GitHub user SameerMesiah97 created a discussion: RedshiftCreateClusterOperator 
leaks Redshift cluster on failure with partial IAM permissions

### Apache Airflow Provider(s)

amazon

### Versions of Apache Airflow Providers

`apache-airflow-providers-amazon>=9.21.0rc1`

### Apache Airflow version

main

### Operating System

Debian GNU/Linux 12 (bookworm)

### Deployment

Other

### Deployment details

_No response_

### What happened

When using `RedshiftCreateClusterOperator`, a Redshift cluster may be 
successfully created even when the AWS execution role has **partial Redshift 
permissions**, for example lacking `redshift:DescribeClusters`.

In this scenario, the operator successfully calls `create_cluster` and the 
Redshift cluster begins provisioning in AWS. However, subsequent steps—such as 
waiting for the cluster to become available when 
`wait_for_completion=True`—fail due to insufficient permissions.

The Airflow task then fails, but the Redshift cluster continues provisioning or 
remains active in AWS, resulting in leaked infrastructure and ongoing cost.

This can occur, for example, when the execution role allows 
`redshift:CreateCluster` but explicitly denies `redshift:DescribeClusters`, 
which is required by the waiter used to monitor cluster availability.

### What you think should happen instead

If the operator fails after successfully initiating cluster creation (for 
example due to missing `DescribeClusters` or other follow-up permissions), it 
should make a **best-effort attempt to clean up** the partially created 
resource by deleting the cluster.

Cleanup should be attempted opportunistically (i.e. only if the cluster 
identifier is known and the necessary permissions are available), and failure 
to clean up should **not mask or replace the original exception**.

### How to reproduce

1. Create an IAM role that allows `redshift:CreateCluster` but denies 
`redshift:DescribeClusters`.

2. Configure an AWS connection in Airflow using this role.
   (The connection ID `aws_test_conn` is used for this reproduction.)

3. Ensure a valid Redshift cluster subnet group exists.
   (For example: `example-subnet-group`.)

4. Use the following DAG:

```python
from datetime import datetime

from airflow import DAG
from airflow.providers.amazon.aws.operators.redshift_cluster import (
    RedshiftCreateClusterOperator,
)

with DAG(
    dag_id="redshift_partial_auth_cluster_leak_repro",
    start_date=datetime(2025, 1, 1),
    schedule=None,
    catchup=False,
) as dag:
    create_cluster = RedshiftCreateClusterOperator(
        task_id="create_redshift_cluster",
        aws_conn_id="aws_test_conn",
        cluster_identifier="leaky-redshift-cluster",
        node_type="ra3.large",
        master_username="example",
        master_user_password="example",
        cluster_type="single-node",
        cluster_subnet_group_name="example-subnet-group",
        wait_for_completion=True,  # triggers DescribeClusters via waiter
    )
```

5. Trigger the DAG.

 **Observed Behaviour**

The task fails due to missing `redshift:DescribeClusters` permissions, but the 
Redshift cluster is successfully created and remains active in AWS. The cluster 
is not cleaned up automatically and continues incurring cost.

### Anything else

Redshift clusters begin incurring cost immediately once creation starts, even 
if the cluster never reaches an `available` state. When post-creation failures 
occur, leaked clusters can therefore result in unexpected and ongoing cost.

This issue follows a broader pattern across AWS operators where resources are 
created successfully but not cleaned up when subsequent steps fail. Apache 
Airflow has been introducing best-effort cleanup behavior to address this class 
of problems consistently across providers.

### Are you willing to submit PR?

- [x] Yes I am willing to submit a PR!

### Code of Conduct

- [x] I agree to follow this project's [Code of 
Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)


GitHub link: https://github.com/apache/airflow/discussions/61930

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