Agile Analytics v2.5.4 Release Notes
Version 2.5.4 is a hardening release focused on correctness, accessibility, CI quality gates, safer defaults, and developer-tooling cleanup across the extension.
Read articleGuides, best practices, and deep-dives on sprint metrics, flow analytics, and data-driven agile coaching for Azure DevOps teams.
Version 2.5.4 is a hardening release focused on correctness, accessibility, CI quality gates, safer defaults, and developer-tooling cleanup across the extension.
Read articleVersion 2.5.2 redesigns the Feature Configuration tab by replacing the legacy visual filter builder with a focused Enterprise Scope picker, simplified Team Scope controls, and preserved field mappings.
Version 2.5.1 is a major redesign of Feature Analytics — individual feature list, live filter bar, quarterly heatmaps by team and product area, SP trend chart, and process-agnostic field mapping configuration.
Version 2.4.9 improves Feature Analytics scope matching for multi-team environments and reinforces the required setup path that protects dashboard data accuracy.
Version 2.4.5 expands enterprise multi-team analytics across projects, improves team-activity clarity, and aligns portfolio metrics with configured Live Stats scope.
Version 2.4.2 improves workflow-stage clarity, hardens cycle-time data quality, and adds cross-project multi-team scope usability.
Version 2.4.0 improves multi-team scalability, team selection UX, Agile Coach visibility, and cross-view performance for larger Azure DevOps organizations.
Version 2.3.2 of Agile Analytics adds two new Configuration tabs that make it easier to validate a new install and diagnose issues — Customer Readiness and Support Diagnostics.
If your sprint and flow numbers feel off, workflow mapping is usually the root cause. Here is how to map Azure DevOps states so Agile Analytics reports match how your team actually works.
Carryover is one of the clearest signs that sprint commitments are drifting from delivery reality. Learn how to reduce it without shrinking ambition or teaching teams to sandbag.
Daily standups get much more useful when the team focuses on aging work instead of reciting every ticket. Here is how to use item age as a practical delivery signal inside Azure DevOps.
P50, P85, and P95 forecasts answer different business questions. This guide helps Azure DevOps teams choose the confidence level that fits the decision instead of defaulting to one date for every audience.
The AI Agile Coach feature uses GPT-powered analysis to turn your sprint data into actionable coaching insights, retrospective summaries, and proactive alerts — without any manual data interpretation.
A step-by-step guide to installing Agile Analytics from the Visual Studio Marketplace, configuring it for your Azure DevOps project, and getting your first sprint metrics in minutes.
Monte Carlo simulation gives you probabilistic delivery forecasts based on your team's actual historical throughput. Learn how Agile Analytics uses it to answer "when will we be done?" with confidence.
Cycle time and WIP (Work In Progress) are the two most powerful flow metrics for identifying bottlenecks and improving delivery throughput. Here is how to read and act on them.
Sprint velocity and burndown are the two most fundamental agile metrics. Learn what they measure, why they matter, and how Agile Analytics enhances them beyond the built-in Azure DevOps reports.
Agile Analytics is an Azure DevOps-native extension that gives your team real-time sprint and flow visibility without sending data to any external server. Learn how it works under the hood.