This page was last edited on May 31, 2019, at 17:01.
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See the Digital Messaging Server Options Reference for information on the configuration options available.
Options for a particular monitor override the general channel options.
You must set the following Java VM properties according to which DMS channels are used in your environment:
Channel(s) | Options |
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Chat mode only is used in all DMS channels |
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Paging mode only is used in all DMS channels |
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Both chat and paging modes are used in DMS channels |
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DMS channels do not post messages to DMS (for example, a channel for bots) |
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Although values for sensitive data such as passwords are masked in key-value lists, these values are not masked when users view or modify the related configuration options.
You can use the internal log-filtering mechanism in Digital Messaging Server to properly mask these values, based on the logging-filter-default.json configuration file that you put into the directory where your DMS jar file resides. Specify the configuration file to use in the value for logging-filter-spec. Click here to download a sample for logging-filter-default.json.
First, define a set of filters that are applied to the server's log messages before they are passed to a logging system. The filters intercept the original message's content and produce new content (possibly empty values) for specific messages in a log file (for example, a message that has specific identification information).
There are three types of filter procedures:
The filter can modify content as part of a series of steps. For example, it can mask one category of information before masking a separate category.
Modification of content is based on a search-and-replace approach using regular expressions and replace expressions (“search” predicate and “replace” action). See the following links for more information:
You must extensively test regular expressions to ensure they perform as expected in all cases. The following tools might be useful for testing:
The following are examples and definitions of typical sensitive data: