Mastering AWS Cost Explorer Commands (with examples)

AWS Cost Explorer is a powerful tool that allows users to manage and analyze their AWS costs and usage. By utilizing the AWS Cost Explorer command-line interface, users can automate cost management tasks, gain insights into their spending, and optimize their resource utilization. These commands are invaluable for financial planning, anomaly detection, and budget management. Below, we explore various use cases for different AWS Cost Explorer commands to illustrate their potential and utility.

Create Anomaly Monitor

Code:

aws ce create-anomaly-monitor --monitor monitor_name --monitor-type monitor_type

Motivation:

Creating an anomaly monitor helps in automatically identifying unusual spending patterns in AWS usage. This is critical for maintaining cost control and preventing unexpected charges by being alerted to irregular spending behaviors that could indicate errors, misconfigurations, or unauthorized usage.

Explanation:

• --monitor: Specifies the name of the monitor. This should be a descriptive name that helps you quickly identify the purpose or focus of the monitor.
• --monitor-type: Indicates the type of anomaly detection. This could be based on specific services or costs, allowing you to focus on either total spending or spending per service.

Example Output:

{
    "MonitorArn": "arn:aws:ce::123456789012:anomaly-monitor/abcdef12-3456-7890-abcd-ef1234567890"
}

Create Anomaly Subscription

Code:

aws ce create-anomaly-subscription --subscription subscription_name --monitor-arn monitor_arn --subscribers subscribers

Motivation:

Once an anomaly monitor is in place, an anomaly subscription ensures you or relevant stakeholders are promptly notified about detected anomalies. This facilitates quick responses to unusual spending, enabling cost-saving actions or early investigations into potential issues.

Explanation:

• --subscription: Name for the subscription plan, helping to identify what the subscription is for.
• --monitor-arn: The Amazon Resource Name (ARN) of the associated anomaly monitor, linking to which monitor’s anomalies will generate notifications.
• --subscribers: Specifies the recipients of anomaly alerts. This could be in the form of email addresses or other notification endpoints.

Example Output:

{
    "SubscriptionArn": "arn:aws:ce::123456789012:anomaly-subscription/00112233-4455-6677-8899-aabbccddeeff"
}

Get Anomalies

Code:

aws ce get-anomalies --monitor-arn monitor_arn --start-time start_time --end-time end_time

Motivation:

Reviewing anomalies helps in understanding when and how spending diverged from normal patterns, facilitating root cause analysis of cost spikes.

Explanation:

• --monitor-arn: Identifies which monitor’s anomalies to retrieve.
• --start-time: Defines the beginning of the time range for which anomalies are being queried.
• --end-time: Indicates the end of the time range for the anomaly query.

Example Output:

{
    "Anomalies": [
        {
            "AnomalyId": "anomaly-123456",
            "StartDate": "2023-01-01",
            "EndDate": "2023-01-02",
            "Description": "Unusual increase in EC2 usage"
        }
    ]
}

Get Cost and Usage

Code:

aws ce get-cost-and-usage --time-period start_date/end_date --granularity granularity --metrics metrics

Motivation:

Retrieving detailed cost and usage information supports budgeting, forecasting, and analysis efforts by allowing you to understand how and where your funds are being used.

Explanation:

• --time-period: Specifies the date range for the desired cost and usage data.
• --granularity: Determines the reporting period, which could be daily or monthly, depending on how detailed the data needs to be.
• --metrics: Indicates the types of data needed, such as ‘UnblendedCost’ or ‘UsageQuantity’.

Example Output:

{
    "ResultsByTime": [
        {
            "TimePeriod": {
                "Start": "2023-01-01",
                "End": "2023-01-31"
            },
            "Total": {
                "UnblendedCost": {
                    "Amount": "100.00",
                    "Unit": "USD"
                }
            }
        }
    ]
}

Get Cost Forecast

Code:

aws ce get-cost-forecast --time-period start_date/end_date --granularity granularity --metric metric

Motivation:

Cost forecasting is crucial for anticipating future spending, helping organizations budget efficiently and make informed financial decisions.

Explanation:

• --time-period: Designates the future period for which the cost forecast should be generated.
• --granularity: Specifies the level of detail, such as daily or monthly forecasts.
• --metric: Identifies the type of forecast required, such as ‘UnblendedCost’ for cost projection.

Example Output:

{
    "ForecastResultsByTime": [
        {
            "TimePeriod": {
                "Start": "2023-02-01",
                "End": "2023-02-28"
            },
            "MeanValue": "150.00"
        }
    ]
}

Get Reservation Utilization

Code:

aws ce get-reservation-utilization --time-period start_date/end_date --granularity granularity

Motivation:

Understanding reservation utilization helps organizations maximize the value of Reserved Instances (RIs) by revealing how much of the reserved capacity is used, thus guiding optimization efforts to reduce costs.

Explanation:

• --time-period: Specifies the range over which reservation usage is assessed.
• --granularity: Defines the reporting detail, such as daily or monthly reservation usage.

Example Output:

{
    "UtilizationsByTime": [
        {
            "TimePeriod": {
                "Start": "2023-01-01",
                "End": "2023-01-31"
            },
            "Total": {
                "UtilizationPercentage": "85.0%",
                "UtilizationQuantity": "20"
            }
        }
    ]
}

List Cost Category Definitions

Code:

aws ce list-cost-category-definitions

Motivation:

Listing cost category definitions allows you to review existing groupings of cost and usage data, facilitating better organization and understanding of spending according to custom categories.

Explanation:

• This command doesn’t require additional arguments as it simply lists all the defined cost categories in your AWS account.

Example Output:

{
    "CostCategoryReferences": [
        {
            "CostCategoryArn": "arn:aws:ce::123456789012:costcategory/abcd1234",
            "Name": "ProjectA",
            "EffectiveStart": "2023-01-01"
        },
        {
            "CostCategoryArn": "arn:aws:ce::123456789012:costcategory/abcd5678",
            "Name": "Marketing",
            "EffectiveStart": "2023-01-01"
        }
    ]
}

Tag Resource

Code:

aws ce tag-resource --resource-arn resource_arn --tags tags

Motivation:

Tagging resources is essential for organizing, tracking, and managing AWS assets more effectively, which aids in cost allocation and resource management through clear identification.

Explanation:

• --resource-arn: Specifies the ARN of the resource that needs tagging.
• --tags: Defines the key-value pairs for tagging, serving as identifiers and categorizers for the resource.

Example Output:

{
    "ResponseMetadata": {
        "RequestId": "abcd1234-efgh-5678-ijkl-1234567890mn",
        "HTTPStatusCode": 200
    }
}

Conclusion

Utilizing AWS Cost Explorer commands empowers users to comprehensively manage, analyze, and optimize their AWS costs. From anomaly detection and forecasting to resource tagging and usage analysis, these commands provide the necessary tools to keep AWS expenditures in check and resource allocations efficient.