kibana/docs/apm/correlations.asciidoc
2021-03-16 15:22:44 -04:00

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[role="xpack"]
[[correlations]]
=== Find latency and error correlations
**Correlations** surface attributes of your data that are potentially correlated with high-latency or erroneous transactions.
Surfaced attributes are user-defined, meaning that they are completely customizable to your APM data.
Find something interesting? A quick click of a button will auto-query your data as you work to resolve the underlying issue.
For example, a site reliability engineer, who is responsible for keeping production systems up and running,
notices an increase in latency in certain transactions.
Analyzing metadata or tags that exist in high-latency transactions but not in lower-latency transactions
can potentially point towards the root cause.
They may find that a particular piece of hardware, like a host or pod, has failed, increasing latency.
Or, perhaps a set of users, based on IP address or region, is physically too far away from the nearest
data center, increasing latency.
[discrete]
[[view-correlations]]
=== View correlations
With a service selected, click **View correlations**:
[role="screenshot"]
image::apm/images/correlations.png[Correlations]
Queries within the APM app apply to the correlations shown in the correlations fly-out.
If a correlated field seems noteworthy, use the **Filter** quick links:
* `+` creates a new query in the APM app for transactions containing the selected value.
* `-` creates a new query in the APM app for transactions without the selected value.
[discrete]
[[correlations-latency]]
==== Find high-latency correlations
Correlations help you discover which fields are contributing to increased service latency.
A latency distribution chart visualizes the overall latency of the selected service's transactions.
Correlated attributes are sorted by _Impact_a visual representation of the score for the underlying
aggregation that powers correlations.
Attributes with a high impact, or attributes present in a large percentage of slow transactions,
may contribute to increased latency.
To find high-latency correlations, hover over each potentially correlated attribute to
compare the latency distribution of transactions with and without the selected attribute.
For example, in the screenshot below, the field `user_agent.name` and value `HeadlessChrome`
exists primarily in higher-latency transactions between 3.7 and 8.7 seconds.
[role="screenshot"]
image::apm/images/correlations-hover.png[Correlations hover effect]
Selecting the `+` filter creates a new query in the APM app for transactions with
`user_agent.name: HeadlessChrome`. With the "noise" now filtered out,
you can begin viewing sample traces to continue your investigation.
[discrete]
[[correlations-error-rate]]
==== Find error rate correlations
Correlations help you discover which fields are contributing to failed transactions.
The Error rate over time chart visualizes the change in error rate over the selected time frame.
Correlated attributes are sorted by _Impact_a visual representation of the score for the underlying
aggregation that powers correlations.
Attributes with a high impact, or attributes present in a large percentage of failed transactions,
may contribute to increased error rates.
To find error rate correlations, hover over each potentially correlated attribute to
compare the error rate distribution of transactions with and without the selected attribute.
For example, in the screenshot below, the field `url.original` and value `http://localhost:3100...`
existed in 100% of failed transactions between 6:00 and 10:30.
[role="screenshot"]
image::apm/images/error-rate-hover.png[Correlations errors hover effect]
Selecting the `+` filter creates a new query in the APM app for transactions with
`url.original: http://localhost:3100...`. With the "noise" now filtered out,
you can begin viewing sample traces to continue your investigation.
[discrete]
[[correlations-custom-fields]]
==== Customize fields
Correlations are only as good as the data they're searching for.
By default, a handful of potentially useful fields are selected, like `lables`, `service.version`, and `host.ip`.
You can remove and add fields to this list under the **Customize fields** dropdown.
TIP: Want to start over? Select **reset** to clear your customizations.