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## Summary Adds fixes that have already been made in the serverless docs. Closes https://github.com/elastic/staging-serverless-observability-docs/issues/181 ### Checklist n/a Co-authored-by: Kibana Machine <42973632+kibanamachine@users.noreply.github.com>
177 lines
7.7 KiB
Text
177 lines
7.7 KiB
Text
[role="xpack"]
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[[transactions]]
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=== Transactions
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TIP: A {apm-guide-ref}/data-model-transactions.html[transaction] describes an event captured by an Elastic APM agent instrumenting a service.
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APM agents automatically collect performance metrics on HTTP requests, database queries, and much more.
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[role="screenshot"]
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image::apm/images/apm-transactions-overview.png[Example view of transactions table in the APM app in Kibana]
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The *Latency*, *Throughput*, *Failed transaction rate*, *Time spent by span type*, and *Cold start rate*
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charts display information on all transactions associated with the selected service:
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*Latency*::
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Response times for the service. Options include average, 95th, and 99th percentile.
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If there's a weird spike that you'd like to investigate,
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you can simply zoom in on the graph - this will adjust the specific time range,
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and all of the data on the page will update accordingly.
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*Throughput*::
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Visualize response codes: `2xx`, `3xx`, `4xx`, etc.
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Useful for determining if more responses than usual are being served with a particular response code.
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Like in the latency graph, you can zoom in on anomalies to further investigate them.
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[[transaction-error-rate]]
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*Failed transaction rate*::
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The failed transaction rate represents the percentage of failed transactions from the perspective of the selected service.
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It's useful for visualizing unexpected increases, decreases, or irregular patterns in a service's transactions.
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+
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[TIP]
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====
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HTTP **transactions** from the HTTP server perspective do not consider a `4xx` status code (client error) as a failure
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because the failure was caused by the caller, not the HTTP server. Thus, `event.outcome=success` and there will be no increase in failed transaction rate.
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HTTP **spans** from the client perspective however, are considered failures if the HTTP status code is ≥ 400.
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These spans will set `event.outcome=failure` and increase the failed transaction rate.
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If there is no HTTP status, both transactions and spans are considered successful unless an error is reported.
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====
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*Time spent by span type*::
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Visualize where your application is spending most of its time.
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For example, is your app spending time in external calls, database processing, or application code execution?
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+
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The time a transaction took to complete is also recorded and displayed on the chart under the "app" label.
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"app" indicates that something was happening within the application, but we're not sure exactly what.
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This could be a sign that the APM agent does not have auto-instrumentation for whatever was happening during that time.
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+
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It's important to note that if you have asynchronous spans, the sum of all span times may exceed the duration of the transaction.
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*Cold start rate*::
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Only applicable to serverless transactions, this chart displays the percentage of requests that trigger a cold start of a serverless function.
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See <<apm-lambda-cold-start-info>> for more information.
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[discrete]
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[[transactions-table]]
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=== Transactions table
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The *Transactions* table displays a list of _transaction groups_ for the selected service.
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In other words, this view groups all transactions of the same name together,
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and only displays one entry for each group.
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[role="screenshot"]
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image::apm/images/apm-transactions-table.png[Example view of the transactions table in the APM app in Kibana]
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By default, transaction groups are sorted by _Impact_.
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Impact helps show the most used and slowest endpoints in your service - in other words,
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it's the collective amount of pain a specific endpoint is causing your users.
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If there's a particular endpoint you're worried about, you can click on it to view the <<transaction-details, transaction details>>.
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[IMPORTANT]
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====
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If you only see one route in the Transactions table, or if you have transactions named "unknown route",
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it could be a symptom that the APM agent either wasn't installed correctly or doesn't support your framework.
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For further details, including troubleshooting and custom implementation instructions,
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refer to the documentation for each {apm-agents-ref}[APM Agent] you've implemented.
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====
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[discrete]
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[[rum-transaction-overview]]
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=== RUM Transaction overview
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The transaction overview page is customized for the JavaScript RUM agent.
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Specifically, the page highlights *page load times* for your service:
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[role="screenshot"]
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image::apm/images/apm-geo-ui.png[average page load duration distribution]
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Additional RUM goodies, like core vitals, and visitor breakdown by browser, location, and device,
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are available in the Observability User Experience tab.
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// To do
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// Add link to the Observability UE docs when complete
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[discrete]
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[[transaction-details]]
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=== Transaction details
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Selecting a transaction group will bring you to the *transaction* details.
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This page is visually similar to the transaction overview, but it shows data from all transactions within
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the selected transaction group.
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[role="screenshot"]
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image::apm/images/apm-transactions-overview.png[Example view of response time distribution]
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[[transaction-duration-distribution]]
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==== Latency distribution
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The latency distribution shows a plot of all transaction durations for the given time period.
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The following screenshot shows a typical distribution
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and indicates most of our requests were served quickly -- awesome!
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The requests on the right are taking longer than average; we probably need to focus on them.
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[role="screenshot"]
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image::apm/images/apm-transaction-duration-dist.png[Example view of latency distribution graph]
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Click and drag to select a latency duration _bucket_ to display up to 500 trace samples.
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[[transaction-trace-sample]]
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==== Trace samples
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Trace samples are based on the _bucket_ selection in the *Latency distribution* chart;
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update the samples by selecting a new _bucket_.
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The number of requests per bucket is displayed when hovering over the graph,
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and the selected bucket is highlighted to stand out.
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Each bucket presents up to ten trace samples in a *timeline*, trace sample *metadata*,
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and any related *logs*.
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*Trace sample timeline*
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Each sample has a trace timeline waterfall that shows how a typical request in that bucket executed.
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This waterfall is useful for understanding the parent/child hierarchy of transactions and spans,
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and ultimately determining _why_ a request was slow.
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For large waterfalls, expand problematic transactions and collapse well-performing ones
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for easier problem isolation and troubleshooting.
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[role="screenshot"]
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image::apm/images/apm-transaction-sample.png[Example view of transactions sample]
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NOTE: More information on timeline waterfalls is available in <<spans, spans>>.
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*Trace sample metadata*
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Learn more about a trace sample in the *Metadata* tab:
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* Labels - Custom labels added by APM agents
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* HTTP request/response information
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* Host information
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* Container information
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* Service - The service/application runtime, APM agent, name, etc..
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* Process - The process id that served up the request.
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* APM agent information
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* URL
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* User - Requires additional configuration, but allows you to see which user experienced the current transaction.
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* FaaS information, like cold start, AWS request ID, trigger type, and trigger request ID
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TIP: All of this data is stored in documents in Elasticsearch.
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This means you can select "Actions - View transaction in Discover" to see the actual Elasticsearch document under the discover tab.
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*Trace sample logs*
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The *Logs* tab displays logs related to the sampled trace.
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include::./logs.asciidoc[tag=log-overview]
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[role="screenshot"]
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image::apm/images/apm-logs-tab.png[APM logs tab]
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[[transaction-latency-correlations]]
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==== 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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To learn more, see <<correlations>>.
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[role="screenshot"]
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image::apm/images/correlations-hover.png[APM lattency correlations]
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