The purpose of this Python based command line tool is to generate a CloudWatch Dashboard which is based on a list of resources you provide and contains predefined useful CloudWatch metrics selected by AWS Support engineers for monitoring AWS resources during special events or IEM (AWS Infrastructure Event Management) scenarios.

• Python version between 3.8 and 3.11.
• Has pip installed.

First install pip is the package installer for Python

$ python -m ensurepip --upgrade --user

If you have any issue to install pip, try using get-pip.py to install

1. Download the script, from https://bootstrap.pypa.io/get-pip.py.
2. Run python get-pip.py

If you run pip install but got error command not found: pip

It might indicated that your pip install path in not in env PATH, please reference WARNING message while install pip to find install path or try /Users/${USER}/Library/Python/3.8/bin/pip install -r requirements.txt

Find more information at pip installation document: https://pip.pypa.io/en/stable/installation/

pip install -r requirements.txt

Then execute this tool.

$ python3 iemcwd.py -h
Usage: iemcwd.py [OPTIONS]

  IEMCWD is a tool to generate an IEM CloudWatch Dashboard based on
  resources you provide. The IEM CloudWatch Dashboard contains useful
  predefined metrics for IEM monitoring.

Options:
  -f, --file FILENAME         [required]
  -o, --output-file FILENAME  [required]
  -h, --help                  Show this message and exit.

The tool is quite simple. It reads a CSV file to get your resource IDs, then output the dashboard JSON to the directory you specified.

There is an example CSV file at inputs/csv/example.csv under this package for your reference. The table in CSV file must follow the format as below:

For the explanation of these attributes, see below for more.

You may create a CSV file matching the columns and format above, or fill in inputs/csv/fill-in.csv with the resources you want to monitor on the dashboard. The order of entries(rows) in this table does not matter. The below is an example for the CSV input file, or refer to inputs/csv/example.csv in this repository. Though most of the service only requires one metric (dim1_name and dim1_value columns), please note that some services, including Elasticache, contain a second dimension entry dim2_name and dim2_value.

Example:

python3 iemcwd.py -f inputs/csv/example.csv -o outputs/example_output.json

Successfully generated CloudWatch dashBoard JSON file.

After generating the dashboard JSON file, use the following AWS CLI command to create a CloudWatch based on this JSON file:

$ aws cloudwatch put-dashboard --dashboard-name your-iem-dashboard --dashboard-body file://outputs/example_output.json

You may also follow the below documentation to create the CloudWatch dashboard using AWS Console using the generated JSON:

• https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/add_old_metrics_to_graph.html

service should be one of the following:

• ALB
• CLB
• CloudFront
• EC2
• ElastiCache
• NLB
• RDS
• NAT
• AuroraCluster

region_code is the AWS region where your resource is located at. See definitions/Regions.json for a list of region code.

dim1_name and dim1_value is the dimension of a metric in Cloud Watch. A dimension is a name/value pair that is part of the identity of a metric.Take EC2 for example, the dim1_name is InstanceId, and dim1_value will be the instance ID. Some metrics may contain multiple dimensions, such as ElastiCache. Understanding each AWS service resource Dimension here: https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/aws-services-cloudwatch-metrics.html

See CONTRIBUTING for more information.

This library is licensed under the MIT-0 License. See the LICENSE file.