Forecasting and monitoring costs for sensitive data discovery jobs - Amazon Macie

Forecasting and monitoring costs for sensitive data discovery jobs

Amazon Macie pricing is based partly on the amount of data that you analyze by running sensitive data discovery jobs. To forecast and monitor your estimated costs for running sensitive data discovery jobs, you can review cost estimates that Macie provides when you create a job and after you start running jobs.

To view and monitor your actual costs, you can use AWS Billing and Cost Management. AWS Billing and Cost Management provides features that are designed to help you track and analyze your costs for AWS services, and manage budgets for your account or organization. It also provides features that can help you forecast usage costs based on historical data. To learn more, see the AWS Billing and Cost Management User Guide.

For information about Macie pricing, see Amazon Macie pricing.

Forecasting the cost of a sensitive data discovery job

When you create a sensitive data discovery job, Macie can calculate and display estimated costs during two key steps in the job creation process: when you review the table of S3 buckets that you selected for the job (step 2) and when you review all the settings for the job (step 6). These estimates can help you determine whether to adjust the job's settings before you save the job. The availability and nature of the estimates depends on the settings that you choose for the job.

Reviewing estimated costs for individual buckets (step 2)

If you explicitly select individual buckets for a job to analyze, you can review the estimated cost of analyzing objects in each of those buckets. Macie displays these estimates during step 2 of the job creation process, when you review your bucket selections. In the Select S3 buckets table for this step, the Estimated cost field indicates the total estimated cost (in US Dollars) of running the job once to analyze objects in a bucket.

Each estimate reflects the projected amount of uncompressed data that the job will analyze in a bucket, based on the size and types of objects that are currently stored in the bucket. The estimate also reflects Macie pricing for the current AWS Region.

Only classifiable objects are included in the cost estimate for a bucket. A classifiable object is an S3 object that uses a supported Amazon S3 storage class (S3 Intelligent-Tiering, S3 One Zone-IA, S3 Standard, or S3 Standard-IA) and has a file name extension for a supported file or storage format. If any classifiable objects are compressed or archive files, the estimate assumes that the files use a 3:1 compression ratio and the job can analyze all extracted files.

Reviewing the total estimated cost of a job (step 6)

If you create a one-time job or you create and configure a periodic job to include existing S3 objects, Macie calculates and displays the job's total estimated cost during the final step (step 6) of the job creation process. You can review this estimate while you review and verify all the settings that you selected for the job.

This estimate indicates the total projected cost (in US Dollars) of running the job once in the current Region. The estimate reflects the projected amount of uncompressed data that the job will analyze. It's based on the size and types of objects that are currently stored in buckets that you explicitly selected for the job or up to 500 buckets that currently match bucket criteria that you specified for the job, depending on the job's settings.

Note that this estimate doesn't reflect any options that you selected to refine and reduce the scope of the job—for example, a lower sampling depth, or criteria that exclude certain S3 objects from the job. It also doesn't reflect your monthly sensitive data discovery quota, which might limit the scope and cost of the job's analysis, or any discounts that might apply to your account.

In addition to the total estimated cost of the job, the estimate provides aggregated data that offers insight into the projected scope and cost of the job:

  • Size values indicate the total storage size of the objects that the job can and can't analyze.

  • Object count values indicate the total number of objects that the job can and can't analyze.

In these values, a Classifiable object is an S3 object that uses a supported Amazon S3 storage class (S3 Intelligent-Tiering, S3 One Zone-IA, S3 Standard, or S3 Standard-IA) and has a file name extension for a supported file or storage format. Only classifiable objects are included in the cost estimate. A Not classifiable object is an object that doesn't use a supported Amazon S3 storage class or doesn't have a file name extension for a supported file or storage format. These objects aren't included in the cost estimate.

The estimate provides additional aggregated data for S3 objects that are compressed or archive files. The Compressed value indicates the total storage size of objects that use a supported Amazon S3 storage class and have a file name extension for a supported type of compressed or archive file. The Uncompressed value indicates the approximate size of these objects if they're decompressed, based on a specified compression ratio. This data is relevant due to the way that Macie analyzes compressed files and archive files.

When Macie analyzes a compressed or archive file, it inspects both the full file and the contents of the file. To inspect the file’s contents, Macie decompresses the file, and then inspects each extracted file that uses a supported format. The actual amount of data that a job analyzes therefore depends on:

  • Whether a file uses compression and, if so, the compression ratio that it uses.

  • The number, size, and format of the extracted files.

By default, Macie assumes the following when it calculates cost estimates for a job:

  • All compressed and archive files use a 3:1 compression ratio.

  • All the extracted files use a supported file or storage format.

These assumptions can result in a larger size estimate for the scope of the data that the job will analyze, and, consequently, a higher cost estimate for the job.

You can recalculate the job's total estimated cost based on a different compression ratio. To do this, choose the ratio from the Choose an estimated compression ratio list in the Estimated cost section. Macie then updates the estimate to match your selection.

For more information about how Macie calculates estimated costs, see Forecasting and monitoring Amazon Macie costs.

Monitoring estimated costs for sensitive data discovery jobs

If you’re already running sensitive data discovery jobs, the Usage page on the Amazon Macie console can help you monitor the estimated cost of those jobs. The page shows your estimated costs (in US Dollars) for using Macie in the current AWS Region during the current calendar month. For information about how Macie calculates these estimates, see Forecasting and monitoring Amazon Macie costs.

To review your estimated costs for running jobs

  1. Open the Macie console at https://console.aws.amazon.com/macie/.

  2. By using the AWS Region selector in the upper-right corner of the page, select the Region in which you want to review your estimated costs.

  3. In the navigation pane, choose Usage.

  4. In the Estimated costs section, refer to the breakdown of estimated costs for your account. The Data discovery jobs item reports the total estimated cost of the jobs that you've run thus far during the current month in the current Region.

    If you're the Macie administrator for an organization, the Estimated costs section shows estimated costs for your organization overall for the current month in the current Region. To show the total estimated cost of the jobs that were run for a specific account, choose the account in the table. The Estimated costs section then shows a breakdown of estimated costs for the account, including the estimated cost of the jobs that were run. To show this data for a different account, choose the account in the table. To clear your account selection, choose X next to the account ID.

To view and monitor your actual costs, use AWS Billing and Cost Management.