Event Detail

From Performance and Discover, you can drill all the way down into a span for a single transaction and traverse multiple directions. This will accelerate your ability to debug slow HTTP requests, database queries, identify associated errors, and root out other bottlenecks.

Information about this specific event is located in the sidebar, listing out the Event ID, date and time of occurrence, project, and downloadable JSON package. More can be found under Event Tag Details. You'll also get a breakdown of operations, which will correspond to the waterfall span view as a legend.

Span View

The span view is a split view where the left-hand side shows the transaction’s span tree, and the right-hand side represents each span as a colored rectangle. Within the tree view, Sentry identifies spans by their op and description values. If a span doesn’t have a description, Sentry uses the span’s id as a fallback. The first span listed is always the transaction’s root span, from which all other spans in the transaction descend.

To find these views, you can either go through the Transaction Summary or Query Builder. Event IDs will be linked to open the corresponding Event Detail.

With Transaction Summary

Select the Performance Homepage, then click the affected transaction to display the trace data.

With Query Builder

Scroll down to the "Trace Details" context panel in either the Issue Details or the Discover Event Details page, and click on the "View Summary" button. This will maintain the context of the current Sentry event.

Note: Users on the Team or Business plans can also view a list of transaction events by clicking on the "Transactions" pre-built query in Discover or by performing a search with the event.type:transaction condition the Discover Query Builder view.

Minimap

The minimap (top of the span view) reflects the entirety of the transaction broken into spans. You can either click and drag your cursor across the minimap to zoom in or adjust the window selection by dragging the handlebar (black dashed lines) in from the side. This will affect the range you see in the waterfall view.

Waterfall

The waterfall view is a split view where the left reflects the transaction's span tree, and the right reflects each span as a horizontal bar (colors represent the operation). Within the tree, Sentry identifies spans by their operation and description values. If a span doesn't have a description, Sentry uses the span's ID as a fallback. The first span listed is always the transaction's root span, from which all other spans in the transaction descend.

Span Details

Clicking on a span row expands the details of that span. From here, you can see all attached properties, such as tags and other field data. With the Trace ID, you'll be able to view all transactions within that given trace. Click "Search by Trace" to view that Discover list. Learn more about distributed tracing in our docs.

Traversing Transactions

Some spans within a transaction may be the parent of another transaction. Under these circumstances, some Span IDs will have a "View Child" or "View Children" button. These will potentially lead to another transaction or a list of transactions.

Adding Query Information and Parameters to Spans

Currently, every tag has a maximum character limit of 200 characters. Tags over the 200 character limit will become truncated, losing potentially important information. To retain this data, you can split data over several tags instead.

For example, a 200+ character tagged request:

https://empowerplant.io/api/0/projects/ep/setup_form/?user_id=314159265358979323846264338327&tracking_id=EasyAsABC123OrSimpleAsDoReMi&product_name=PlantToHumanTranslator&product_id=161803398874989484820458683436563811772030917980576

The 200+ character request above will become truncated to:

https://empowerplant.io/api/0/projects/ep/setup_form/?user_id=314159265358979323846264338327&tracking_id=EasyAsABC123OrSimpleAsDoReMi&product_name=PlantToHumanTranslator&product_id=1618033988749894848

Instead, using span.set_tag and span.set_data you could structure the details of this query as metadata. This could be done over columns, table, and conditions, in this case, resulting in three different calls:

import sentry_sdk

#  ...

columns = ["first_column", "second_column", "third_columns", "fourth_column", "fifth_column", "sixth_column"]

table = "this_is_a_long_table_name"

conditions = "first_column=some_value AND second_column=some_other_value AND third_column=yet_another_value"

with sentry_sdk.start_span(op="db", transaction="query api") as span:
    span.set_tag("table", table)
    span.set_data("columns", columns)
    span.set_data("conditions", conditions)

    query = "SELECT {columns} FROM {table} WHERE {conditions}".format(
        columns=columns,
        table=table,
        conditions=conditions,
    )

    # ...

Missing Instrumentation

Gaps between spans may be marked as "Missing Instrumentation." This means a duration in the transaction that isn't accounted for by any of the transaction's spans. It likely means that you need to manually instrument that part of your process. Go back to Getting Started for details.