January 09, 2024 – Application Update

We’re excited to kick off the new year with a feature-packed update that enhances your experience with DNIF HYPERCLOUD. Explore the latest improvements and features below:

WHAT’S NEW

DASHBOARD PRIVACY SETTINGS: PUBLIC FOR ALL, PRIVATE FOR SOME

• Dashboards are now categorized into two types: public and private.
• Public and private dashboards allow users to tailor their views and collaborate more effectively with team members. Public dashboards can be shared across the SOC for collective visibility, while private dashboards enable selective sharing for sensitive information.
• View-only access to dashboards adds a layer of access control, allowing security engineers to grant specific users read-only access to sensitive dashboards. This ensures that critical information is shared with the right personnel while preventing unauthorized modifications.
  

TAILOR YOUR VIEW: EFFORTLESS DATA FILTERING ACROSS PAGES

• The ability to tailor views on pages such as Dashboards, Cases, Workbooks, and more allows users to customize their analysis based on specific criteria.
• Users can adapt their views to match the context of their investigations, enhancing the relevance of the information presented.

READABLE LOGS, HAPPY USERS: A PRETTY SEARCH EXPERIENCE

The pretty view of log events in search results enhances the legibility of log data, making it easier for users to read and understand raw log information. This contributes to a more user-friendly and efficient log exploration experience.

SWIFT ANALYSIS: QUICK FILTERS AND AGGREGATES AT YOUR FINGERTIPS

• Users can swiftly add a field to filters and/or aggregate functions when exploring search results of a query.
• Enhances the flexibility and efficiency of data analysis.

CONNECTED CONTEXTS: STREAM-BASED WORKBOOK MANAGEMENT

• At-a-glance visibility into the number of active and total workbooks associated with each stream, aiding in quick assessment.

QUERY ECONOMICS: ANTICIPATE QUERY COSTS FOR OPTIMAL SEARCH PERFORMANCE

• Users can preview the volume of data to be scanned before executing a query.
• The ability to forecast query volumes aids in crafting precise queries tailored to the desired scope.
• Users can achieve a more targeted analysis, focusing on the relevant data subsets without unnecessary data scans.