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Add the OTel quickstart #4615

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2 changes: 2 additions & 0 deletions docs/en/observability/index.asciidoc
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Expand Up @@ -22,6 +22,8 @@ include::quickstarts/monitor-hosts-with-elastic-agent.asciidoc[leveloffset=+2]

include::quickstarts/monitor-k8s-logs-metrics.asciidoc[leveloffset=+2]

include::quickstarts/monitor-hosts-with-otel.asciidoc[leveloffset=+2]
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include::quickstarts/monitor-k8s-otel.asciidoc[leveloffset=+2]

include::quickstarts/collect-data-with-aws-firehose.asciidoc[leveloffset=+2]
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[[quickstart-monitor-hosts-with-otel]]
= Quickstart: Monitor hosts with OpenTelemetry

preview::[]

In this quickstart guide, you'll learn how to collect logs and metrics using the Elastic Distribution of OpenTelemetry (EDOT) Collector.
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You'll also learn how to get value out of your observability data after collecting it.
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[discrete]
== Prerequisites

* An {es} cluster for storing and searching your data, and {kib} for visualizing and managing your data. This quickstart is available for all Elastic deployment models. To get started quickly, try out our hosted {ess} on {ess-trial}[{ecloud}].
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* A Linux or MacOS system.
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* A user with the **Admin** role or higher—required to onboard system logs and metrics. To learn more, refer to {cloud}/ec-user-privileges.html[User roles and privileges].
* Root privileges on the host—required to run the OpenTelemetry collector.
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[discrete]
== Limitations
Refer to https://github.com/elastic/opentelemetry/blob/main/docs/collector-limitations.md[Elastic OpenTelemetry Collector limitations] for known limitations when using the EDOT Collector.

[discrete]
== Collect your data

Follow these steps to collect logs and metrics using the EDOT Collector:

. In {kib}, go to the **Observability** UI and click **Add Data**.
. Under **What do you want to monitor?** select **Host**, and then select **OpenTelemetry: Logs & Metrics**.
+
[role="screenshot"]
image::images/quickstart-monitor-hosts-otel-entry-point.png[Host monitoring entry point]
. Select the appropriate platform.
. Copy the command, open a terminal on your host, and run the command to download and configure the OpenTelemetry collector.
. Copy the command under Step 2 and it in your terminal to start the EDOT Collector.

Logs are collected from setup onward, so you won't see logs that occurred before starting the EDOT Collector.
The default log path is `/var/log/*`. To update the path, modify `otel.yml`.

Under **Visualize your data**, you'll see links to **Logs Explorer** to view your logs and **Hosts** to view your host metrics.

[discrete]
== Get value out of your data

After using the Hosts page and Logs Explorer to confirm you've ingested all the host logs and metrics you want to monitor,
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you can use Elastic {observability} to gain deeper insight into your data.
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For host monitoring, the following capabilities and features are recommended:

* In the <<monitor-infrastructure-and-hosts,Infrastructure UI>>, analyze and compare data collected from your hosts.
You can also:
** <<inspect-metric-anomalies,Detect anomalies>> for memory usage and network traffic on hosts.
** <<create-alerts,Create alerts>> that notify you when an anomaly is detected or a metric exceeds a given value.
* In the <<explore-logs,Logs Explorer>>, search and filter your log data,
get information about the structure of log fields, and display your findings in a visualization.
You can also:
** <<monitor-datasets,Monitor log data set quality>> to find degraded documents.
** {kibana-ref}/xpack-ml-aiops.html#log-pattern-analysis[Run a pattern analysis] to find patterns in unstructured log messages.
** <<create-alerts,Create alerts>> that notify you when an Observability data type reaches or exceeds a given value.
* Use {kibana-ref}/xpack-ml.html[machine learning] to apply predictive analytics to your data:
** {kibana-ref}/xpack-ml-anomalies.html[Detect anomalies] by comparing real-time and historical data from different sources to look for unusual, problematic patterns.
** {kibana-ref}/xpack-ml-aiops.html#log-rate-analysis[Analyze log spikes and drops].
** {kibana-ref}/xpack-ml-aiops.html#change-point-detection[Detect change points] in your time series data.

Refer to the <<observability-introduction>> for a description of other useful features.
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1 change: 1 addition & 0 deletions docs/en/serverless/index.asciidoc
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Expand Up @@ -25,6 +25,7 @@ include::./projects/create-an-observability-project.asciidoc[leveloffset=+3]
// Quickstarts
include::./quickstarts/monitor-hosts-with-elastic-agent.asciidoc[leveloffset=+3]
include::./quickstarts/k8s-logs-metrics.asciidoc[leveloffset=+3]
include::./quickstarts/monitor-hosts-with-otel.asciidoc[leveloffset=+3]
include::./quickstarts/monitor-k8s-otel.asciidoc[leveloffset=+3]
include::./quickstarts/collect-data-with-aws-firehose.asciidoc[leveloffset=+3]

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68 changes: 68 additions & 0 deletions docs/en/serverless/quickstarts/monitor-hosts-with-otel.asciidoc
Original file line number Diff line number Diff line change
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[[quickstart-monitor-hosts-with-otel]]
= Quickstart: Monitor hosts with OpenTelemetry

preview::[]

In this quickstart guide, you'll learn how to collect logs and metrics using the Elastic Distribution of OpenTelemetry (EDOT) Collector.
You'll also learn how to get value out of your observability data after collecting it.

[discrete]
== Prerequisites

* An {observability} project. To learn more, refer to <<observability-create-an-observability-project>>.
* A Linux or MacOS system.
* A user with the **Admin** role or higher—required to onboard system logs and metrics. To learn more, refer to <<general-assign-user-roles>>.
* Root privileges on the host—required to run the OpenTelemetry collector.

[discrete]
== Limitations
Refer to https://github.com/elastic/opentelemetry/blob/main/docs/collector-limitations.md[Elastic OpenTelemetry Collector limitations] for known limitations when using the EDOT Collector.

[discrete]
== Collect your data

Follow these steps to collect logs and metrics using the EDOT Collector:

. <<observability-create-an-observability-project,Create a new {obs-serverless} project>>, or open an existing one.
. To open the quickstart, go to **Add Data**.
. Select **Collect and analyze logs**, and then select **OpenTelemetry**.
. Under **What do you want to monitor?** select **Host**, and then select **Elastic Agent: Logs & Metrics**.
+
[role="screenshot"]
image::images/quickstart-monitor-hosts-otel-entry-point.png[Host monitoring entry point]
. Select the appropriate platform, and complete the following:
. For **MacOS and Linux**, copy the command, open a terminal on your host, and run the command to download and configure the OpenTelemetry collector.
. For **Kubernetes**, download the manifest.
. Copy the command under Step 2:
. For **MacOS and Linux**, run the command in your terminal to start the EDOT Collector.
. For **Kubernetes**, run the command from the directory where you downloaded the manifest to install the EDOT Collector on every node of your cluster.

Logs are collected from setup onward, so you won't see logs that occurred before starting the EDOT Collector.
The default log path is `/var/log/*`. To update the path, modify `otel.yml`.

Under **Visualize your data**, you'll see links to **Logs Explorer** to view your logs and **Hosts** to view your host metrics.

[discrete]
== Get value out of your data

After using the Hosts page and Logs Explorer to confirm you've ingested all the host logs and metrics you want to monitor,
you can use Elastic {observability} to gain deeper insight into your data.

For host monitoring, the following capabilities and features are recommended:

* In the <<observability-infrastructure-monitoring,Infrastructure UI>>, analyze and compare data collected from your hosts.
You can also:
** <<observability-detect-metric-anomalies,Detect anomalies>> for memory usage and network traffic on hosts.
** <<observability-create-manage-rules,Create alerts>> that notify you when an anomaly is detected or a metric exceeds a given value.
* In the <<observability-discover-and-explore-logs,Logs Explorer>>, search and filter your log data,
get information about the structure of log fields, and display your findings in a visualization.
You can also:
** <<observability-monitor-datasets,Monitor log data set quality>> to find degraded documents.
** {kibana-ref}/xpack-ml-aiops.html#log-pattern-analysis[Run a pattern analysis] to find patterns in unstructured log messages.
** <<observability-create-manage-rules,Create alerts>> that notify you when an Observability data type reaches or exceeds a given value.
* Use {kibana-ref}/xpack-ml.html[machine learning] to apply predictive analytics to your data:
** {kibana-ref}/xpack-ml-anomalies.html[Detect anomalies] by comparing real-time and historical data from different sources to look for unusual, problematic patterns.
** {kibana-ref}/xpack-ml-aiops.html#log-rate-analysis[Analyze log spikes and drops].
** {kibana-ref}/xpack-ml-aiops.html#change-point-detection[Detect change points] in your time series data.

Refer to the <<what-is-observability-serverless>> for a description of other useful features.
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