Amazon Lookout for Metrics

To create a flow with Amazon Lookout for Metrics as the destination

1. Sign in to the AWS Management Console and open the Amazon AppFlow console at https://console.aws.amazon.com/appflow/.

2. Choose Create flow and enter a name for your flow.

3. Under Data encryption, choose Customize encryption settings (advanced) then select an existing customer managed key (CMK) or create a new one. The default AWS managed CMK is not supported when using Amazon Lookout for Metrics as a destination.

4. (Optional) To add a tag, choose Tags, Add tag and then enter the key name and value.

5. Choose Next.

6. For Source details, choose a supported source and provide the requested information.

7. For Destination details, choose Amazon Lookout for Metrics as the destination for your time-series data.

8. When using Amazon Lookout for Metrics as a destination, only the Run flow on schedule option is available. Specify the appropriate schedule settings, such as the frequency, start date, and start time. You can also enter an end date (optional).

   Amazon Lookout for Metrics currently supports the following scheduling options:

   • If the source supports minutes: you can run the flow every 5 or 10 minutes by selecting 5 or 10 from the Every dropdown list.

   • If the source supports hours: you can run the flow once an hour by selecting 1 from the Every dropdown list.

   • If the source supports days: you can run the flow once a day by selecting 1 from the Every dropdown list.

9. Choose Next.

10. Under Source to destination field mapping, go to the Source field name dropdown list and choose Map all fields directly. Alternatively, you can manually select the fields that you want to use from the list.

    Note

    A timestamp field is not required in your data. However, in order to use the anomaly detection feature of Amazon Lookout for Metrics, you need at least one measure or numeric column with values changing over time.

11. (Optional) Under Validations - optional, add validations to check whether a field has bad data. For each field, choose the condition that indicates bad data and what action Amazon AppFlow should take when a field in a record is bad.

12. Choose Next.

13. (Optional) Specify a filter to determine which records to transfer. To add a filter, choose Add filter, select the field name, select a condition, and then specify the criteria.

14. Choose Next.

15. Review the settings and then choose Create flow.