Logging Best Practice

Here we outline the best practices for logging settings on stages in processes and objects. A conscious use of the logging settings is key to preventing and resolving database, performance and archiving problems, as well as to address sensitive data policies.

Log settings

By default, stages used in Process Studio are logged and those in Object Studio are not. This can easily be changed by modifying the properties of a stage, selection of stages or all stages. Nearly all stage properties windows have a combo box with the stage logging options:

  • Enabled
  • Disabled
  • Errors Only

Errors only will log the stage only if an error is thrown when the stage runs.

Errors

Alternatively, the menu commands Edit > Selected Stages > and Edit > All Stages can be used to modify the stage logging of more than one stage at a time.

Selected stages

Page information stages are not logged, and Data Items are only logged when their values are used as inputs and outputs.

    Best Practice

    The decision as to which stages are logged and which are not should not be overlooked:

    • Logs are particularly useful during a test phase to investigate bugs
    • A live Process running all day can put a vast amount of data into the database, the maintenance and back up of which should be considered
    • The security or legal implications of storing sensitive data are also something to think about.

    Note: When Blue Prism Processes are run by Runtime Resources then they log information into the Blue Prism database. Over time, and if not regularly monitored and maintained, then the amount of data can get prohibitively large, potentially affecting the performance of the product and leading to an inability to establish a reliable automatic archiving function within the Blue Prism product.

    Potential Issues

    Potential issues arising from unduly large volumes of logging data are as follows:

    • The database performance degrades and the general speed of running Processes also suffers
    • Database queries time out, recording timeout-related errors in the Event Logs and causing Processes to fail
    • Archiving fails to complete, only archiving small amounts of data when larger volumes were selected 
    • Automatic archiving is blocked by an overly large log that cannot be moved due to its size.
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