|CMDB Workshop User Guide|
This user guide describes CMDB Workshop version 2.0 and later.
Installing CMDB WorkshopIf you download the zip file version then there is no install process. Just unzip the file and start to run. Otherwise follow the instruction of the installer.
System RequirementsCMDB Workshop is written in 100% Java. The memory requirement depends on the size of CMDB data you are viewing and editing.
CMDB Analyzer uses CMDB SDK version 2.0.
The following diagram describes function areas in CMDB Workshop main window:
A CMDB Workshop project is a folder in file system that contains views. There are different types of views:
There are two types of CMDB Workshop project you can create:
Notes: Instances creation tools are only available after the current active project has retrieved the class definition information. For on-line project it means that it has made the first successful connection to the server.
Right-mouse click on the project and then select "Remove" to remove the project from the project panel. The project folder and all its content are not deleted from the file system. You can later open the project again using "Open Project" option.
Tip: To change project settings after a project has been created, right-mouse click on a project in Project Panel and then select "Preference...".
A dataset view is where you look and edit CI and relationship instances. If the view belongs to a on-line project, you can also commit instances changes.
View Dataset ID
Each dataset view is assigned a dataset ID for identity purpose. For views belong to a on-line project, the dataset ID is used to identify the server dataset where you are going to commit instance changes. When a new instance is created, its dataset ID attribute value is set to the view dataset ID. You can change view dataset ID by selecting "Change Dataset ID" menu option.
Notes: When you are editing instances, no changes are committed to CMDB server until you commit the changes explicitly.
Common Editing Tasks
See section Working with Instance Creation Tools
See section Editing Instance Attributes
Only tasks that involve instance creation and deleting are undoable.
Save instances to a file.
Delete all instances
See section Committing Instance Changes
When dataset view instance attributes are refreshed, their values are overridden by attributes retrieved from server dataset. You can refresh one instance, or refresh the selected instances, or refresh all instances in dataset view.
Notes: The difference of importing instances vs. pasting instances is that imported instances keep their original instance IDs while pasting assigns new instance IDs for created instances.
You use instance creation tools to create CI instances and relationships.
Notes: Instance creation tools are tied to the current active project. When a dataset view window is activated, the project associated with the view is the current active project, thus the contents in the instance creation tools are updated accordingly.
Using CI Class Tool
Mouse click on a class and then click in a dataset view to create an CI instance in the dataset view. You can organize CDM classes in a hierarchical tree or in a sortable flat table.
Using Relationship Tool
Mouse click on a relationship class and then click a CI instance in the dataset view to initiate the creation of a relationship. Click on another CI instance builds a new relationship from source instance to destination instance. CMDB relationships have cardinality constrains and source-destination class type constrains. Those constrains are validated before the new relationship is created.
Using CI Map Tool
Mouse click on an entry in the CI Map table and then click in a dataset view to create an CI instance. The new instance has pre-fined attribute fields.
Using Template Tool
Mouse click on a template and then click in a dataset view to create a group of instances and relationships defined by the template. See section Working with Templates for more detail.
A template is a pre-defined group of CI instances and relationships that models a particular system. For example, a "computer system" that includes both hardware and software components, a "oracle database", a "virtual system" and a "business system". Templates enable you to raptly build accurate CI instances and relationships. You can also create a graph and export it as a template by selecting "Export As Template" menu in dataset view toolbar. To delete a template, select the template and click the "Delete Template" button in the template toolbar.
Click a CI or relationship instance and all its attributes are listed in the Attribute Edit Panel.
Not all attributes are editable. System attributes, display-only attributes, hidden attributes are those that cannot be edited and are grayed out in the Attribute Edit Panel. Attributes such as instancesId, reconciliationId, classId, datasetId are maintained by the application or have internal constraint and thus are not allowed to edit directly. These attribute entries are not grayed out in the Attribute Edit Panel but still can be edited. To edit an attribute, click the table cell in "Attribute Value" column.
The action of reconnecting (to different CI instances) one or both end points of a relationship is called "Rewiring". To rewire a relationship, you right-mouse click on it and select either "Rewire Outbound" or "Rewire Inbound" menu option. "Rewire Outbound" allows you to break the outbound connection and pick a new outbound instance. "Rewire Inbound" allows you to change inbound instance. Relationship end point class type constraint and cardinality constraint are verified again when the relationship is reconnected.
Importing From XML Instance File
You can import instance data from a xml instance file. Xml instance file can be generated by:
Importing From CSV FileYou can also import instance data from CSV file.
Steps to import instance data from CSV file:
Step One - Open CSV file to load data.
Step Two - If the CSV file contains instances that belong to different classes, use "Split" button to separate instances into different tables according to classes.
Step Three - Select the class that instances belong to.
Step Four - Map columns to the class attribute fields, or you can apply a saved mapping template.
Step Five - Click "Validate" button to validate the data in the mapped column.
Step Six - Click "Import" button to import the instances in the table. If there are multiple tables, always import CI instances first then import Relationship instances.
Importing From Server Dataset (On-line project only)
To import instance data from a dataset, specify the dataset name and select an instance filter (the default filter will retrieve all instances in the dataset). The dataset id attribute in the imported instances will be reset to the dataset id of the current view.
You can export instance data to a xml file. You can also export class definitions and class UI definitions. You can export the dataset view to a gif image file.
Committing instance changes is only available for on-line project.
You select "Commit" menu in the dataset view to commit instance changes.
Tips: Committing frequently on a small number of changes is a good practice over committing a large number of instance changes at last minute. Keeping the overall instance numbers as small as possible to improve the performance.
Tips: Use instance filter or other ways to keep the overall instance number in a dataset view as small as possible to improve clarity and increase performance.
You need to go though the following steps to commit instance changes.
Step One - Setting options for detecting instance changes
Dataset view can detect four types of instance changes by comparing instances in the dataset view with instances in the server dataset. Each instance change type associates with an action which will do the work to commit the change.
What Changed: new instances are detected by comparing instance id
What Changed: instances are marked deleted in dataset view and their
ids are found in server dataset
What Changed: instance attributes are different
What Changed: instances have different relationships
You have options to disable one or more change detections in the Commit dialog.
Tips: If you are sure there is no attribute changes or rewiring (rewiring detection is done by detecting attribute change), you can turn off attribute detection because it is a time-consuming task especially if you have a large number of instances to detect. Even if there are attribute changes you could commit Create and Delete first by turning off attribute detection and commit Update and Rewire later.
Step Two - Detecting instance changes (Scan)
The screenshot below shows the result of instance change scanning:
Step Three - Commit changes
The commit status column in Detail table will be updated as well as the Succeed and Failed column in Summary table to give you a clear picture of what actions succeed and what actions have failed. You can also click the action entry to highlight the correspond instance in the dataset view.
Tips: Use another dataset view to verify the changes you just committed.