Modifies Get started guide, renames and updates Create a new API key page

Author: kosabogi

serverless/images/copy-connection-details.png

@@ -16,7 +16,7 @@ include::./pages/pricing.asciidoc[leveloffset=+2]
 
 include::./pages/get-started.asciidoc[leveloffset=+2]
 
-include::./pages/create-new-api-key.asciidoc[leveloffset=+2]
+include::./pages/connecting-to-es-endpoint.asciidoc[leveloffset=+2]
 
 include::./pages/clients.asciidoc[leveloffset=+2]
 include::./pages/clients-go-getting-started.asciidoc[leveloffset=+3]

serverless/images/create-an-api-key.png

@@ -0,0 +1,79 @@
+[[elasticsearch-connecting-to-es-serverless-endpoint]]
+= Connecting to your Elasticsearch Serverless endpoint
+
+[discrete]
+[[elasticsearch-create-new-api-key]]
+== Create a new API key
+
+Create an API key, which will enable you to access the {es} API to ingest and search data.
+
+. On the **Getting Started** page, scroll to **Add an API Key** and select **New**.
++
+image::images/create-an-api-key.png[Create an API key.]
+. In **Create API Key**, enter a name for your key and (optionally) set an expiration date.
+. (Optional) Under **Control Security privileges**, you can set specific access permissions for this API key. By default, it has full access to all APIs.
+. (Optional) The **Add metadata** section allows you to add custom key-value pairs to help identify and organize your API keys.
+. Select **Create API Key** to finish.
+
+After creation, you'll see your API key displayed as an encoded string.
+Store this encoded API key securely. It is displayed only once and cannot be retrieved later.
+You will use this encoded API key when sending API requests.
+
+[NOTE]
+====
+You can't recover or retrieve a lost API key. Instead, you must delete the key and create a new one.
+====
+
+[discrete]
+[[elasticsearch-get-started-copy-url]]
+== Copy your {es} endpoint
+
+Copy the URL of your {es} API endpoint.
+You'll send all {es} API requests to this URL.
+
+. On the **Getting Started** page, scroll to **Copy your connection details** section, and find the **Elasticsearch endpoint** field.
+. Copy the URL for the Elasticsearch endpoint.
+
+image::images/copy-connection-details.png[Copy your Elasticsearch endpoint.]
+
+[discrete]
+[[elasticsearch-get-started-test-connection]]
+== Test connection
+
+We'll use the `curl` command to test your connection and make additional API requests.
+(See https://everything.curl.dev/install/index.html[Install curl] if you need to install this program.)
+
+`curl` will need access to your Elasticsearch endpoint and `encoded` API key.
+Within your terminal, assign these values to the `ES_URL` and `API_KEY` environment variables.
+
+For example:
+
+[source,bash]
+----
+export ES_URL="https://dda7de7f1d264286a8fc9741c7741690.es.us-east-1.aws.elastic.cloud:443"
+export API_KEY="ZFZRbF9Jb0JDMEoxaVhoR2pSa3Q6dExwdmJSaldRTHFXWEp4TFFlR19Hdw=="
+----
+
+Then run the following command to test your connection:
+
+[source,bash]
+----
+curl "${ES_URL}" \
+  -H "Authorization: ApiKey ${API_KEY}" \
+  -H "Content-Type: application/json"
+----
+
+You should receive a response similar to the following:
+
+[source,json]
+----
+{
+  "name" : "serverless",
+  "cluster_name" : "dda7de7f1d264286a8fc9741c7741690",
+  "cluster_uuid" : "ws0IbTBUQfigmYAVMztkZQ",
+  "version" : { ... },
+  "tagline" : "You Know, for Search"
+}
+----
+
+Now you're ready to ingest and search some sample documents.

serverless/index-serverless-elasticsearch.asciidoc

@@ -36,7 +36,7 @@ Once your project is set up, you'll be directed to a page where you can create y
 An index is where documents are stored and organized, making it possible to search and retrieve data.
 
 . Enter a name for your index.
-. Click *Create my index*. You can also create the index by clicking on *Code* to view and run code examples through the command line.
+. Click *Create my index*. You can also create the index by clicking on *Code* to view and run code through the command line.
 +
 image::images/get-started-create-an-index.png[Create an index.]
 
@@ -49,170 +49,50 @@ image::images/get-started-create-an-index.png[Create an index.]
 You won’t be able to view this API key again. If needed, refer to <<elasticsearch-create-new-api-key,Create a new API key>> to generate a new one.
 ====
 
-[discrete]
-[[elasticsearch-get-started-ingest-data]]
-== Ingest data
+The UI provides ready-to-use code examples for ingesting data via the REST API. 
+Choose your preferred tool for making these requests:
 
-The UI provides ready-to-use code examples for ingesting data via the REST API. Choose your preferred tool for making these requests:
 * Elastic Console in your project's UI
 * Python 
 * JavaScript 
 * cURL
-If you'd prefer to upload a file using the UI, refer to <<elasticsearch-ingest-data-file-upload>>.
-
-In this section, we walk you through the ingest process using the Console.
-
-. Click *Run in Console*.
-. Run the first API call to create the index mapping.
-+
-[source,console]
-----
-PUT /search-test/_mapping
-{
-  "properties": {
-    "vector": {
-      "type": "dense_vector",
-      "dims": 3
-    },
-    "text": {
-      "type": "text"
-    }
-  }
-}
-----
-
-. Run the second API call to ingest documents.
-
-[source,console]
-----
-POST /_bulk?pretty
-{ "index": { "_index": "search-test" } }
-{"vector":[2.542,5.807,9.735],"text":"Example text 1"}
-{ "index": { "_index": "search-test" } }
-{"vector":[5.879,8.179,9.932],"text":"Example text 2"}
-{ "index": { "_index": "search-test" } }
-{"vector":[6.534,7.155,3.236],"text":"Example text 3"}
-----
-
-[discrete]
-[[elasticsearch-get-started-search-data]]
-== Search data
-
-To search, send a `POST` request to the `_search` endpoint, specifying the index to search.
-
-Run the following command to search the `search-test` index for documents containing `Example` in the text field:
-
-[source,bash]
-----
-POST /search-test/_search?pretty
-{
-  "query": {
-    "match": {
-      "text": "Example"
-    }
-  }
-}
-----
-
-This query will use the match query, which is designed to search for full-text fields.
-
-You should receive a response that includes the documents matching your search term. 
-Here’s an example of what the response might look like:
-
-[source,console]
-----
-{
-  "took": 6,
-  "timed_out": false,
-  "_shards": {
-    "total": 3,
-    "successful": 3,
-    "skipped": 0,
-    "failed": 0
-  },
-  "hits": {
-    "total": {
-      "value": 3,
-      "relation": "eq"
-    },
-    "max_score": 0.2876821,
-    "hits": [
-      {
-        "_index": "search-test",
-        "_id": "NJZmIJMBSZbIKcD1sOUO",
-        "_score": 0.2876821,
-        "_source": {
-          "vector": [
-            2.352,
-            4.133,
-            1.718
-          ],
-          "text": "Example text 2"
-        }
-      },
-      {
-        "_index": "search-test",
-        "_id": "M5ZmIJMBSZbIKcD1sOUO",
-        "_score": 0.18232156,
-        "_source": {
-          "vector": [
-            6.407,
-            1.821,
-            0.404
-          ],
-          "text": "Example text 1"
-        }
-      },
-      {
-        "_index": "search-test",
-        "_id": "NZZmIJMBSZbIKcD1sOUO",
-        "_score": 0.18232156,
-        "_source": {
-          "vector": [
-            4.959,
-            5.986,
-            3.873
-          ],
-          "text": "Example text 3"
-        }
-      }
-    ]
-  }
-}
-----
-
-In this response:
-
-- `hits`: This section contains the matching documents. Each document includes the `_source` field with the original vector and text fields.
-- `_score`: This field indicates the relevance score of each document to the search query. A higher score means a closer match.
 
 [discrete]
 [[elasticsearch-get-started-continue-on-your-own]]
-== Continue on your own
-
-Congratulations!
-You've set up an {es} project, and you've ingested and searched some sample data.
-Now you're ready to continue on your own.
-
-[discrete]
-[[elasticsearch-get-started-explore]]
-=== Explore
-
-Want to explore the sample documents or your own data?
-
-By creating a data view, you can explore data using several UI tools, such as Discover or Dashboards. Or, use {es} aggregations to explore your data using the API. Find more information in <<elasticsearch-explore-your-data>>.
+== Ingest data
 
-[discrete]
-[[elasticsearch-get-started-build]]
-=== Build
+Elasticsearch provides several methods for ingesting data:
 
-Ready to build your own solution?
+* <<elasticsearch-ingest-data-through-api,{es} API>>
+* <<elasticsearch-ingest-data-through-integrations-connector-client,Connector clients>>
+* <<elasticsearch-ingest-data-file-upload,File Uploader>>
+* <<elasticsearch-ingest-data-through-beats,{beats}>>
+* <<elasticsearch-ingest-data-through-logstash,{ls}>>
+* https://github.com/elastic/crawler[Elastic Open Web Crawler]
 
-To learn more about sending and syncing data to {es}, or the search API and its query DSL, check <<elasticsearch-ingest-your-data>> and <<elasticsearch-http-apis>>.
+For more information on data ingestion and synchronization, 
+see <<elasticsearch-ingest-your-data>>. 
+To learn about the search API and query DSL, refer to <<elasticsearch-http-apis>>.
 
 ////
 /*
 - <DocLink slug="/serverless/elasticsearch/search-your-data" />
 - <DocLink slug="/serverless/elasticsearch/search-your-data-the-search-api" />
 */
 ////
+
+[discrete]
+[[elasticsearch-get-started-explore]]
+== Explore
+
+*Create a data view*: You can explore data using UI tools like Discover or Dashboards by creating a data view. 
+Or, you can use {es} aggregations to explore data through the API. Find more information in <<elasticsearch-explore-your-data>>.
+
+*Try Playground*: You can test {es} queries and combine {es} data with LLMs for retrieval augmented generation (RAG) in the 
+<<elasticsearch-playground>>.
+
+*Search your data*: You can perform search queries in {es} to filter by exact values, 
+conduct full-text searches, or use vector search. Learn more in <<elasticsearch-search-your-data>>.
+
+*Use semantic search*: You can retrieve data based on intent and context using NLP and vector embeddings with 
+<<elasticsearch-reference-semantic-search>>.