Release Update 02/09/2026

Unified Insights

Introducing Git Custodian Issues Trend & Risk Insights in the Code Reliability Dashboard

The Git Custodian KPI in the Code Reliability Dashboard provides time-based visibility into security and quality issues detected across repositories, branches, and pipelines.

Key Highlights:

• Issues Trend Over Time: A unified trend view tracks Created, Open, and Resolved Issues across scanned repositories. This enables teams to understand how risk evolves over time and quickly spot spikes or reductions in issue activity.

• Project, Branch, and Pipeline Risk Analysis: Drill-down views compare issue distribution across projects, branches, and pipelines, helping teams identify high-risk areas, prioritize remediation efforts, and focus on pipelines or branches contributing most to overall risk.

• Comprehensive Issues Investigation Table: A detailed issues table lists individual findings at scan level, including pipeline execution details, project and branch context, scanner information, and resolution status. Teams can filter hierarchically, export results, and download issues per pipeline run for faster triage and reporting.

Introducing New Insights for the Cursor Dashboard

Users can now view a new set of KPIs and reports on the Cursor dashboard, including developer activity, Cursor usage reports, and the Cursor Contribution report with export capabilities. These additions provide visibility into adoption rate, AI-assisted coding impact, and resource utilization.

New Metrics Added:

• Adoption: Shows the number of developers actively using Cursor during the selected period.

• Cursor PR Percentage: Displays the percentage of pull requests created or merged using Cursor-generated code.

• Average Time PR Open to Merge: Measures the average time taken to merge Cursor-assisted pull requests.

• Task Throughput: Indicates the number of tasks completed or tracked with Cursor assistance.

• Heavy Users Percentage: Shows the percentage of developers engaging with Cursor frequently.

• Total Licensed Users: The total number of developers with an active Cursor license.

• Active Users: Licensed developers who used Cursor within the selected date range.

• User Adoption Rate: The percentage of licensed users who were active during the selected period.

• Chat vs Users: Visibility into how developers engage with Cursor across Chat and IDE apps.

• Cursor Usage Report: A summary of active and inactive users to analyze engagement over time and track organization-wide adoption.

• Cursor Contribution Report: A summary showing developer usage and contribution, such as suggested vs accepted lines, acceptance rate, and contribution rate.

Visualizations & Export Options:

• New line graphs for developer activity, pull requests, task throughput, and impact.

• Improved line graphs for adoption and acceptance rates.

• Daily and weekly views added for adoption and developer activity.

• Bar charts and heatmaps were introduced to visualize developer activity.

• KPI tables are provided with Export for usage metrics and contribution reports.

Enhanced Filtering:

• All dashboard views now support advanced filters, such as Workday, Geography, and Vendor.

Introducing Productivity Columns in Sprint Velocity Dashboard

To help leaders quickly understand delivery efficiency across teams, new productivity insights have been added to the Sprint Velocity report. These updates enhance the existing view with clearer context on how work is delivered, without introducing new dashboards or workflows.

Key Highlights

• Clear Productivity Indicators: Two new columns now appear in the Sprint Velocity table.

  • Productivity (Overall): Shows how much work is delivered per contributor, based on Jira assignees.

  • Productivity (Mainstream): Shows how much work is delivered per core contributor, based on mainstream users assigned to work items.

• Consistent Numbers Across Filters: Productivity values automatically adjust based on selected filters such as date range or organization level, so leaders always see accurate, up-to-date summaries.

Platform

Introducing a Centralized Pipeline Approval Experience with a Notification Interface

A Notification Center is introduced for users to view, search, and act on pipeline approvals directly from any point inside the platform. The capability supports both single and parallel approval steps with real-time updates.

Key Highlights:

• Centralized Notification Hub in the Navbar:

  • A notification capability is introduced displaying a real-time badge count of pending approvals. Clicking the bell opens a dedicated notification panel, giving users immediate access to approvals without navigating away from their current workflow.

  • The notification panel presents a structured layout with a Pending Approvals section and recent activity context.

  • Each pipeline entry displays approval details, trigger information, timestamps, and clear action buttons.

• Parallel Approval Steps with Bulk Actions: Pipelines with multiple parallel approval steps are clearly grouped for users to select one or multiple steps. All steps are selected by default for faster bulk approvals.

Support for Creating and Referencing Global Parameters Through API

The Global Parameters API allows users to create and manage global parameters where teams can define reusable Pipeline configuration values. The capability makes it easy to automate environment-specific settings, secrets, and shared configurations.

Key Highlights:

• Create Global Parameters via API: Users can create global parameters programmatically by providing a name, value, scope, and optional details.

• Use Global Parameters in Pipeline Creation: Each global parameter returns a unique ID that can be referenced in the pipeline creation API, allowing pipelines to reuse global parameters consistently across environments.

Introducing Proactive Notifications for Pipeline and Task Schedulers

Pipeline and task schedulers are now proactively monitored for configuration changes, missed executions, and failures. Users and administrators receive real-time notifications across configured channels. This helps prevent silent failures, enables faster issue detection, and reduces manual monitoring. Key Highlights:

• Scheduler Change Notifications: Receive alerts on user-configured communication channels, such as Email or Slack, when a pipeline or task scheduler is modified, disabled, or reconfigured.

  
• Missed Execution Alerts: Active schedulers that fail to run on time trigger alerts within five minutes. Notifications are sent to owners and administrators with key run information.

• Critical Scheduler Monitoring: Git Custodian triggers alerts to internal operations channels on missed, delayed, or failed runs.

• Comprehensive Audit Logs: All scheduler actions (Create, Read, Update, and Delete) are captured with the user, timestamp, and old/new values to support traceability.

Capabilities to DataOps Wizard Flow

Support for Resource Type Selection in Databricks DataOps CodeGen Flow

The DataOps CodeGen workflow has been enhanced to support explicit Resource Type selection, giving users greater flexibility and control when generating Databricks YAML configurations.

Supported resource types include:

• Jobs

• Pipelines

• Clusters

• SQL Warehouses

• Secret Scopes

Based on the selected resource types, the flow dynamically adapts to capture only the relevant inputs and parameters required for YAML generation. Template options are available for resource types like Jobs and Pipelines, allowing predefined configurations during DABS (Databricks Asset Bundle Specification) YAML generation.

Enhanced Template Addition

To streamline complex YAML creation, users can browse and select from a library of templates to instantly include in their new configuration file.

Predefined Configurations: Template options are available for key resource types like Jobs and Pipelines. Users can rapidly inject specific blocks during DABS (Databricks Asset Bundle Specification) YAML generation. By leveraging predefined, standardized templates, developers ensure consistent compliance with organizational best practices.

Support for User-Defined Git Commit Messages in DataOps Code Generation

DataOps Code Generation now supports user-defined git commit messages during the YAML Generation step. Users can enter a custom commit message directly in the Databricks YAML Editor view before committing generated code to the repository.

This capability ensures that commits generated by the platform comply with repository-specific commit policies, reducing commit failures.

Capability to Re-Run IDP Jenkins Jobs Using Existing Configuration

Users can quickly rerun IDP Jenkins jobs using the existing setup, reducing duplication and making repeated runs simpler.

Key Highlights:

• Single Configuration, Multiple Runs: Once an IDP Jenkins job is configured, users can now re-execute the same job multiple times using the original configuration and job name. This removes duplication and simplifies repeated job execution.

• Rerun Action: A Rerun action is available for previously created IDP Jenkins run tasks. Selecting this action triggers a new Jenkins build using the same configuration as the original run

• The Rerun option is visible in:

  • Job details view

  • Job execution history

• Preserved Execution History: Each rerun is recorded as a separate execution in the job’s history, including: Unique run ID or build number, Execution timestamp, Run status and Triggered by details.