How to Export Issues From Jira: A Comprehensive Guide

When managing your projects in Jira, the need for exporting data is inevitable, e.g. for data sharing, analysis, migration, or backup. Whether you are a brand new user ready to get started or you are simply looking to brush up on your skills, you may find this guide on how to export issues from Jira helpful. 

Below you will find out how to use Jira’s built-in export functionalities and how to overcome the various limitations they pose. Visual examples of how external tools ride to the rescue are provided. We hope that you will find enough information here to start off the exporting experience on the right foot and make it more productive and, importantly, effortless. Let’s get started!

Why export issues from Jira

Here are a few reasons why teams may need to export Jira issues:

• Sharing information with external people: It is pretty common to collaborate on your projects together with external users in your Jira instance. Clients, partners, or stakeholders can create new issues, prioritize them, share ideas, and provide feedback. Keeping them aware of the objectives, requirements, needs, and constraints of a project allows them to bring up issues or concerns about addressing all of them.

• Analyzing data in spreadsheets and external tools: Exporting Jira issues comes in handy when you need to manipulate this raw Jira data in Excel, Google Sheets, or data analysis tools. You can also connect Jira to Looker Studio to visualize data in interesting ways, and generate custom reports. Although Jira helps stay on top of different projects and team needs, it lacks some features that make spreadsheets or data visualization tools great. Getting actionable insight from raw Jira data holds the key to some key questions: Is your team tracking toward their key performance indicators? Is the project likely to complete in due time?

• Migrating issues between Jira instances: It’s necessary to export issues from Jira when you want to move data from one Jira instance to another. For example, your business might need to merge the separate instances (Jira Cloud sites) it has for different purposes and departments. Another example is when you need to migrate your Jira instance from the cloud to a self-hosted server or vice versa.

• Analyzing compliance with SLAs: Customers often ask for statistics about their SLAs, which define contractually agreed-upon terms for services, including uptime and support responsiveness. Exporting issues to spreadsheet forms (e.g. Excel) or searching for better reporting alternatives in the Atlassian Marketplace than Jira is common when you want to assess how you are performing against SLAs.

How you can export issues from Jira – all options explained

Depending on what data you are looking for, you can export Jira issues using the following methods: 

• Jira’s built-in functionality
• Jira plugins
• ETL tools
• Jira’s REST APIs

The built-in options enable you to export Jira issues in different formats, including XML, Word, CSV, and HTML.

All you have to do is to apply the desired filters in the issue search to select issues for export. For a more advanced search, you can enter your JQL query to bring up the issues you want to export. If the built-in queries don’t have what you are looking for, and you are skilled in JQL, you can write your own query.

In certain cases that will be described later, native options are limited in their ability to export certain data you desire. If data cannot be exported natively through the UI, you can use Jira plugins found in the Atlassian Marketplace.

In addition, you can extract data from Jira with external ETL tools, like the one provided by Coupler.io. It allows you to load data from Jira without requiring any coding knowledge. You will be walked through this export process step by step in the later sections below. 

The most advanced way to export issues from Jira is through the REST API. Overall, the process involves using an HTTP GET or POST request to call Jira’s search REST endpoint, providing the desired search parameters in JQL. In most cases, this requires you to write a script in Python or another programming language. Alternatively, you can do this without coding using a JSON API connector.

How to export issues from Jira manually

Exporting issues from Jira using its native features involves pretty simple steps. 

Once you have logged in to your Jira account, select the Filters option from the panel on the top of your screen. Then click on Advanced issue search.

Once you select the advanced search option, a new search window opens up. You can use Jira’s various built-in JQL queries in the search bar to get the issues you want to export. If you are searching for a query that doesn’t exist, you can create your own.

You can also select the bugs, epics, stories, or tasks manually by clicking on the Switch to basic option on the right of the search bar.

Jira’s Export drop-down at the top right menu allows you to export data in various formats such as XML, Word, HTML, and Excel.

How to export Jira issues to Excel

The simplest way to make a Jira export to Excel is via the Export Excel CSV button. Once you have found the issues you want to export, either through the JQL filters or the ‘Switch to basic’ option, click Export and Export Excel CSV (all fields) or Export Excel CSV (current fields).

The CSV file is loaded as an Excel spreadsheet. Once you open the downloaded Excel file, here is what the exported data will look like:

Limitations when exporting Jira issues through the UI

The native option to export Jira issues poses a few limitations. The main problems are the following: 

• Jira does not export all the content from Jira issues. The issues that have been exported natively lack data that might be critical for your business, such as comments and attachments. 
• Using Jira’s built-in functionalities, the maximum number of exported issues is 1000. 
• Jira does not support issue exports to PDF. The supported formats are XML, Word, CSV, and HTML.

Jira – Export all issues automatically

Jira is one of the leading platforms for issue tracking, but what if you want to get more than this management tool can provide? For example, to build a custom dashboard to regularly track the progress of your project. Creating spreadsheets manually and copying the information in another tool consumes much time that could be dedicated to doing something more productive. So, is it possible to automatically export issues from Jira on a set schedule?

A more convenient alternative to manual exports is using an integration tool, such as one provided by Coupler.io.

Coupler.io is a data automation and analytics platform that provides an ETL no-code solution to pull data from Jira to BigQuery, Google Sheets, or Excel. With Coupler.io, you can set an automatic data refresh on the desired schedule so that your data remains up to date. Selecting a daily or hourly data refresh eliminates all concerns regarding outdated data: Considering that work is still being conducted in Jira even after you export your issues, frequent automatic updates in Excel will reflect any updates in Jira.

You can build your Coupler.io flow and start exporting Jira issues in a matter of minutes. Below, we show you how this is done. Please note, the particular flow described is not applied in certain cases, for example, when you want to export issues with all their content (namely with comments and attachments). We discuss how the above scenario can be realized in a later section.

To export all issues from Jira, you need to take the following steps:

• Sign up with Coupler.io and click on Add new importer.
• Select Jira as your source app and Microsoft Excel as your destination app if you need Jira export to Excel. You can also benefit from Jira Google Sheets integration or Jira to BigQuery export.

• Once you connect to your source account, select your Jira Cloud instance with the data to be extracted. Furthermore, you can enter the JQL query of your filter. In this example, we want to filter the issues created over the last 30 days using the following JQL query:

created >= -30d order by created DESC

• Select the Export format and specify the columns to export from Jira, if needed.

• Connect your Microsoft account. Then, you will need to select an existing workbook and a sheet to load exported data from Jira. The importer also provides an optional feature that lets you specify the column where the imported data will be added to the destination sheet. This facilitates the operation of any formulas you might have created on a selected range of cells. Ultimately, select the import mode.

To automate data export, toggle the Automatic data refresh button and schedule the day, time, and timezone. Then click on Save and Run.

Here is what the exported issues from Jira will look like in Excel:

Jira export all issues and custom fields

Either you attempt to export issues from Jira manually or automatically using Coupler.io, all issues and custom fields are being exported to Excel – unless you specify which particular columns to export. 

Jira – Export issues with comments and attachments

Exporting issues together with all their comments and attachments is not possible through Jira’s built-in features. Comments and attachments will not appear as columns in a spreadsheet or a table. Copying them manually for every issue would inevitably take a lot of time, especially if the number of issues created daily is high.

Below we will show you how you can export the comments and attachments from Jira through the REST API without any coding with the help of Coupler.io.

Jira – Export issues with comments

The steps taken to export Jira issues with comments using Coupler.io are:

• First, you need to enter the proper JQL in Jira to filter the issues with comments that you want to export. In our example, we filter the issues with comments that have been created over the last 30 days using the following query:

created >= -30d and (comment ~ 'keyword*' OR comment !~ 'keyword*')

• Select JSON as your source app and Microsoft Excel as your destination app.

• Insert the URL of your JIRA endpoint.

• Select the POST request method.
• Specify the following HTTP headers for your JIRA request:

Authorization: Basic {encoded-api-token}
Content-Type: application/json

For more information on how to create an API token, visit this page in Atlassian Support. Also, make sure that you encode your API token to Base64 format using a dedicated tool like base64encode.org or base64encode.net.

• To narrow down the number of exported fields in Excel, namely view information relevant to comments, add the following lines in the Request body:

The above lines are the POST request body. Note that the maximum number of returned results cannot exceed 1000. In addition to the comment value, we added attachment as the process for exporting issues with attachments is similar to that of exporting comments.

• In Path, type issues to get the content under issues from the JSON response.

• Just like in the previous Coupler.io flow describing how to export all issues, connect to your Microsoft account. Then, select an existing workbook and a sheet to load exported data from Jira.

• Ultimately, toggle the Automatic data refresh button and schedule the day, time, and timezone. Then click on Save and Run.

Here is what the exported issues with comments from Jira will look like in Excel. The image shows the number of the issue and the content of the two comments that each issue has.

Please note that once you run the importer, the number of columns appearing in Excel that relate to comments is high, but not all of them might be useful for you.

You could choose which comment-related columns you would like to export, just as in our example above. As mentioned earlier, we deemed it useful to display the number of each issue and the content of the comments that each issue contains. The easiest way to do so is:

• After running the importer, open the Excel sheet and search for the column names that you would like to export.
• Edit the importer and click on Columns found under the Request body and type the following comma-separated column names:

key,fields.comment.comments.0.body.content.0.content.0.text,fields.comment.comments.1.body.content.0.content.0.text

• Repeat the above step each time you want to export issues together with the content of their comments without having to search them in the multiple-column Excel file.  

Jira – Export issues with attachments

The process for exporting issues with attachments using Coupler.io is similar to the previous one (Jira export issues with comments). However, you need to take into account the two following points:

• The JQL query in Jira that filters the issues with attachments is different:

created >= -30d and attachments is not empty order by created DESC

• The Request body with the above JQL query will now look like this:

Here is what the exported issues with attachments from Jira will look like in Excel. The image shows the number of issues, the attachment filenames, and the links for their download:

Once again, the number of columns appearing in Excel that relate to attachments is high, but not all of them might be useful for you. You could choose which attachment-related columns you would like to view by following the same workflow for comments.

In our example, we display the number of each issue, the filenames of the two attachments each one contains, and the links for their download. To view them, we typed the following comma-separated column names in Columns:

key,fields.attachment.0.filename,fields.attachment.0.content,fields.attachment.1.filename,fields.attachment.1.content

Jira – Export linked issues

Linking issues in Jira is very useful when two issues have some type of dependency on each other. The four default issue links are blocks, clones, duplicates, and relates to. You can also create your own types of issue links.

Jira offers you the option to export linked issues through its interface. The following JQL query will let you view all types of issue links:

issueLinkType IS NOT EMPTY

In the above image, we view issue types PROJ-1 and PROJ-2 that refer to a task (parent) and sub-task (child). This task-subtask relationship is as special as the epic-story relationship.

If you wish to view issues that use specific types of links, you can use the following query:

issueLinkType in ("blocks", "cloners", "duplicate", "relates")

Whether you want to export all types of issue links or specific ones, click Export on the top right and Export Excel CSV (all fields).

This is what the exported issue links will appear in Excel:

In the image above, the column ‘Inward issue link’ demonstrates that an issue affects another issue (e.g., ISM-1 affects ISM-2). The column ‘Outward issue link’ shows that an issue is affected by another issue (e.g., ISM-7 is affected by ISM-3).

How to export all issues in an epic from Jira

Jira offers the option to export all issues in a specified epic through its interface. Below, we identify two cases, depending on whether you want to view all issues in one epic or find all epics with their issues.

Exporting all issues in one epic manually

To display in Jira all the issues in a specific epic, e.g. stories and tasks, navigate to the advanced search and type in the following JQL query:

issuekey=X or parent=X

Where X is the issue key (in our example X = ISM-3).

The image shows the issue key (ISM-3) with its child issues (ISM-4, ISM-5, and ISM-6).

To export an epic with its issues, click Export on the top right and Export Excel CSV (all fields).

In the Excel image below, the ‘Issue Type’ column identifies the epic and the stories.

Exporting all issues from all epics manually

To display in Jira all epics with their issues, navigate to the advanced search and type in the following JQL query:

issuetype=epic or (issuetype=story and parent IS NOT EMPTY)

The image above shows epic ISM-3 with its child issues (ISM-4, ISM-5, and ISM-6) and epic ISM-7 with its child issue (ISM-11).

To export epics with their issues, click on Export in the top right corner, as in the previous case.

Jira – Export to Excel more than 1,000 issues

Jira sets a default limit of 1,000 rows set on the number of issues that can be returned in the issue navigator. Therefore, when exporting to Excel manually, JIRA will only export the first 1,000 issues. 

Coupler.io can easily help you overcome this 1,000-issue limitation, eliminating the need to manually repeat the above-mentioned steps. The process is similar to that described in the this section.

After selecting Jira as your source app and Google Sheets as your destination app, enter your JQL query. In our example below, we filter the issues that have been created over the last 60 days using the following query:

created >= -60d order by created DESC

Following the same workflow as before, select the Export format (namely, Jira CSV export). Then, connect to your Google Sheets account and select the spreadsheet and sheet to load exported data from Jira.

Then, click on Save and Run to run the importer. In a matter of minutes, you will have all issues created over the last two months loaded from Jira to Google Sheets.

In the image below, Coupler.io overcomes the 1,000-result limitation, returning over 2,900 issues!

Exporting more than 1,000 issues manually

The following workaround will help you deal with this issue. 

• Run a search on the issue navigator using the proper JQL functions to get all the issues you need to export. We would also recommend using an ORDER BY option to sort the results in an ascending or descending order, as they might appear in a messy order.
• Export the first 1,000 issues using the standard export feature: Export->Export Excel CSV.
• For the next thousand issues, right-click on the same option above and open in a new tab. You should get a URL string like:

https://team-16705757846246.atlassian.net/sr/jira.issueviews:searchrequest-csv-all-fields/temp/SearchRequest.xls?jqlQuery=Parent%20%3D%20ISM-3&tempMax=1000

• Append the &pager/start=1000 at the end of the URL string to instruct JIRA to export from index 1001 and above.
• Repeat the previous step for exporting the next batch of 1,000 issues, setting the index value to 2,000 (and so forth).
• Open the exported CSV files and manually consolidate them if necessary.

How to export issues from Jira – summary

As we have discussed, exporting issues from Jira can be done in two ways: manually and automatically. JQL functions in Jira or custom ones boil down complex logic and make it easy to search issues by multiple criteria. 

Jira’s native options are good for one-time exports, for example, if you need to move the data to another software.

The automated exporting option, namely the one provided by Coupler.io, allows you to schedule the export of data at a custom schedule, such as every day or every hour.

Coupler.io’s ability to connect to Jira’s REST API allows you to fetch any type of data from Jira using the multitude of JQL functions. This tool provides a route around exporting Jira issues with comments and attachments – critical data that cannot be exported using native options.

We hope that the content covered in the article will serve as a powerful guide for exporting issues, providing newcomers with a smooth transition into the world of Jira and saving some valuable time for more experienced individuals.

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