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Determination of Database Types & Focus Databases

The appliance automatically categorizes a found NSF/NTF instance into one of the following types of categories:

  1. User Mail database(identified by a person document pointing to the instance)
  2. Mail-In database(identified by a non-system mail-in document …)
  3. System database(identified via well-known file or template name)
  4. database(identified from Domino server configuration settings)
  5. Directory(identified from Domino server configuration/used template)
  6. Orphaned User Mail(user mail files no longer associated with a person document)
  7. Application databases(all remaining not categorized into cat 1-6)

If a NSF/NTF instance is categorized once on one server, all existing instances with the same replica ID get categorized into the same category. This indication will not change once an instance is scanned for the first time unless things change in the infrastructure, servers are added, the design or ACL is changed, or the calculation algorithm is optimized (for instance with a new release of ApplicationInsights).

Based on the identified types, the DBs are divided into two groups: „Focus Databases" (consisting of Applications and Mail-in Dbs) and „Other Databases" (consisting of the remaining database types).

The majority of detailed usage and design analysis is performed on Focus DBs, but there is a variety of charts and reports with information about the other types.

Additional information outside the scope of ApplicationInights regarding these other DB types and infrastructure topics is available in panagenda iDNA. Please check our website or contact us for additional information.

User access days versus sessions

Each time a user accesses an application a session is set up. During the day users can have multiple sessions, as sessions get closed, users log out/login again or because they use multiple windows or clients. So, one user accessing an application over the day can result in multiple sessions. Sessions can also occur when servers and processes access database instances.

A User Access Day is identified as a unique user accessing an application on any given day within the analyzed period.

So, there could be 20 sessions for User A accessing application Z in a period of 7 days but if that user only accessed the application on day 1 and 5 of that period with 14 sessions occurring on the first day and 6 on the fifth day the User Access Days number will still only be 2. In several graphs this distinction is used to eliminate the risk of skewed numbers and to allow you to make a more balanced decision when it comes to usage numbers.

Design Complexity, Design Complexity score, Design Similarities and Design Insights

Design Complexity is based on the magnitude of design elements and the amount of source code in these elements. The calculation is refined by several considerations like code language type, usage of Reader/Author fields, custom XPages control, etc.

Design Similarity analysis identifies how much alike a database is to all other analyzed databases. Databases with high similarity are grouped into design clusters, which allows for quick identification of replicas that might deviate from a common design. It also provides means to identify 'template candidates' for databases that have no template specified.

Design Insights are combinations of certain patterns occurring in the source code. These combinations are called "Findings" and can be anything from identifying platform dependencies when local DLLs are referenced to understanding if a piece of code interacts with other databases.

Design Complexity score is a categorization of seven levels from "Insignificant" to "Exceptional" that indicate the impact redesigning or migrating the application would have. The Design impact is calculated from three main sources: Complexity, Insights and Similarity.

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Data Collection and Time Constraints (Servers Being Polled_ Period Collected)