Release Update 01/2026
Unified Insights
Multi-Project Visibility for Teams and Projects in Investment Spectrum Dashboard
Teams can analyze time investments by individual resources or by project, with dynamic filtering and visual cues to spotlight focus areas, both within and beyond selected hierarchies.
Key Highlights:
Dual-View Pivot Tables: Two intuitive tables, By Resource and By Project, reveal where team members are investing time. Track Employee Name, JIRA Project Name, Total Issues Assigned, Resource Allocation percentages, Issue Type breakdown.
Smart Hierarchy Filtering: Basic Filters show core views with color-coded rows. Workday Hierarchy unlocks advanced details like Resource Type, Vendor, Geolocation, and leadership breakdowns.
Cross-Filter Consistency: Both filter types display both tables, ensuring comprehensive visibility into work distribution regardless of selections. Expand/collapse rows for drill-down for quick scans.
Branch-Level Filtering Support for Deployment Frequency & Lead Time for Changes KPI
Branch filtering brings granular control to Deployment Frequency (DF) and Lead Time for Changes (LTFC) group mapping. Teams can scope dashboard data to specific branches across all supported tools, enabling precise analysis of pipeline performance at the branch level. Key Highlights:
Dynamic Branch Selection: Branch filter lists available branches based on the selected tool and data availability.
Smart Selection Controls: Includes "Select All," "Deselect All," and "Reset" options for efficient multi-branch management.
Filtered Dashboard Insights: Applied branch selections automatically refine DF & LTFC group data, delivering branch-specific DORA metrics and performance trends.
GitHub Copilot Report Enhancements
Copilot Impact Charts now support direct exports of Lines of Code and Commit metrics. Teams can download data for analysis, presentations, and stakeholder reviews while preserving aggregation context.
Key Highlights:
Lines of Code Export: You can now export the "Lines of Code Suggested & Accepted" data from Impact Charts. The export respects all applied filters and date ranges and includes columns specifying whether the aggregation method is SUM or AVG.
Commit Metrics Export: The export of "Commit & Copilot Lines of Code" will retain the current filter and date range. This export will clearly indicate whether the data represents the SUM or AVG of the metrics.
Copilot Dashboards offer full widget enable/disable controls for personalized views. Users can tailor metrics to focus on the most relevant KPIs across standard and custom dashboards.
Key Highlights:
Granular Widget Management: Toggle visibility added for the following key widgets: Developer Usage, Copilot Usage, Copilot Adoption, Impact Chart, Developer Activity, Acceptance Rate, Suggestion Retention Rate, and Copilot Contribution Report.
Personalized Dashboard Views: Enable only the metrics that matter for your team, optimize for executive summaries, engineering reviews, or adoption tracking.
Enhanced Copilot Metrics View by Organization and Team
The Copilot dashboard KPIs provide an expanded tabular metrics view that enables users to compare performance across multiple organizations and teams in a single, unified view.
Key Highlights:
Multi-Organization and Team Comparison: When multiple organizations, or all organizations are selected, Copilot displays metrics in a structured tabular format, allowing side-by-side comparison across organizations and teams within a single view.
Expanded Metrics Visibility Across All Widgets: The tabular comparison view is available across all Copilot dashboard widgets, ensuring consistent insights regardless of the metric being analyzed.
Flexible Organization and Team Selection: Users can dynamically select and switch between organization-level and team-level views within the table, enabling deeper analysis at different levels of the organizational hierarchy.
Exportable Metrics for Offline Analysis: Tabular metric views can be exported, allowing users to share insights and perform offline analysis.
Analyze Sprint Velocity Contributor Delivery Insights Using Reasoning AI
Hummingbird AI Sprint Velocity Reasoning Agent delivers granular visibility into sprint points delivered by contributor and sprint. Track performance against planned timelines, including post-sprint resolutions for complete velocity analysis.
Key Highlights:
Per-Contributor Sprint Points: View exact points delivered by each team member across sprints, with clear attribution of completed work.
Sprint-Timeline Tracking: Displays Sprint End Date vs. Planned Sprint End Date, plus issues resolved within 1-2 days post-sprint for accurate velocity calculation.
Comprehensive Velocity View: Combines in-sprint delivery with graceful post-sprint completions, providing true picture of team throughput and deadline adherence.
Expanded AI Code Comparison with GitLab and Amazon Q
Opsera expands its AI Code Comparison Dashboard to include GitLab AI and Amazon Q, enabling side-by-side evaluation of AI coding assistants alongside Windsurf, Cursor, and GitHub Copilot.
Key Highlights
GitLab AI and Amazon Q Support: Compare GitLab AI and Amazon Q with other AI coding tools across adoption, productivity, and impact metrics in a unified dashboard.
Leadership Dashboard Improvements: Adoption Rate is now the primary leadership metric, with Hours Saved available through drill-down for clearer executive insights.
Updated License Cost Accuracy: License costs have been updated to reflect current pricing: Windsurf: $15/user/month, Cursor: $20/user/month, GitHub Copilot: $4/user/month, GitLab AI: $29/user/month and Amazon Q: $20/user/month.
Clear License Usage Visibility: Adoption metrics now distinguish Allocated Licenses vs Active Users, with a new Usage tab added under Adoption & Developer Experience.
Enhanced Metric Organization and Filters: Developer Productivity is now the first tab under Commit Integration Rate. Users can enable or disable Commit Integration Rate, Multi-Dimensional Impact, and Throughput based on data availability
Introducing Model and Language Usage Insights Comparison in AI Code Comparison Dashboard
The AI Code Comparison Dashboard includes model-level and language-level comparison views, enabling teams to understand how AI code assistants and their underlying models are used across tools and programming languages.
Key Highlights:
Model Usage by AI Tool: A new comparison matrix shows adoption rate, total LOC suggested and accepted, top and least used languages, and total users for each model within every AI coding assistant.
Language-Centric Tool and Model Comparison: A language-first view highlights which AI tools and models are most frequently used for specific programming languages, helping teams standardize on the most effective tool for each language ecosystem.
Hummingbird AI Recommendations: Hummingbird AI analyzes usage patterns across models and languages to recommend optimal tool and model combinations and identify opportunities to decommission underutilized AI tools.
Additional Capabilities
Year context added to KPI charts and tooltips KPI Overview charts display the relevant year directly within tooltips for both DORA and DevEx metrics. This enhancement provides immediate time context when hovering over performance tiles, making it easier to interpret trends, compare results across periods, and improve the accuracy of reporting and analysis.
SDLC
Bulk Enable/Disable Pipeline Steps from Summary View
Users with Edit permissions can bulk enable or disable multiple pipeline steps directly from the Summary view. This allows teams to manage complex pipelines more efficiently.
Key Highlights:
RBAC-Controlled Bulk Actions: Select multiple Pipeline steps to perform Enable Selected, Disable Selected, Enable All, or Disable All actions.
Visual Indication: Disabled steps are clearly grayed out in Summary and Workflow views.
Template Compatibility: Pipeline Templates retain step enable/disable states.
Dynamic Artifact Resolution for Parent–Child Pipeline Approvals
Approval steps in parent pipelines now dynamically resolve and show deployment artifacts from child pipelines. This capability allows teams to get full visibility into image names/tags before approving the Pipeline workflow.
Key Highlights:
Cross-Pipeline Artifact Discovery: Approval dialogs now show exact deployment artifacts passed from child builds to deployments.
Smart Variable Resolution: Dynamic variables are resolved with clear indicators.
Multi-Child Support: Displays artifacts from multiple child pipelines in a table with source pipeline, build step, and target environment.
Introducing Customizable IDP Workflows
The IDP module includes a "Create Your Own" custom workflow feature, which enhances teams' control, visibility, and flexibility when designing and running automation. This new capability allows users to build and execute workflows that integrate both Opsera-supported actions and existing IDP functionalities.
Key Highlights:
One-Click Jenkins Job Execution:
Jenkins IDP Tile: Run Jenkins jobs instantly from Opsera without switching tools.
Select and Execute Easily: Choose any configured Jenkins instance and job from the catalog.
Full Visibility: Trigger jobs with one click and see execution status and results right in the platform.
Integrated Orchestration: Include Jenkins job runs directly within broader pipeline workflows.
Flexible Automation Design: Create custom IDP workflows tailored to your team’s delivery and deployment needs. Integrate diverse tools and automate complex actions end-to-end.
Unified Orchestration Experience: A redesigned interface and workflow catalog make it easier to build, run, and monitor workflows. Output log visibility improves tracking and troubleshooting.
Seamless Tool Integration: The Jenkins integration tile expands IDP compatibility, allowing streamlined job selection and execution alongside other tools.
Additional Capabilities
Downloadable Test Reports for JUnit, NUnit, xUnit, and Cypress
Teams can instantly access test results for JUnit, NUnit, Xunit, and Cypress Pipeline steps for analysis, debugging, and stakeholder reviews. Download complete reports directly from the respective pipeline execution views.
Salesforce
Automated Salesforce Package XML Generation in VS Code
Opsera launches VSCode plugin, automating Salesforce package.xml generation. This capability streamlines Salesforce deployment preparation by automating the generation of package.xml and destructiveChanges.xml files directly within the developer IDE. By analyzing Git commits and Salesforce metadata changes, the plugin removes manual component selection and reduces deployment errors.
Key Highlights:
Commit-Driven Package XML Generation: Automatically analyzes selected commit ranges to identify valid Salesforce metadata changes, including Apex classes, triggers, and other supported components and generates deploy-ready package.xml files with optional destructiveChanges.xml for deletions.
Manual and Automatic Analysis Modes: Supports both manual commit range selection for deployments and automatic analysis triggered after commits are pushed to the remote repository, ensuring accurate and up-to-date package tracking.
Seamless Jira Mapping via Opsera: When Jira integration is configured in Opsera, issue mapping is handled centrally by the platform. The VS Code plugin automatically inherits this mapping, ensuring consistent traceability between commits, packages, and Jira issues without additional plugin configuration.
Multi-Repository and Workspace Flexibility: Analyze commits across GitHub, GitLab, or Bitbucket repositories and work with the current VS Code workspace or alternate local Salesforce repositories as needed.
Simplified Access to Salesforce Analytics with Sectioned Dashboard Insights
The Salesforce landing page now features a dedicated Dashboard Insights area that organizes key analytics into clear, purpose-built sections.
Key Highlights:
Direct Access to Key Metrics: Instead of a generic insights page, users can navigate straight to the metrics that matter most, including Deployment, Cycle Time, Code Scan, and User Story analytics.
Tailored Insight Experience: Each insights section delivers relevant navigation and content, making it easy to explore performance trends, monitor quality signals, and build or view dashboards from a unified analytics experience.
Last updated