shivaam commented on issue #62247:
URL: https://github.com/apache/airflow/issues/62247#issuecomment-3988166952

   Tested multi-team AWS Batch executor config isolation with two teams sharing 
the same AwsBatchExecutor class but with independent configurations.
   
   
   Setup:
   
   Airflow running from main (3.2.0dev) on EC2
   Two teams: team_alpha and team_beta
   Each team has its own [team_name=aws_batch_executor] config section pointing 
to separate Batch job queues and job definitions
   
   Config:
   ```
   [core]
   executor = 
LocalExecutor;team_alpha=AwsBatchExecutor;team_beta=AwsBatchExecutor
   
   [team_alpha=aws_batch_executor]
   job_name = alpha-airflow-worker
   job_queue = alpha-batch-queue
   job_definition = alpha-batch-job-def
   
   [team_beta=aws_batch_executor]
   job_name = beta-airflow-worker
   job_queue = beta-batch-queue
   job_definition = beta-batch-job-def
   ```
   
   Results:
   - Triggered alpha_simple_dag → Batch job submitted to alpha-batch-queue with 
alpha-batch-job-def ✅
   - Triggered beta_simple_dag → Batch job submitted to beta-batch-queue with 
beta-batch-job-def ✅
   - Scheduler correctly routed alpha to 
AwsBatchExecutor(team_name='team_alpha') and beta to 
AwsBatchExecutor(team_name='team_beta') ✅
   - No cross-contamination: alpha jobs only appear in alpha-batch-queue, beta 
jobs only in beta-batch-queue ✅
   
   Bundle routing confirmed from Batch job command payloads:
   Alpha: bundle_info.name=team_alpha_dags, dag_rel_path=alpha_dag.py ✅
   Beta: bundle_info.name=team_beta_dags, dag_rel_path=beta_dag.py ✅
   
   Each team's executor instance correctly reads its own config section and 
submits jobs to the corresponding Batch infrastructure.


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