, to wait for a previous scaling activity to take effect. 
        "StepAdjustments": # A set of adjustments that enable you to scale based on the size of the alarm breach.
        [ 
            {
              "MetricIntervalLowerBound": 0,
              "ScalingAdjustment": 1
            }
          ]
    },    
)

cw_client = boto3.client('cloudwatch')
step_scaling_policy_arn = response['PolicyARN']

response = cw_client.put_metric_alarm(
    AlarmName=f'step_scaling_policy_alarm_name-{async_predictor.endpoint_name}',
    MetricName='HasBacklogWithoutCapacity',
    Namespace='AWS/SageMaker',
    Statistic='Average',
    EvaluationPeriods= 2,
    DatapointsToAlarm= 2,
    Threshold= 1,
    ComparisonOperator='GreaterThanOrEqualToThreshold',
    TreatMissingData='missing',
    Dimensions=[
        { 'Name':'EndpointName', 'Value':async_predictor.endpoint_name },
    ],
    Period= 60,
    AlarmActions=[step_scaling_policy_arn]
)

response_scalein = asg_client.put_scaling_policy(
    PolicyName = f'scaleinpolicy-{async_predictor.endpoint_name}',
    ServiceNamespace="sagemaker",  # The namespace of the service that provides the resource.
    ResourceId=resource_id,  # Endpoint name
    ScalableDimension="sagemaker:variant:DesiredInstanceCount",  # SageMaker supports only Instance Count
    PolicyType="StepScaling",  # 'StepScaling' or 'TargetTrackingScaling'
    StepScalingPolicyConfiguration={
        "AdjustmentType": "ChangeInCapacity", # Specifies whether the ScalingAdjustment value in the StepAdjustment property is an absolute number or a percentage of the current capacity. 
        "MetricAggregationType": "Average", # The aggregation type for the CloudWatch metrics.
        "Cooldown": 300, # The amount of time, in seconds, to wait for a previous scaling activity to take effect. 
        "StepAdjustments": # A set of adjustments that enable you to scale based on the size of the alarm breach.
        [ 
            {
              "MetricIntervalUpperBound": 0,
              "ScalingAdjustment": -1
            }
          ]
    },    
)

cw_client = boto3.client('cloudwatch')
stepin_scaling_policy_arn = response_scalein['PolicyARN']

response = cw_client.put_metric_alarm(
    AlarmName=f'step_scale-in_policy-{async_predictor.endpoint_name}',
    MetricName='ApproximateBacklogSizePerInstance',
    Namespace='AWS/SageMaker',
    Statistic='Average',
    EvaluationPeriods= 2,
    DatapointsToAlarm= 2,
    Threshold= 0.5,
    ComparisonOperator='LessThanOrEqualToThreshold',
    TreatMissingData='missing',
    Dimensions=[
        { 'Name':'EndpointName', 'Value':async_predictor.endpoint_name },
    ],
    Period= 60,
    AlarmActions=[stepin_scaling_policy_arn]
)