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BMC Discovery components

BMC Discovery automatically discovers the hardware and software in your data center, determines configuration and relationship data, and maps applications to the IT infrastructure. 

The following list defines the components of BMC Discovery:

Discovery Engine

Information about your organization's hardware and software is obtained by the Discovery Engine. The Engine uses credentials, which are held in a secure encrypted vault, to log into target hosts using variety of methods, such as SSH, Telnet, WMI and SNMP. Once logged in, the Discovery Engine executes commands, the results of which are returned and stored in the datastore as directly discovered data (DDD). Windows discovery uses an external proxy running on a dedicated windows server to log into and scan Windows hosts in the estate.


The Discovery Engine is supported by Reasoning which intelligently infers information about hosts and programs from the DDD returned. The process of adding DDD to the datastore causes Reasoning to execute patterns against the DDD. Each pattern represents knowledge about particular software or hardware and Reasoning uses this knowledge to create more detailed "inferred" data. Inferred data is the representation of the scanned IT environment and is stored in the datastore. The provenance of each item of inferred data is also stored meaning that when examining an inferred entity in the UI, you can examine the information which was used to create it.

Patterns can be updated, either through monthly Technology Knowledge Update (TKU) releases, or by writing new patterns using The Pattern Language (TPL).


The datastore is the database in which the DDD and inferred data is stored. Data written to the datastore is instantly indexed allowing you to search for items of interest using simple keywords in the UI. In addition to the DDD and inferred data mentioned, the datastore holds TKU information, patterns, operational data and some configuration data.

The datastore uses a graph model meaning that it represents data as nodes connected to each other with relationships. This is more suited to modeling the complex relationships in an IT environment than a relational database.

CMDB Synchronization

CMDB synchronization provides a means of keeping data in the BMC Atrium CMDB continuously synchronized with information discovered by BMC Discovery. The BMC Discovery data model is different from the Common Data Model (CDM) used in the CMDB, so the synchronization mechanism transforms the required information from one data model to the other.

Start anywhere application modeling

Start anywhere application modeling is a new approach to application modeling, which enables you to choose any entry point, or points into an application, and begin modeling from there. For robust applications, logical entry points differ depending on the view of the user. For example, an application owner might choose where the data is stored as the best entry point, and a user of the application might choose the server to which they connect to access the application. The start anywhere approach also prevents parts of applications from being missed if they are not currently connected to an entry point, such as a URL, which may lead to a load balanced service or web server. You might also choose multiple entry points to model the application.

You should start application modeling from anywhere that is interesting in the context of the application you are modeling. The best way of doing this is the search box in the top right of the UI. Enter the name or other detail of something you know to be in the application, and explore the data from there. When you see what you are looking for, start modeling.

The models produced with start anywhere application modeling are simple to create and work on the basis of data that has already been discovered from you network, data that is held in the BMC Discovery datastore. This does not mean that the models are static, rather, they update automatically to reflect the current data. So, if you scan the application and a new component of the application is discovered, it is automatically linked in to the existing components, and reflected when you view the model again. If the new component is of a type that you have excluded from the model, it is still in the datastore, but not included in the application model.


Clustering, also known as Big Discovery, enables you to discover and get usable results from even the largest Data Centers in the shortest time possible with the help of clusters. A cluster consists of two or more coordinated BMC Discovery machines, one of which is in control of the group and is referred to as the coordinator. Additional machines can be added to the cluster at any time. When you do so, the system spreads the existing data out amongst all the machines evenly, in order to maximize performance and utilization of each machine in the cluster. This can take a while to happen, but the system is fully usable while it happens: you can do discovery and browse the data.

You can configure clusters with fault tolerance meaning that if a machine fails, it can be removed and replaced, without any consequent loss of data, and without interrupting normal operation. Managing your cluster has been made as simple as possible. Use any machine in the cluster to manage all others: update TKUs, add credentials and scans, and even upgrade the product itself from a single place. Regardless of data center size or complexity, BMC Discovery delivers a refreshed view of your data center as often as needed. Clustering delivers powerful, actionable data center insight in the shortest possible time:

  • Leverages new appliance clustering technology
  • No scanning limits – just add hardware
  • Transparent cluster management
  • Fault tolerance to manage hardware failures
  • Highly scalable end-user UI

Related topics

BMC Discovery

Key concepts

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