How to Track Jira Issues with Charts and Graphs
Short answer: Add a chart gadget to a Jira Cloud dashboard, scope it to a project or saved filter (narrowed with JQL if needed) and group the issues by a field. The most useful setups are issues by status, open issues by assignee, priority, issue type, and a stacked status bar for sprint progress. Charts for Jira adds bar, line, pie, area, scatter and table charts in one gadget.
Jira stores detailed data about every issue: status, assignee, priority, type, labels, sprint, created and resolved dates. Getting the data into Jira is easy. Getting something useful out of it, without rebuilding a spreadsheet report every week, is harder.
This guide covers the most practical chart setups for tracking Jira issues: what to chart, how to configure it, and what to look for in the result.
Getting started
Charts - Reports and Graphs for Jira Dashboard adds a chart gadget to Jira Cloud dashboards. It's free on the Atlassian Marketplace. Once it's installed, open a dashboard, click Edit, then Add gadget, and search for "Charts - Reports and Graphs".
Each gadget is configured on its own. You choose:
- Data source: projects, fields, labels or a saved filter, with an optional JQL query to narrow things down
- Chart type: bar, line, pie, area, scatter or table
- Grouping: status, assignee, issue type, project, labels or priority
- Appearance: title, logo, colors, segment order and axis labels
The quick start guide walks through each option.
1. Status distribution: where is everything right now?
The first question for any sprint or project: how many issues are in each status?
Chart type: Bar (horizontal) Group by: Status Scope: Current sprint, or open issues in the project
One bar per status (To Do, In Progress, In Review, Done) gives you the snapshot. When "In Review" is twice as long as "In Progress", reviews are backing up.
For a Kanban team without sprints, scope to all open issues and group by status. The bar lengths show your work-in-progress distribution and make it obvious when one column is collecting more than it should.
2. Assignee workload: is work spread evenly?
Chart type: Bar (vertical or horizontal) Group by: Assignee Scope: Open issues in the current sprint or project
This answers the question that comes up in every planning meeting: is the work balanced? One bar per person, length showing open issue count.
The real insight comes from the pattern over several sprints. If the same one or two people always have the longest bars, that's a structural problem worth fixing, not a one-off.
Refinement: Add a second gadget with the same grouping, scoped with JQL to status = "In Progress". Side by side, the two charts show who has the most assigned and who is actively juggling the most work at once, which is a better signal for overload.
3. Priority breakdown: where are the critical issues?
Chart type: Pie or bar Group by: Priority Scope: Open issues in the project
A priority chart shows the share of Critical, High, Medium and Low issues in your backlog. It's most useful for bug tracking and escalation management.
Check it at the start of each sprint. A growing "Critical" share is an early warning that something in triage or in the product isn't working. If "Critical" grows while "High" shrinks, priorities may simply be inflating.
Practical use: Bring this chart to the retrospective. If a large share of issues marked Critical keep getting pushed back, the label is losing its meaning, and that's worth a conversation.
4. Issue type distribution: what kind of work are we doing?
Chart type: Pie (donut style works well)
Group by: Issue type
Scope: Issues created in the last 30 days (created >= -30d), or the current sprint
Issue types (Bug, Story, Task, Spike and so on) show what the team is actually spending time on. If the roadmap says "feature sprint" but the chart shows 60% bugs, planning and reality have drifted apart.
This chart is more useful at project level than sprint level, since one sprint can be an outlier. A 30-day or 90-day scope shows the real pattern.
5. Sprint progress: are we on track?
Chart type: Bar (stacked) Group by: Status Scope: Current sprint
A stacked bar grouped by status shows the whole sprint in one bar, with segments for To Do, In Progress, In Review and Done. Check it mid-sprint: the size of the Done segment against what's left tells you whether you're ahead, on track or behind, and the other segments show where the remaining work is sitting.
JQL for the current sprint:
project = YOURPROJECT AND sprint in openSprints()
For a burndown over time, use Jira's built-in Sprint Burndown gadget alongside this chart. Our guide to the best Jira dashboard widgets covers which built-in gadgets pair well with Charts for Jira.
6. Label-based tracking: your own dimensions
Labels are underused for reporting. If your team applies labels consistently (customer-request, regression, tech-debt), you can build charts around them.
Example: A bar chart scoped to labels = customer-request and grouped by status shows how many customer-requested issues are open, in progress or done. That's the chart for a customer success update, with no list to compile by hand.
Example: A chart of all open issues grouped by labels shows how work is split across areas or workstreams. To see whether a label's volume is rising or falling over time, Jira's Created vs Resolved gadget pointed at a filter for that label does the job.
Building a dashboard around these charts
A practical sprint team dashboard needs three gadgets:
| Gadget | Chart | Data |
|---|---|---|
| 1 | Status distribution (bar) | Current sprint issues |
| 2 | Assignee workload (bar) | Open issues, current sprint |
| 3 | Priority breakdown (pie) | Open bugs in the project |
That's enough to run a 15-minute sprint check-in without opening a single filter. Everyone looks at the same charts, asks questions from the same data, and the meeting moves faster.
Each gadget keeps its own scope. When you want a different time window, such as last month instead of the current sprint, update the JQL in that gadget, or keep a second dashboard for the longer view. For more on picking the right metrics per audience, read Building a Jira Dashboard That Actually Tells You Something.
