# Service environment states and lifecycle in AWS Batch
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Service environments maintain lifecycle states that indicate their current operational status and readiness to process SageMaker Training jobs. Understanding these states helps you monitor service environment health, troubleshoot configuration issues, and ensure reliable job processing. The state management system follows established patterns from compute environments while accommodating the unique requirements of SageMaker Training job integration.

Service environment states are managed automatically by AWS Batch based on configuration validation, resource availability, and operational health checks. Unlike compute environments that manage physical infrastructure, service environments focus on configuration validation and integration readiness with SageMaker AI services. The state transitions provide visibility into whether your service environment can successfully submit and manage SageMaker Training jobs.

# Service environment state definitions
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Service environments can be in one of four possible states that indicate their current operational status and readiness to process SageMaker Training jobs. Each state represents a specific phase in the service environment lifecycle, from initial creation through operational readiness to eventual deletion. The following table describes each state and its meaning:


| State | Description | 
| --- | --- | 
| CREATING |  The initial state when you create a service environment. During this state, AWS Batch validates the configuration parameters and establishes integration with SageMaker AI services. The service environment cannot process jobs, and any job queues associated with it will not accept service job submissions. The creation process typically completes within a few seconds for properly configured service environments.  | 
| VALID |  The operational state indicating that the service environment has passed all configuration validation checks and is ready to process SageMaker Training jobs. This state indicates that the service environment configuration is correct, all required permissions are in place, and AWS Batch can successfully submit jobs to SageMaker AI on your behalf. Service environments spend most of their operational lifecycle in this state.  | 
| INVALID |  A state indicating that the service environment has encountered a configuration or permissions issue that prevents it from processing SageMaker Training jobs. Job queues associated with invalid service environments cannot process new service job submissions until the underlying issues are resolved.  | 
| DELETING |  The state that occurs when you request deletion of a service environment. During this state, AWS Batch ensures that no active SageMaker Training jobs are associated with the environment and performs necessary cleanup operations. Service environments in this state cannot process new job submissions, and the deletion process completes once all associated resources are properly cleaned up.  | 

## Service environment state transitions
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Service environment state transitions occur automatically based on configuration changes, validation results, and operational health monitoring. The AWS Batch service continuously monitors service environment health and updates states accordingly. Understanding these transitions helps you anticipate when configuration changes will take effect and how to resolve issues that cause invalid states.

After successful creation and validation, service environments transition from `CREATING` to `VALID`. This transition confirms that all configuration parameters are correct, required IAM permissions are properly configured, and the service environment can successfully integrate with SageMaker AI services. Once in the `VALID` state, associated job queues can begin processing service job submissions.

Service environments transition from `VALID` to `INVALID` when configuration validation fails or when dependencies become unavailable. This can occur due to IAM role modifications, capacity limit changes that violate quotas, or external resource modifications that affect the service environment's ability to function. The status reason field provides specific details about what caused the invalid state.

Service environments can transition back to `VALID` from `INVALID` once the underlying issues are resolved. This might involve updating IAM permissions, correcting capacity configurations, or restoring access to required AWS resources. The transition typically occurs automatically once AWS Batch detects that the configuration issues have been addressed.