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[mdx → asciidoc] Add AsciiDoc serverless files (#4480)
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* migrate mdx to asciidoc

* fix broken links

* clean up landing page

* clean up links

* fix attributes in parentheses

* qa observability

* clean post rebase and qa

* restructure index

* update readme

* update pr template

* catch up to main again

* use asciidoc-dir

* comment out description and keywords
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colleenmcginnis authored Nov 5, 2024
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3 changes: 1 addition & 2 deletions .github/pull_request_template.md
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Expand Up @@ -19,14 +19,13 @@ Closes # <!-- Add the issue this PR closes here -->
Add labels to:
1. Backport to other versions (`backport-*`):
- `backport-8.x` to backport to the latest minor
- `backport-skip` to not backport (for example, for serverless docs)
- `backport-skip` to not backport (for example, for serverless docs)
- `backport-main` to "backport" to `main` if the target branch is _not_ `main`
- Individual `backport-*` labels to target specific minor versions
2. Surface blocking reviews (`needs-*-review`):
- `needs-writer-review` for codeowners
- `needs-dev-review` for dev team
- `needs-product-review` for PM review
3. Build serverless preview docs: `ci:doc-build`
-->

- [ ] Product/Engineering Review
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16 changes: 14 additions & 2 deletions README.md
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Expand Up @@ -10,7 +10,7 @@ Within this repo, the `/docs/en/` directory is structured as follows:
| --------------------- | ----------- |
| __integrations__ | Contains the source files for the [Integrations Developer Guide](https://www.elastic.co/guide/en/integrations-developer/current/index.html).
| __observability__ | Contains the source files for the [Observability Guide](https://www.elastic.co/guide/en/observability/current/index.html), which includes content for APM, Logs, Metrics, Synthetics, User experience, and Uptime.|
| __serverless__ | Contains the source files for the [Elastic Observability Serverless docs](https://docs.elastic.co/serverless/observability/what-is-observability-serverless).
| __serverless__ | Contains the source files for the [Elastic Observability Serverless docs](https://www.elastic.co/docs/current/serverless/observability/what-is-observability-serverless).
| __shared__ | Contains the source files for shared Observability content.|
| __templates__ | Contains content templates.|

Expand Down Expand Up @@ -38,7 +38,19 @@ If you prefer to use aliases, you can load the [elastic/docs/doc_build_aliases.s
### Elastic Observability Serverless docs
The Elastic Observability Serverless docs use a custom syntax written in [MDX](https://mdxjs.com/). In many cases, you only need to know plain Markdown to contribute. We'll add a public component reference and additional contribution guidelines in future. Elasticians can refer to our [internal syntax reference](https://docs.elastic.dev/docsmobile/syntax).
The source files for the Serverless docs are written in [AsciiDoc](https://docs.asciidoctor.org/asciidoc/latest/) and are built using [elastic/docs](https://github.com/elastic/docs).
To build the docs locally:
1. Check out the `elastic/docs` repository, along with any repositories that contain source files.
2. Run the `build_docs` script, passing in the path to the `index.asciidoc` and resource paths to other repos that contain source files. For example, to build the Observability Guide and open it in the browser, run:
```
../docs/build_docs --doc ../docs-content/serverless/index.asciidoc --chunk 5 --open --resource ./docs/en/serverless --resource ../security-docs/docs/serverless --resource ../docs-content/serverless
```
The above command assumes that this repo, [elastic/docs](https://github.com/elastic/docs), [elastic/observability-docs](https://github.com/elastic/observability-docs), [elastic/security-docs](https://github.com/elastic/security-docs), and [elastic/docs-content](https://github.com/elastic/docs-content) are checked out into the same parent directory.
If you prefer to use aliases, you can load the [elastic/docs/doc_build_aliases.sh file](https://github.com/elastic/docs/blob/master/doc_build_aliases.sh), which has the resources defined for you.
### Integrations Developer Guide
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359 changes: 359 additions & 0 deletions docs/en/serverless/ai-assistant/ai-assistant.asciidoc

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73 changes: 73 additions & 0 deletions docs/en/serverless/aiops/aiops-analyze-spikes.asciidoc
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[[observability-aiops-analyze-spikes]]
= Analyze log spikes and drops

// :description: Find and investigate the causes of unusual spikes or drops in log rates.
// :keywords: serverless, observability, how-to

preview:[]

// <DocCallOut template="technical preview" />

{observability} provides built-in log rate analysis capabilities,
based on advanced statistical methods,
to help you find and investigate the causes of unusual spikes or drops in log rates.

To analyze log spikes and drops:

. In your {observability} project, go to **AIOps** → **Log rate analysis**.
. Choose a data view or saved search to access the log data you want to analyze.
. In the histogram chart, click a spike (or drop) to start the analysis.
+
[role="screenshot"]
image::images/log-rate-histogram.png[Histogram showing log spikes and drops ]
+
When the analysis runs, it identifies statistically significant field-value combinations that contribute to the spike or drop,
and then displays them in a table:
+
[role="screenshot"]
image::images/log-rate-analysis-results.png[Histogram showing log spikes and drops ]
+
Notice that you can optionally turn on **Smart grouping** to summarize the results into groups.
You can also click **Filter fields** to remove fields that are not relevant.
+
The table shows an indicator of the level of impact and a sparkline showing the shape of the impact in the chart.
. Select a row to display the impact of the field on the histogram chart.
. From the **Actions** menu in the table, you can choose to view the field in **Discover**,
view it in <<log-pattern-analysis,Log Pattern Analysis>>,
or copy the table row information to the clipboard as a query filter.

To pin a table row, click the row, then move the cursor to the histogram chart.
It displays a tooltip with exact count values for the pinned field which enables closer investigation.

Brushes in the chart show the baseline time range and the deviation in the analyzed data.
You can move the brushes to redefine both the baseline and the deviation and rerun the analysis with the modified values.

[discrete]
[[log-pattern-analysis]]
== Log pattern analysis

// <DocCallOut template="technical preview" />

Use log pattern analysis to find patterns in unstructured log messages and examine your data.
When you run a log pattern analysis, it performs categorization analysis on a selected field,
creates categories based on the data, and then displays them together in a chart.
The chart shows the distribution of each category and an example document that matches the category.
Log pattern analysis is useful when you want to examine how often different types of logs appear in your data set.
It also helps you group logs in ways that go beyond what you can achieve with a terms aggregation.

To run log pattern analysis:

. Follow the steps under <<observability-aiops-analyze-spikes>> to run a log rate analysis.
. From the **Actions** menu, choose **View in Log Pattern Analysis**.
. Select a category field and optionally apply any filters that you want.
. Click **Run pattern analysis**.
+
The results of the analysis are shown in a table:
+
[role="screenshot"]
image::images/log-pattern-analysis.png[Log pattern analysis of the message field ]
. From the **Actions** menu, click the plus (or minus) icon to open **Discover** and show (or filter out) the given category there, which helps you to further examine your log messages.

// TODO: Question: Is the log pattern analysis only available through the log rate analysis UI?

// TODO: Add some good examples to this topic taken from existing docs or recommendations from reviewers.
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