Release Update 02/23/2026
Unified Insights
Introducing the Snaplogic Insights Dashboard with Infrastructure and Capacity Planning KPIs
Snaplogic Insights has been introduced as a new dashboard category in the Outer Loop Dashboards list. It provides centralized visibility into infrastructure health and resource utilization for Snaplogic environments, enabling infrastructure planning and operational decision-making.
Key Highlights
Infrastructure Health Monitoring: Running and down node counts, node availability, failure rate, and overall health score provide consolidated visibility into system status.
Capacity and Resource Utilization Insights: Slot utilization, available capacity, capacity headroom, and memory allocation metrics enable evaluation of infrastructure capacity and utilization levels.
Snaplex Status Reporting: Status distribution and Snaplex availability SLA metrics provide environment-level visibility into operational states and uptime measurement.
Adding Visibility in Copilot Insights on Contributions made by Agents through GitHub Copilot
The Copilot Insights dashboard is updated to reflect data from the latest GitHub Copilot APIs. This new version separates agent-related contributions across widgets, giving users clearer visibility into how agents contribute to suggestions and accepted code, and commits historical data.
Key Highlights
Track Agent Contributions: Agent-related activity is now displayed independently within each applicable widget. This allows teams to clearly distinguish between standard Copilot usage and agent-driven contributions for more precise analysis.
Impact KPI Organized into Individual Widgets: The metrics Suggestions vs. Acceptances and Lines of Code (LOC) Suggested vs. Accepted have been separated into independent widgets to improve clarity and allow for focused, individual analysis.
Copilot Usage Adoption Panel: The adoption panel now includes new agent line metrics, which are Agent Lines Accepted to Add and Agent Lines Accepted to Delete.
Improved Copilot Dashboard with Role-Based Export Entitlements
PII compliance controls have been implemented for the Copilot Dashboard to ensure that no personally identifiable information is exposed. The dashboard now displays only aggregated metrics, and export functionality in the Copilot Usage tab is governed by entitlement settings.
Key Highlights
Aggregated Metrics Only: All Copilot dashboard views now display only aggregated organization-level metrics. User-level identifiable information is not shown.
Role-Based Export Controls: Export options in the Copilot Usage section are governed by entitlements to prevent unauthorized access to detailed user data.
PII Access Entitlement Setting: A new toggle in Organization Settings enables administrators to control access to Copilot dashboard exports through the PII Access entitlement.
Support for Nexus Artifactory in Artifact Statistics KPI (Devex Dashboard)
The Artifact Statistics KPI in the Devex dashboard now supports Nexus Artifactory as an additional data source. Artifact tool mapping enables Nexus repositories to be associated with configured tools, and the KPI data is reflected in the existing Artifacts table view.
Key Highlights
Artifact tool mapping capability was added to support association of Nexus repositories with configured tools.
Artifact Statistics support has been extended beyond the previously supported JFrog source.
Nexus artifact data is now populated within the existing Artifacts list view used for Artifact Statistics KPI.
Enhanced Pipeline Metrics in DevEx Dashboard
Pipeline health metrics views have been distinguished into Summary View and Pipeline Details View within the Pipeline Statistics KPI on the DevEx dashboard. The update introduces monthly execution visibility, repository-level execution insights, and run duration metrics, improving clarity of pipeline performance trends.
New Metrics Added
Unique Pipeline Runs: Displays the number of unique pipeline executions per month.
Total Pipeline Runs: Shows the total number of pipeline executions per month.
Average Successful Run Duration: Displays the average duration for successful pipeline executions.
Visualizations & Export Options
Bar charts are added for Month vs Unique Pipeline Runs and Month vs Total Pipeline Runs, displayed by month irrespective of the selected date range.
A table view is added to list repositories that were triggered, including Total Pipelines and Total Runs, with column-level sorting.
A table view is added in the Summary View, displaying workflow-level metrics including run counts, duration statistics, and success and failure details.
All tables across the Summary and Pipeline Details views provide export functionality in the new UI.
Improved Hummingbird AI Reasoning for Sprint Velocity Dashboard
The reasoning logic for Hummingbird AI has been updated to improve the accuracy of sprint velocity analysis across leadership summaries and contributor views. The update enhances sprint performance interpretation, risk identification, and forecasting using percentile-based predictions.
Key Highlights
Enhanced Sprint Performance Analysis: Consolidated sprint summaries are generated covering delivery performance, scope changes, Say/Do metrics, velocity trends, contributor participation, and predictability impact, including unplanned work.
Refined Risk Identification: Risks, bottlenecks, spillover patterns, and planning concerns are identified with recommendations for upcoming sprints.
Predictive Forecast with Percentile Analysis: Sprint forecasts are generated using contributor data based on current and recommended flow, with P70 and P90 percentile analysis for future sprint projections.
New Tool Integrations to AI Code Comparison Insights
GitLab and AmazonQ have been added to the Languages Comparison Matrix and Adoption Comparison KPIs in AI Code Comparison. The update also introduces standardized value states and informational messaging to improve clarity when tool data is unavailable or unsupported.
Key Highlights
Standardized Value States: Defined display values are introduced to represent supported but unavailable data, unsupported model fields, and unavailable language splits.
Informational Messaging: An info note is displayed at the bottom of the view when a data field is not supported by the selected tool.
Extended KPI Coverage: The Languages Comparison Matrix and Adoption Comparison now include additional tool data for comparative analysis.
Support for Azure Boards in Tool Mappings for DORA Metrics
Azure Boards tool integration has been added to Groups Mapping configuration for CFR, CTFC, and MTTR KPIs. This enables users to configure filters and map Azure Boards data to these metrics, expanding tool coverage within Insights.
Key Highlights
Azure Boards is now available as a supported tool option in Groups Mapping for CFR, CTFC, and MTTR configuration.
Users can configure filters using Azure Boards data to map records to the respective KPIs.
Platform
Capabilities for Hummingbird AI
Hummingbird AI automatically retrieves console logs from failed pipeline steps to provide instant, log-based root cause analysis. This capability eliminates manual log hunting and delivers precise, actionable remediation.
Key Highlights
Automated Log Extraction: The AI identifies failed steps, pulls relevant logs from the crash and preceding tasks, and extracts critical error messages or stack traces.
Root Cause Detection: By correlating log data with pipeline metadata, the agent identifies specific patterns to pinpoint the exact source of the break.
Structured Remediation: Every failure is presented in a standardized format:
Failure Reason: A concise summary of the crash.
Log Evidence: The specific lines confirming the error.
Actionable Fix: Step-by-step instructions to resolve the issue.
Hummingbird AI protects chat history using role-based access controls (RBAC). Your AI conversations are private, securely stored, and retained based on your role. This ensures better data protection, clear ownership, and compliance with enterprise security standards.
Key Highlights
Private and Secure by Default: You can view your own chat history unless your role allows additional access. Unauthorized access attempts are automatically blocked, keeping your AI conversations secure and confidential.
Clear Ownership & Retention Rules: Each chat is owned by the user who created it and cannot be transferred. Retention periods are defined by role to ensure consistent governance, and you can see how long your chats will be stored. Expiration indicators help prevent unexpected data loss.
Strong Data Protection & Audit Tracking: Chat data is securely isolated to prevent cross-user access. All retention changes and access activity are logged for transparency and compliance.
Git Custodian: Instant Alerts to Reduce Security Exposure Time
Git Custodian delivers instant email alerts for high-risk security vulnerabilities detected in your monitored repositories. This capability enables security teams to move from scheduled reviews to immediate response.
Key Highlights
Instant Critical Alerts: Automatically identifies new critical vulnerabilities as they appear and triggers immediate email notifications to your security or DevOps teams.
Actionable Security Insights: Each alert provides the essential context needed for a quick fix:
Context: Vulnerability type and severity level.
Location: The exact file and repository affected.
History: Clarity on whether the issue is new or recurring.
Direct Access: A one-click link to the Git Custodian dashboard for remediation.
Flexible Thresholds: Customize your notification settings and assign multiple recipients at the team or repository level for precise, role-based routing.
Timeline View for Parallel Step Executions
Opsera introduces a new Timeline Activity View designed to improve visibility into parallel pipeline executions. This capability transforms traditional linear logs into an interactive, time-based visualization that makes debugging and performance analysis faster and more intuitive.
Key Highlights
Interactive Timeline View for Parallel Steps: Pipeline activity logs are now displayed as a horizontal timeline, where each parallel step appears as a separate lane. Users can visually track start time, duration, overlap, and completion status of concurrent steps
Real-Time Status Indicators & Log Drill-Down: Each step in the timeline includes visual status markers (Running, Success, Failed, Skipped) and duration bars. Clicking on any segment expands a contextual side panel with detailed logs, timestamps, and error highlights for that specific step.
Improved Debugging & Performance Insights: The timeline view clearly reveals bottlenecks, wait states, retries, and failure points across parallel executions.
Intelligent Post-Deployment Pipeline Analysis & Recommendations for AI Run Pipeline Summary
The Hummingbird AI-powered Pipeline Run Summary, delivered directly within the Pipeline, provides users with actionable insights. This capability is controlled via a feature flag and becomes available when the flag is enabled. This eliminates the need for manual log analysis, enabling faster issue resolution, performance optimization, and risk identification.
Key Highlights
Intelligent Pipeline Overview: Generates a high-level map of the pipeline’s design and intent. It automatically identifies the pipeline owner, workflow purpose, parallel steps, and critical deployment stages, providing instant context for every run.
Health & Trend Analysis: The system compares the current execution against historical data from the last 10 days. It automatically highlights anomalies, duration spikes, and recurring failure patterns.
Proactive Security & Optimization: The AI evaluates your configuration against DevOps best practices and provides prioritized recommendations.
Additional Capabilities
Improved Argo CD Application Creation Flow
The Argo CD Application Creation flow has been updated to prevent API downtimes from blocking your deployments. The Branch/Tag field now allows for both dropdown selection and direct manual entry.
Salesforce
New Branch Creation Supported in “Push Artifacts to Git” Step
Opsera has improved the Push to Git step to support automatic, per-execution branch creation.
Key Highlights
Execution-Specific Branching: The pipeline automatically creates a new Git branch for every run. It pushes build artifacts to this unique branch, ensuring that each build is isolated and standardized without manual Git operations.
Enhanced Audit & Traceability: By capturing every build in a separate branch, users can create a clear map between a pipeline execution and its resulting code. This makes historical inspections, rollbacks, and compliance audits significantly faster and more accurate.
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