How nodes are removed

It is important that the model of your network environment stays current over time and that it is maintained efficiently. This not only involves creating new nodes to represent recently discovered data, but also the removal of existing data that is no longer present in your environment. BMC Discovery views the environment so that different kinds of nodes are removed in different ways. Different methods are used to remove inferred nodes and Directly Discovered Data nodes from the model. These variations in behavior are detailed in the following sections.

Inferred nodes removal

The following sections detail the ways in which inferred nodes are removed from BMC Discovery. For more information on inferred nodes, see Inferred nodes.

Manual

To remove a node manually, select it in the node list and pick Destroy from the Actions list.

Authoritative

BMC Discovery has inferred the presence of a node from data such as an interface list, where there is clear evidence that the node exists. When BMC Discovery cannot see any evidence of this node, it no longer exists. Therefore, BMC Discovery removes the node automatically from the model. Aging is not applied to this type of removal.

Non-authoritative (aging)

BMC Discovery has inferred the presence of a node from data such as a process list, where there is clear evidence that the node exists. However, in cases when BMC Discovery cannot see any evidence that the node still exists, it does not necessarily imply that the node no longer exists. There might be other reasons why the node appears to no longer exist.

For example, a process that relates to a software instance (SI), such as an Adobe FrameMaker desktop application, might appear to be running during an initial scan, but not on a subsequent scan. This does not necessarily indicate that Adobe FrameMaker no longer exists; instead, it is possible that the user has stopped running the application during the subsequent scan. Because it is the nature of IT infrastructure to have frequent minor changes to configurations, hosts, and software, discovered data becomes less relevant over time.

Aging is applied to this type of removal to prevent frequent removal and recreating of SIs. When the node has been in the aging state for some time, it is then removed from the model.

Only the following classes of nodes age:

  • Root nodes (Host, Network Device, MFPart, Printer, SNMP Managed Device, and Management Controller.)
  • First order Software Instances (ones created directly from DDD)
  • Runtime Environment
  • Storage

The Software Instance, Runtime Environment, and Storage nodes mentioned above are only automatically aged if they are triggered on certain types of DDD. These are described on the individual node pages.

Although there are important considerations before doing so, you can modify data aging limits in the Model Maintenance settings of the user interface.

Secondary authoritative

This type of removal is authoritative, however it is based on different criteria than the original evidence for its existence.
An example of this would be a batch process, where a node creation (and therefore existence) is triggered from seeing the job running in the process list, but BMC Discovery might check the timestamp of a log file to see if it believes it is running regularly.

This type will apply to any removal which involves actively seeking evidence about whether something exists.

Containment

This type of removal applies when BMC Discovery has inferred nodes which have a containment relationship to another node. These are generally nodes which model physical items such as network interface cards. If the non-authoritative removal process (Aging) has caused BMC Discovery to remove a host, then the network interfaces that are contained in that host will also cease to exist. Therefore, Aging is not applied and the inferred node is removed.

Cascade

This type of removal applies where further inferred nodes are constructed from first order or other inferred nodes. Any aging or specific removal will already have taken place at the first order nodes, so there is no need to apply any further removal strategies. In this case the removal should cascade up.

Directly Discovered Data nodes removal

The removal process for DDD nodes, is a much simpler process than it is for Inferred nodes.

The five removal strategies for Inferred nodes calculate that the entity in the real-world to which the data corresponds no longer exists and therefore the node is removed. Each time you run a discovery of DDD nodes, a new set of data is retrieved. If the data is older than a certain cut-off point and BMC Discovery discovers more recent data which refers to the same node, the node is removed.

Removal groups in the pattern language

When patterns construct complicated structures, such as DatabaseDetail nodes when doing deep discovery of databases, removal must be performed by the pattern that creates them. Removal Groups are named groups of nodes which simplify deletion of these complex structures. They are described in Model functions in the TPL Guide.

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