Jira teams today expect more than just basic reporting or simple issue counting. To drive continuous improvement, they need accurate flow metrics, predictable delivery forecasts, and absolute confidence that their sensitive data is handled correctly.
That’s why Atlassian introduced the Runs on Atlassian designation — a clear, verifiable signal that an app is built to operate fully inside Atlassian Cloud.
Time Metrics Tracker is a designated Runs on Atlassian app designed to help teams analyze Time Between Statuses and Agile Time Metrics directly within Jira. It delivers deep insights without requiring external infrastructure, complex integrations, or additional data exposure risks.
What Makes a ‘Runs on Atlassian App’ Different?
The Runs on Atlassian badge isn’t just a marketing label; it is assigned by Atlassian based on verified technical architecture rather than vendor claims. Apps with this status are built exclusively on Forge, Atlassian’s next-generation development platform, and run entirely on Atlassian-managed infrastructure.
In practice, this means the app utilizes Atlassian-hosted compute and storage power. It processes data strictly within the Atlassian Cloud environment and automatically adheres to your organization’s Jira and Confluence data residency settings.
For enterprise teams and security-conscious admins, this removes the uncertainty about where data lives, who has access to it, and how it is processed. If you trust Atlassian with your Jira data, you can trust a Runs on Atlassian app.
Why This Matters for Jira Teams
Adopting new Jira apps often triggers rigorous internal reviews regarding security, data access, and compliance (GDPR, SOC2, etc.). A Runs on Atlassian app significantly reduces this friction by aligning with Atlassian’s own cloud standards from day one.
Teams benefit from:
Faster Approvals: Simplified security reviews since data doesn’t leave the cloud.
Clearer Governance: Automatic compliance with your existing data policies.
Reduced Risk: No third-party servers holding your sensitive workflow data.
Instead of managing additional risk, teams can focus on what matters: improving how work actually flows through Jira.
Agile Time Metrics Without Compromise
Jira is excellent at showing what is happening to work items—who is assigned, what the status is, and when it is due. However, native reporting often lacks the nuance of time analysis.
Time Metrics Tracker adds context by showing exactly how long each step actually takes. It moves beyond simple “Start” and “End” dates to analyze the granular movements of every issue.
By analyzing Time Between Statuses, teams can visualize:
Hidden Bottlenecks: Identify exactly where work waits instead of moving.
Process Efficiency: Pinpoint which statuses consume the most time (e.g., is “Code Review” taking longer than “Development”?).
Impact of Change: Determine whether recent process changes actually improved flow or simply shifted delays to a different stage.
These Agile Time Metrics are calculated automatically from your Jira history. Crucially, the app allows you to define Work Schedules. This means your metrics reflect real business hours, holidays, and time zones, ensuring that weekends or non-working hours don’t skew your data. No exports, spreadsheets, or manual adjustments are required.
Turning Status History into Actionable Insight
Every Jira issue contains a detailed, often untapped record of status changes. Time Metrics Tracker transforms that raw log data into clear, practical metrics.
Key Metrics for Flow Analysis
Cycle Time: Measure the time it takes to complete work once it has started.
Lead Time: Understand the total time from a customer request to delivery.
Time in Status: See granular breakdowns of how long issues sit in specific columns.
SLA Performance: Track adherence to service level agreements based on status duration.
The results are available through highly visual reports like WIP (Work In Progress) dashboards, scatter plots, and time-based charts, all embedded directly in Jira. Because the app respects custom workflows, the numbers reflect your team’s reality rather than theoretical averages.
Practical Use Across Different Teams
The value of tracking Time Between Statuses varies by role, making the tool versatile across an organization.
For Development Teams
Engineering leads use Time Metrics Tracker to understand delivery speed and identify overloaded stages. For example, if the time spent in “QA” is increasing, it might signal a need for more automated testing or additional resources. They can also build delivery forecasts based on historical Cycle Time rather than gut feeling.
For Service and Support (ITSM)
Service teams rely on accurate time tracking to separate “active work” from “waiting for customer” time. This ensures that SLAs are measured accurately without distortion from nights, weekends, or time spent waiting for a client reply.
For Product and Discovery
Product managers can track how long ideas spend in the “Review” or “Validation” phases. This helps prevent initiatives from stalling unnoticed in the backlog and ensures a steady flow of requirements to the development team.
Insight You Can Trust Inside Atlassian Cloud
Because Time Metrics Tracker is built entirely on Forge and operates as a Runs on Atlassian app, customer data stays inside Atlassian Cloud at all times. Data residency follows Jira automatically, and security requirements are handled at the platform level.
This creates a unique opportunity: teams can work with detailed, granular Agile Time Metrics while maintaining absolute confidence in privacy, control, and transparency.
Measure Time in Jira with Confidence
If you want reliable answers to questions like:
“How long does it really take to move from ‘To Do’ to ‘Done’?”
“Where do delays hide in our workflow?”
“Are our delivery expectations grounded in real data?”
Time Metrics Tracker provides clear, trustworthy Time Between Statuses analysis—directly in Jira, with no added risk. It is the smart choice for teams that need to turn workflow history into insight, not uncertainty.
