Recently one of the AWS accounts that I manage showed a spike in the bill. On detailed analysis, I found so many active SageMaker instances in the account.
I thought of exporting the details as a csv file and sharing it with the team to understand the usage and delete the unwanted instances. I have developed the following program to generate a csv file with the basic details of all the SageMaker instances present in the AWS account.
The program is very simple. I have used python boto3 to get the complete details of AWS SageMaker instances.
| import csv | |
| import boto3 | |
| client = boto3.client('sagemaker', region_name='us-east-1') | |
| response = client.list_notebook_instances(MaxResults=100) | |
| notebooks = response['NotebookInstances'] | |
| print("Total Number of Notebook Instances —–>", len(notebooks)) | |
| notebook_list = [] | |
| for notebook in notebooks: | |
| notebook_dict = dict() | |
| notebook_dict['NotebookInstanceName'] = notebook['NotebookInstanceName'] | |
| notebook_dict['NotebookInstanceArn'] = notebook['NotebookInstanceArn'] | |
| notebook_dict['NotebookInstanceStatus'] = notebook['NotebookInstanceStatus'] | |
| notebook_dict['InstanceType'] = notebook['InstanceType'] | |
| notebook_list.append(notebook_dict) | |
| print(notebook_list) | |
| with open('notebook_instances.csv', 'w', encoding='utf8', newline='') as output_file: | |
| fc = csv.DictWriter(output_file, | |
| fieldnames=notebook_list[0].keys()) | |
| fc.writeheader() | |
| fc.writerows(notebook_list) |
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