DRYiCE ROAR R7

With this release, we have introduced new features to enable the processing of manual and automatic jobs from ROAR’s online storage, compute and display consolidated RUs on a single page, and provide a unified view of all uploaded files and their current job status/activity. Please find the same put forward in this release note.

Normalization

The Normalization module validates incoming data and replaces the alternate representations of CI information with standard values. Following are the feature enhancements in this module:

• A new capability has been introduced to enable users to run automation and manual jobs by using files stored in ROAR’s online storage as the input source instead of always uploading files from the local machine or importing them through integrations. This will enable users to preload files before running the jobs, increasing the efficiency of the overall process.
• Now, while uploading input records files in advance into ROAR’s online storage or while running an ‘Import & Validate’ job and waiting for its completion, users will be displayed dynamic messages on the UI related to new product enhancements. These messages will keep users abreast of new and upcoming features in the product and help to drive their adoption.
• Now, users will be able to cancel an ‘Import and Validate’ job, which has already been initiated during manual job processing. This will give them the flexibility to abort a job in progress, if required, and not have to wait for its completion.
• Now, while multiple input files are being uploaded into ROAR’s online storage, the ‘Status’ field on the dashboard showing the current job processing activity/status will include details on all uploaded files for which the ‘Import and Validate’ job has already begun and also those files in the job queue. This will enable users to check the current job processing activity for the uploaded files and schedule future job processing accurately.
• Now, the input records that have been rejected during the validation stage will be pushed into ROAR’s database with a flag/tag identifying them as rejected records. These records will not be used for processing but will be available for end-users to view/download from the ‘Import & Validate’ page giving them visibility of the rejected records as well.
• The list of operators in the qualification rule has been enhanced with the inclusion of the additional operators ‘Contains’ and ‘Matches Expression’, providing users with an additional choice of operators to qualify data even more accurately.
• Now, while using online storage as an input source for ‘Import and Validate’, users will be displayed the dynamic progress status of each file on the same page itself. This will help users stay informed about the real time status of the job progress.

Aggregation

The Aggregation module identifies potential records from diverse sources and merges them to remove duplication and create a clean and accurate record database called the Golden Dataset. The following feature enhancement has been introduced in this module:

• Now upon choosing an attribute while creating class prioritization rules, it will be mandatory to select an operator and associated value to save the rule. This increases the efficacy of the rule.

Reconciliation

• The RU calculation capability has been enhanced to support the calculation and display of consolidated RU counts for all classes on the same page instead of viewing them class-wise. Once computed, users will be able to download the report from the same page. This enhancement will enable users to save time and effort spent on downloading RU count for each class individually and manually consolidate them.
• The pop-up, which allows users to download reports and files on Resource Units (RUs) after RU computation, will now include ‘RU Name’, ‘Run Date’ and ‘Report Creation Date’ columns. This will give users a preliminary glimpse of the report being downloaded.
• A new reporting template has been introduced on the ‘Calculate RU’ form to calculate and display RU counts and the associated currency. This increases the reporting capabilities inbuilt in ROAR.

Overall product enhancements

• A new capability has been introduced to schedule jobs in advance so that they can be run automatically on the scheduled date and time. This will allow users to schedule jobs ahead of time as per their convenience.
• Now, upon the success or failure of ‘Import and Validate’, ‘Normalization’, ‘Identification’ and ‘Merge’ jobs, email notifications will be triggered to users to inform them about the job status. These notifications will alert users even if they are not logged into ROAR, enabling them to take any action necessary.
• Now, the automation dashboard will display the detailed status of all the files that have been uploaded into online storage and for which the ‘Import and Validate’ job has been initiated. This will give visibility into the status of input record files uploaded and being processed.
• Now, upon initiating a ‘Purge Data’ activity on jobs that have not been performed and do not exist in ROAR’s records, a ‘No Data’ message will be displayed on user’s screen. This will alert users that the purge activity was not executed because the records did not exist.
• Now, if multiple files have been uploaded for processing onto ROAR, users will be able to view the detailed processing history of each of the files uploaded by them. This will keep users informed about the status of every individual file that they uploaded.
•  Now an error message will be displayed upon trying to initiate a new job process while its immediate previous or next process is being executed according to the normal job processing flow consisting of ‘Import & Validate’, ‘Normalization’, ‘Identification’ and ‘Merge’. This will reduce the chances of errors occurring during job processing.
• A new capability has been introduced in ROAR to identity and differentiate failed manual jobs from new job processing requests in the queue and execute new job requests instead of reattempting to execute failed jobs. This will optimize ROAR resources.
• A new capability has been introduced to retain the last selection of filters used to download a report or initiate any action and not auto-reset them on completion of the activity till the users remain on the same page. This will spare users the trouble of setting the filters after every activity while they continue to work on the same page.

Connectors

Ready to use connectors for exchange of data between ROAR and other software applications

• A dedicated connector has been introduced to automate the process of importing records into ROAR from Zenoss, eliminating delays from manually gathering and populating data into ROAR.
• A dedicated connector has been introduced to automate the process of importing data from Microsoft SCOM into ROAR, saving time and effort needed to gather and populate the data manually into ROAR.
• A connector has been introduced to automate the process of importing .csv files stored on the Amazon cloud containing the necessary details to onboard a company and its users onto ROAR, eliminating the time and effort needed in manually populating the data into ROAR.
• A dedicated connector has been introduced to automate the process of importing data from Nimsoft into ROAR, eliminating the need to populate data into ROAR manually.
• A new connector has been introduced to automate the process of importing data from SolarWinds into ROAR, saving time and effort needed in manually gathering and populating data into ROAR.
• A new connector has been introduced to export the Golden Dataset output from ROAR to ServiceNow CMDB, saving time and effort on manual updates.

Defects

• We have fixed the critical risk vulnerabilities identified in the security scan findings performed during September 2021.

DRYiCE ROAR creates a single source of truth by processing data in the IT environment from multiple IT & OT tools in the enterprise, which can drive the accuracy of downstream applications by removing data reliability issues.

For product-related inquiries, please reach us at [email protected]