kibana/docs/apm/correlations.asciidoc
Brandon Morelli 3044cb7ba5
[APM] Document serverless-specific UI (#135178)
Co-authored-by: Alexander Wert <AlexanderWert@users.noreply.github.com>
2022-07-15 06:34:57 +09:30

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4.5 KiB
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[role="xpack"]
[[correlations]]
=== Find transaction latency and failure correlations
Correlations surface attributes of your data that are potentially correlated
with high-latency or erroneous transactions. For example, if you are a site
reliability engineer who is responsible for keeping production systems up and
running, you want to understand what is causing slow transactions. Identifying
attributes that are responsible for higher latency transactions can potentially
point you toward the root cause. You may find a correlation with a particular
piece of hardware, like a host or pod. Or, perhaps a set of users, based on IP
address or region, is facing increased latency due to local data center issues.
To find correlations, select a service on the *Services* page in the {apm-app}
then select a transaction group from the *Transactions* tab.
NOTE: Queries within the {apm-app} are also applied to the correlations.
[discrete]
[[correlations-latency]]
==== Find high transaction latency correlations
The correlations on the *Latency correlations* tab help you discover which
attributes are contributing to increased transaction latency.
[role="screenshot"]
image::apm/images/correlations-hover.png[Latency correlations]
The progress bar indicates the status of the asynchronous analysis, which
performs statistical searches across a large number of attributes. For large
time ranges and services with high transaction throughput, this might take some
time. To improve performance, reduce the time range.
The latency distribution chart visualizes the overall latency of the
transactions in the transaction group. If there are attributes that have a
statistically significant correlation with slow response times, they are listed
in a table below the chart. The table is sorted by correlation coefficients that
range from 0 to 1. Attributes with higher correlation values are more likely to
contribute to high latency transactions. By default, the attribute with the
highest correlation value is added to the chart. To see the latency distribution
for other attributes, select their row in the table.
If a correlated attribute seems noteworthy, use the **Filter** quick links:
* `+` creates a new query in the {apm-app} for filtering transactions containing
the selected value.
* `-` creates a new query in the {apm-app} to filter out transactions containing
the selected value.
You can also click the icon beside the field name to view and filter its most
popular values.
In this example screenshot, there are transactions that are skewed to the right
with slower response times than the overall latency distribution. If you select
the `+` filter in the appropriate row of the table, it creates a new query in
the {apm-app} for transactions with this attribute. With the "noise" now
filtered out, you can begin viewing sample traces to continue your investigation.
[discrete]
[[correlations-error-rate]]
==== Find failed transaction correlations
The correlations on the *Failed transaction correlations* tab help you discover
which attributes are most influential in distinguishing between transaction
failures and successes. In this context, the success or failure of a transaction
is determined by its {ecs-ref}/ecs-event.html#field-event-outcome[event.outcome]
value. For example, APM agents set the `event.outcome` to `failure` when an HTTP
transaction returns a `5xx` status code.
The chart highlights the failed transactions in the overall latency distribution
for the transaction group. If there are attributes that have a statistically
significant correlation with failed transactions, they are listed in a table.
The table is sorted by scores, which are mapped to high, medium, or low impact
levels. Attributes with high impact levels are more likely to contribute to
failed transactions. By default, the attribute with the highest score is added
to the chart. To see a different attribute in the chart, select its row in the
table.
For example, in the screenshot below, there are attributes such as a specific
node and pod name that have medium impact on the failed transactions.
[role="screenshot"]
image::apm/images/correlations-failed-transactions.png[Failed transaction correlations]
Select the `+` filter to create a new query in the {apm-app} for transactions
with one or more of these attributes. If you are unfamiliar with a field, click
the icon beside its name to view its most popular values and optionally filter
on those values too. Each time that you add another attribute, it is filtering
out more and more noise and bringing you closer to a diagnosis.