124 lines
5.5 KiB
Plaintext
124 lines
5.5 KiB
Plaintext
[role="xpack"]
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[[correlations]]
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=== Find latency and error correlations
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**Correlations** surface attributes of your data that are potentially correlated with high-latency or erroneous transactions.
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By default, a number of attributes commonly known to cause performance issues, like version,
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infrastructure, and location, are included, but all are completely customizable to your APM data.
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Find something interesting? A quick click of a button will auto-query your data as you work to resolve the underlying issue.
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For example, a site reliability engineer, who is responsible for keeping production systems up and running,
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notices an increase in latency in certain transactions.
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Analyzing metadata or tags that exist in high-latency transactions but not in lower-latency transactions
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can potentially point towards the root cause.
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They may find that a particular piece of hardware, like a host or pod, has failed, increasing latency.
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Or, perhaps set of users, based on IP address or region, is facing increased latency due to local data center issues.
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[discrete]
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[[view-correlations]]
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=== View correlations
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With a service selected, click **View correlations**:
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[role="screenshot"]
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image::apm/images/correlations.png[Correlations]
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Queries within the APM app apply to the correlations shown in the correlations fly-out.
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If a correlated field seems noteworthy, use the **Filter** quick links:
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* `+` creates a new query in the APM app for filtering transactions containing the selected value.
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* `-` creates a new query in the APM app to filter out transactions containing the selected value.
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[discrete]
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[[correlations-latency]]
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==== Find high-latency correlations
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Correlations help you discover which fields are contributing to increased service latency.
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A latency distribution chart visualizes the overall latency of the selected service's transactions.
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Correlated attributes are sorted by _Impact_–a visual representation of the
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{ref}/search-aggregations-bucket-significantterms-aggregation.html[significant terms aggregation]
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score that powers correlations.
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Attributes with a high impact, or attributes present in a large percentage of slow transactions,
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may contribute to increased latency.
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To find high-latency correlations, hover over each potentially correlated attribute to
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compare the latency distribution of transactions with and without the selected attribute.
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For example, in the screenshot below, the field `user_agent.name` and value `HeadlessChrome`
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exists primarily in higher-latency transactions between 3.7 and 8.7 seconds.
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[role="screenshot"]
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image::apm/images/correlations-hover.png[Correlations hover effect]
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Select the `+` filter to create a new query in the APM app for transactions with
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`user_agent.name: HeadlessChrome`. With the "noise" now filtered out,
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you can begin viewing sample traces to continue your investigation.
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As you sift through high-latency transactions, you'll likely notice other interesting attributes.
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Return to the correlations fly-out and select *Customize fields* to search on these new attributes.
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You may need to do this a few times–each time filtering out more and more noise and bringing you
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closer to a diagnosis.
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[discrete]
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[[correlations-error-rate]]
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==== Find error rate correlations
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Correlations help you discover which fields are contributing to failed transactions.
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The Error rate over time chart visualizes the change in error rate over the selected time frame.
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Correlated attributes are sorted by _Impact_–a visual representation of the
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{ref}/search-aggregations-bucket-significantterms-aggregation.html[significant terms aggregation]
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score that powers correlations.
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Attributes with a high impact, or attributes present in a large percentage of failed transactions,
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may contribute to increased error rates.
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To find error rate correlations, hover over each potentially correlated attribute to
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compare the error rate distribution of transactions with and without the selected attribute.
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For example, in the screenshot below, the field `url.original` and value `http://localhost:3100...`
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existed in 100% of failed transactions between 6:00 and 10:30.
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[role="screenshot"]
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image::apm/images/error-rate-hover.png[Correlations errors hover effect]
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Select the `+` filter to create a new query in the APM app for transactions with
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`url.original: http://localhost:3100...`. With the "noise" now filtered out,
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you can begin viewing sample traces to continue your investigation.
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As you sift through erroneous transactions, you'll likely notice other interesting attributes.
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Return to the correlations fly-out and select *Customize fields* to search on these new attributes.
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You may need to do this a few times–each time filtering out more and more noise and bringing you
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closer to a diagnosis.
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[discrete]
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[[correlations-customize-fields]]
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==== Customize fields
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Correlations are only as good as the data they're searching for.
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By default, a handful of attributes commonly known to cause performance issues are included.
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During the course of an investigation however, you may to need to add and remove fields from
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this list multiple times as you narrow in on a diagnosis.
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Add and remove fields under the **Customize fields** dropdown.
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The following fields are selected by default.
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To keep the default list manageable, only the first six matching fields with wildcards are used.
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**Frontend (RUM) agent:**
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* `labels.*`
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* `user.*`
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* `user_agent.name`
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* `user_agent.os.name`
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* `url.original`
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**Backend agents:**
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* `labels.*`
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* `host.ip`
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* `service.node.name`
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* `service.version`
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TIP: Want to start over? Select **reset** to clear your customizations.
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