Exporting data from AWS CloudWatch to CSV is a straightforward process that allows you to effectively analyze and share your cloud performance metrics.
This guide will walk you through the steps required to extract data from AWS CloudWatch and save it in CSV format.
Additionally, you'll learn how Sourcetable enables you to analyze your exported data with AI in a simple to use spreadsheet.
You can use a Python script to export AWS CloudWatch metrics into a CSV file. This script retrieves the metrics from CloudWatch and converts them into a comma-separated values (CSV) format for easy readability and analysis.
The Python script requires specifying the AWS service whose metrics should be retrieved as a mandatory argument. It supports multiple AWS services such as AWS Lambda, Amazon EC2, Amazon RDS, Application Load Balancer, Network Load Balancer, and API Gateway.
The script can take optional arguments for specifying the AWS Region and AWS credential profile. If these optional arguments are not provided, the script uses the default Region and profile configured for the workstation where the script runs.
Once the metrics are retrieved, the script generates a CSV file and stores it in the same directory where the script is located. This ensures easy access and management of the exported data.
The script also allows for customization. For instance, it does not collect Amazon EBS volume metrics by default, but this can be modified by updating the metrics.yaml file to include EBS metrics.
It is important to note that the script does not support Amazon Aurora as of now. It can be extended for more services and metrics by adjusting the code and configuration files accordingly.
Exporting AWS CloudWatch data to CSV format is essential for data analysis and reporting. This guide explains the process to retrieve and convert CloudWatch metrics to CSV using a Python script.
To export AWS CloudWatch metrics to a CSV file, you will need a Python script. This script retrieves CloudWatch metrics and converts them into a CSV file for improved readability.
The Python script requires the AWS service whose metrics should be retrieved as a mandatory argument. Optional arguments include the AWS Region and AWS credential profile.
If no optional arguments are provided, the script uses the default Region and profile configured on your workstation.
The script supports AWS Lambda, Amazon EC2, Amazon RDS, Application Load Balancer, Network Load Balancer, and API Gateway. Amazon Aurora and certain EBS metrics are not supported by default.
The script generates a CSV file and stores it in the same directory where the script is executed. Ensure your working directory has appropriate write permissions.
1. Configure your AWS credentials and region on your workstation.
2. Download and prepare the Python script for execution.
3. Run the script with the necessary arguments to retrieve your desired AWS CloudWatch metrics.
4. Find the generated CSV file in the same directory as the Python script.
Exporting AWS CloudWatch metrics to a CSV file enables efficient data handling and reporting. Follow the guidelines above to perform the export effectively using a Python script.
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You can export AWS CloudWatch metrics to a CSV file using a Python script. The script retrieves the metrics and converts them into a CSV file, which is stored in the same directory as the script.
The Python script supports exporting metrics for AWS Lambda, Amazon EC2, Amazon RDS, Application Load Balancer, Network Load Balancer, and API Gateway. However, it does not support Amazon Aurora.
Yes, the Python script can be modified to collect Amazon EBS metrics by updating the metrics.yaml file.
The script requires the AWS service whose metrics should be retrieved as a mandatory argument. It can also take optional arguments for AWS Region and AWS credential profile. If these optional arguments are not provided, the script uses default values.
The CSV file generated by the Python script is stored in the same directory as the script.
Exporting data from AWS CloudWatch to CSV is a straightforward process that involves selecting the relevant logs and utilizing the export function. This allows for easy data handling and analysis.
By converting CloudWatch data to CSV, you can leverage tools that are more suited to your analytical needs.
Sign up for Sourcetable to analyze your exported CSV data with AI in a simple-to-use spreadsheet.