Errors

Errors allows you to search, filter, and query all your error event data across projects and environments to uncover trends and gain insights.

The Errors page lets you query all of your error event metadata across projects and environments. You can build custom queries with flexible filters, group and stack results, visualize trends over time, and save queries for reuse by your team.

While Issues groups related error events for triage and resolution, the Errors page gives you a powerful way to ask questions across all your error data at once, surfacing patterns and trends that individual issues may not reveal.

All error events have built-in key fields and custom tags. Use the search bar to filter events by these keys. For a list of built-in key fields, check out the Searchable Properties documentation.

The search syntax is identical to Sentry's Search syntax. For example, count() gives you the number of times an event occurs:

  • Exact match: count():99
  • Upper bounds: count():<99 or count():<=99
  • Lower bounds: count():>99 or count():>=99
  • Multiple bounds: count():>10 count():<20

Use OR and AND between filters. Note that OR cannot be used between aggregate and non-aggregate filters. Learn more about Using OR and AND.

You can search multiple values for the same key by putting them in a list. For example, x:[value1, value2] returns the same results as x:value1 OR x:value2. Learn more about Multiple Values on the Same Key.

Use the common filters at the top of the page to scope your query by project, environment, and date range.

Every event carries a list of tag values. The tag summary visualizes the top 10 keys sorted by frequency, with the most common tag value shown above the bar. Click Show Tags to see the tag summary.

Click on any tag to refine your search. For example, clicking on Chrome listed under Browser will add Chrome to your search conditions and update the results.

Each query has an interactive graph that reflects the data in the table below. Click and drag over an area to zoom in.

The interval selector controls date groupings in the graph. The available intervals depend on the selected time range -- for example, querying over 90 days limits you to intervals between one hour and 45 days.

  • Total Period
  • Previous Period
  • Release Markers
  • Top Period
  • Total Daily
  • Top Daily
  • Bar Chart

When the display is set to "Top Period" or "Top Daily", you can set a limit. The default is five, showing the top five results.

  • Count
  • Unique User Count

When the display is set to "Total Period", "Previous Period", "Total Daily", or "Bar Chart", you can configure up to three Y-axes by selecting multiple options.

Click "Columns" above the table to manage which columns appear in the results. You can add, remove, and reorder key field columns or custom tag columns.

Add the following functions as columns to stack (group) events:

  • count()
  • count_if(...)
  • count_unique(...)
  • eps()
  • epm()

Each function will ask you to assign a parameter. Some are required, others optional. Functions stack events with the same values. If no functions are applied, events are listed individually. Once you're done editing columns, click "Apply" to update results.

Hovering over a table cell reveals an ellipsis that opens a context menu with additional filtering options. For example, you can add a value to the search conditions by clicking "Add to filter", or exclude it with "Exclude from filter".

Click a column header to sort. A down arrow sorts descending, an up arrow sorts ascending.

You can save any of your queries by clicking the Save As button in the top right. Name your query, and you can then update it or find it later in the All or Starred Queries sections.

Queries can be added to custom dashboards as widgets. Open the context menu on the query card or within the query results view and click "Add to Dashboard". Name your widget, select the target dashboard, and save.

Customize your default view by configuring a query with specific columns, charts, and filters, then clicking "Set as Default". Navigating to the Errors page will then open with this configuration pre-loaded. Click "Remove Default" to revert to the default "All Events" view.

Click "Export Data" to download a CSV file of the results. For large exports, you'll receive an email with the download link. The results are limited to 10 million rows or 1 GB, whichever comes first.

The download includes a SHA1 checksum you can use to verify integrity:

Copied
echo "<SHA1 checksum> <downloaded CSV name>" | sha1sum -c -

Pre-built queries are available from the "Saved Queries" view and are identified by the Sentry avatar. These can be duplicated, but can't be removed.

The Errors page is a powerful way to query across all your error metadata, going beyond the scope of individual issues or projects to reveal trends across all your applications. Enriching your error data with custom tags, release, and environment information makes these queries even more powerful. Learn more about enriching events.

Build a query to find which projects have the most issues:

  1. Select the projects, environments, and date range you want to query.
  2. Edit the table columns to show count(), count_unique(user), and count_unique(issue) per project.
  3. Click the COUNT_UNIQUE(ISSUE) column header to sort by the number of unique issues.
  4. Hover over the top project, click the actions icon, and select "Add to filter" to narrow your results to that project.
  5. Change columns to issue, title, count(), and count_unique(user) to drill into individual issues.

Create a report of errors across URL endpoints:

  • Search condition: has:url
  • Table columns: url, platform.name, count()

Filter URL patterns using wildcards or click "Add to filter" on a specific URL to drill deeper.

Find unhandled fatal errors that may be crashing your application:

  • Search condition: handled:no level:fatal
  • Table columns: mechanism, platform.name, count()

Select a crash type and add it to the filter, then change columns to show the message and count() for more detail.

Find which files in your codebase are generating the most errors:

  • Search condition: has:stack.filename
  • Table columns: stack.filename, count(), count_unique(issue)

Change the display to compare the current period with the previous one to spot trends. Add a specific filename to the filter and change columns to see the major error culprits in that file.

Track how the health of a project changes across releases:

  • Table columns: release, count(), count_unique(issue)

Add a release as a filter and change columns to count() and title to see similar errors. Click the "Open Group" icon to drill into individual events, or open the release in Releases.

The timestamp.to_hour and timestamp.to_day fields round timestamps down to the last hour or day. This lets you group events by time periods -- for example, showing hourly counts for errors that occurred at least twice per hour.

All timestamps display in your preferred timezone, which you can set in User Settings > Account > Account Details.

For more examples of working with error data, see:

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