Defining S3 Delete File Jobs
This job allows you to delete a file from the S3 bucket. A file can only be deleted if it exists in the specified bucket. However, if the file that you have specified does not exist, the job does not fail. It only fails if the region or bucket name do not exist.
On the Delete File Job section, you define the parameters relevant to run that job on the S3 system from Automic Automation.
Some fields allow you to open a picker dialog from where you can select the file and the bucket. By default, only 200 entries are displayed. If the relevant file or bucket is not displayed among those 200, please type in the relevant name on the Search field to narrow down the list.
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Connection
Select the S3 Connection object containing the relevant information to connect to the Simple Storage Service system.
To search for a Connection object, start typing its name to limit the list of the objects that match your input.
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Region
Defining the region in the job is optional and only relevant for AWS. If you choose not to define it, the job takes the URL defined in the Connection object.
However, if you decide to define the region in the job, make sure that the definition matches the one defined in the Connection object that you have selected for the job. If both region definitions do not match, the job execution fails and an error message is logged in both, the Agent (PLOG) and the Job (REP) reports (see Monitoring S3 Jobs).
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Bucket Name
Define the bucket name from where the file must be deleted. You can click the browse button to the right of the field to open a picker dialog where you can select the relevant name.
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File Name
Define the name of the file to be deleted on the bucket. The file name definition is case sensitive. You can click the browse button to the right of the field to open a picker dialog where you can select the relevant name.
If the bucket has folders and sub-folders, you must enter the entire path here. For example <folder name>/<file name>.
The Pre-Process page allows you to define the settings all S3 Jobs using script statements. These statements are processed before the Schedule Job is executed, see Setting S3 Job Properties Through Scripts.
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