Clean up HTTP feature support (#9)

Author: JoshMock

docs/guide/configuration.asciidoc

@@ -4,48 +4,47 @@
 This page contains information about the most important configuration options of 
 the Python {es} client.
 
-
 [discrete]
 [[tls-and-ssl]]
 === TLS/SSL
 
-The options in this section can only be used when the node is configured for HTTPS. An error will be raised if using these options with an HTTP node.
+The options in this section will only be necessary when connecting to Elasticsearch Serverless via a proxy not managed by Elastic that uses its own certificates.
 
 [discrete]
-==== Verifying server certificates
+==== Verifying certificates
 
-The typical route to verify a cluster certificate is via a "CA bundle" which can be specified via the `ca_certs` parameter. If no options are given and the https://github.com/certifi/python-certifi[certifi package] is installed then certifi's CA bundle is used by default.
+The typical route to verify a certificate is via a "CA bundle" which can be specified via the `ca_certs` parameter. If no options are given and the https://github.com/certifi/python-certifi[certifi package] is installed then certifi's CA bundle is used by default.
 
 If you have your own CA bundle to use you can configure via the `ca_certs` parameter:
 
 [source,python]
 ------------------------------------
 es = Elasticsearch(
-    "https://...",
+    cloud_id='project-name:ABCD...',
     ca_certs="/path/to/certs.pem"
 )
 ------------------------------------
 
 If using a generated certificate or certificate with a known fingerprint you can use the `ssl_assert_fingerprint` to specify the fingerprint which tries to match the server's leaf certificate during the TLS handshake. If there is any matching certificate the connection is verified, otherwise a `TlsError` is raised.
 
-In Python 3.9 and earlier only the leaf certificate will be verified but in Python 3.10+ private APIs are used to verify any certificate in the certificate chain. This helps when using certificates that are generated on a multi-node cluster.
+In Python 3.9 and earlier only the leaf certificate will be verified but in Python 3.10+ private APIs are used to verify any certificate in the certificate chain.
 
 [source,python]
 ------------------------------------
 es = Elasticsearch(
-    "https://...",
+    cloud_id='project-name:ABCD...',
     ssl_assert_fingerprint=(
         "315f5bdb76d078c43b8ac0064e4a0164612b1fce77c869345bfc94c75894edd3"
     )
 )
 ------------------------------------
 
-To disable certificate verification use the `verify_certs=False` parameter. This option should be avoided in production, instead use the other options to verify the clusters' certificate.
+To disable certificate verification use the `verify_certs=False` parameter. This option should be avoided in production, instead use the other options to verify the certificate.
 
 [source,python]
 ------------------------------------
 es = Elasticsearch(
-    "https://...",
+    cloud_id='project-name:ABCD...',
     verify_certs=False
 )
 ------------------------------------
@@ -58,7 +57,6 @@ Configuring the minimum TLS version to connect to is done via the `ssl_version`
 [source,python]
 ------------------------------------
 import ssl
-
 es = Elasticsearch(
     ...,
     ssl_version=ssl.TLSVersion.TLSv1_2
@@ -88,43 +86,38 @@ For advanced users an `ssl.SSLContext` object can be used for configuring TLS vi
 [source,python]
 ------------------------------------
 import ssl
-
 # Create and configure an SSLContext
 ctx = ssl.create_default_context()
 ctx.load_verify_locations(...)
-
 es = Elasticsearch(
     ...,
     ssl_context=ctx
 )
 ------------------------------------
 
-
 [discrete]
 [[compression]]
 === HTTP compression
 
 Compression of HTTP request and response bodies can be enabled with the `http_compress` parameter.
 If enabled then HTTP request bodies will be compressed with `gzip` and HTTP responses will include
-the `Accept-Encoding: gzip` HTTP header. By default compression is disabled.
+the `Accept-Encoding: gzip` HTTP header. HTTP compression is recommended for all Serverless requests, and is enabled by default.
+
+To disable:
 
 [source,python]
 ------------------------------------
 es = Elasticsearch(
     ...,
-    http_compress=True  # Enable compression!
+    http_compress=False
 )
 ------------------------------------
 
-HTTP compression is recommended to be enabled when requests are traversing the network.
-Compression is automatically enabled when connecting to Elastic Cloud.
-
-
 [discrete]
 [[timeouts]]
 === Request timeouts
 
-Requests can be configured to timeout if taking too long to be serviced. The `request_timeout` parameter can be passed via the client constructor or the client `.options()` method. When the request times out the node will raise a `ConnectionTimeout` exception which can trigger retries.
+Requests can be configured to timeout if taking too long to be serviced. The `request_timeout` parameter can be passed via the client constructor or the client `.options()` method. When the request times out the project will raise a `ConnectionTimeout` exception which can trigger retries.
 
 Setting `request_timeout` to `None` will disable timeouts.
 
@@ -159,12 +152,11 @@ es.options(
 )
 ------------------------------------
 
-
 [discrete]
 [[retries]]
 === Retries
 
-Requests can be retried if they don't return with a successful response. This provides a way for requests to be resilient against transient failures or overloaded nodes.
+Requests can be retried if they don't return with a successful response. This provides a way for requests to be resilient against transient failures.
 
 The maximum number of retries per request can be configured via the `max_retries` parameter. Setting this parameter to 0 disables retries. This parameter can be set in the client constructor or per-request via the client `.options()` method:
 
@@ -246,115 +238,6 @@ resp.meta.status  # Can be either '2XX' or '400'
 
 When using the `ignore_status` parameter the error response will be returned serialized just like a non-error response. In these cases it can be useful to inspect the HTTP status of the response. To do this you can inspect the `resp.meta.status`.
 
-[discrete]
-[[sniffing]]
-=== Sniffing for new nodes
-
-Additional nodes can be discovered by a process called "sniffing" where the client will query the cluster for more nodes that can handle requests.
-
-Sniffing can happen at three different times: on client instantiation, before requests, and on a node failure. These three behaviors can be enabled and disabled with the `sniff_on_start`, `sniff_before_requests`, and `sniff_on_node_failure` parameters.
-
-IMPORTANT: When using an HTTP load balancer or proxy you cannot use sniffing functionality as the cluster would supply the client with IP addresses to directly connect to the cluster, circumventing the load balancer. Depending on your configuration this might be something you don't want or break completely.
-
-[discrete]
-==== Waiting between sniffing attempts
-
-To avoid needlessly sniffing too often there is a delay between attempts to discover new nodes. This value can be controlled via the `min_delay_between_sniffing` parameter.
-
-[discrete]
-==== Filtering nodes which are sniffed
-
-By default nodes which are marked with only a `master` role will not be used. To change the behavior the parameter `sniffed_node_callback` can be used. To mark a sniffed node not to be added to the node pool
-return `None` from the `sniffed_node_callback`, otherwise return a `NodeConfig` instance.
-
-[source,python]
-------------------------------------
-from typing import Optional, Dict, Any
-from elastic_transport import NodeConfig
-from elasticsearch import Elasticsearch
-
-def filter_master_eligible_nodes(
-    node_info: Dict[str, Any],
-    node_config: NodeConfig
-) -> Optional[NodeConfig]:
-    # This callback ignores all nodes that are master eligible
-    # instead of master-only nodes (default behavior)
-    if "master" in node_info.get("roles", ()):
-        return None
-    return node_config
-
-client = Elasticsearch(
-    "https://localhost:9200",
-    sniffed_node_callback=filter_master_eligible_nodes
-)
-------------------------------------
-
-The `node_info` parameter is part of the response from the `nodes.info()` API, below is an example
-of what that object looks like:
-
-[source,json]
-------------------------------------
-{
-  "name": "SRZpKFZ",
-  "transport_address": "127.0.0.1:9300",
-  "host": "127.0.0.1",
-  "ip": "127.0.0.1",
-  "version": "5.0.0",
-  "build_hash": "253032b",
-  "roles": ["master", "data", "ingest"],
-  "http": {
-    "bound_address": ["[fe80::1]:9200", "[::1]:9200", "127.0.0.1:9200"],
-    "publish_address": "1.1.1.1:123",
-    "max_content_length_in_bytes": 104857600
-  }
-}
-------------------------------------
-
-
-[discrete]
-[[node-pool]]
-=== Node Pool
-
-[discrete]
-==== Selecting a node from the pool
-
-You can specify a node selector pattern via the `node_selector_class` parameter. The supported values are `round_robin` and `random`. Default is `round_robin`.
-
-[source,python]
-------------------------------------
-es = Elasticsearch(
-    ...,
-    node_selector_class="round_robin"
-)
-------------------------------------
-
-Custom selectors are also supported:
-
-[source,python]
-------------------------------------
-from elastic_transport import NodeSelector
-
-class CustomSelector(NodeSelector):
-    def select(nodes): ...
-
-es = Elasticsearch(
-    ...,
-    node_selector_class=CustomSelector
-)
-------------------------------------
-
-[discrete]
-==== Marking nodes dead and alive
-
-Individual nodes of Elasticsearch may have transient connectivity or load issues which may make them unable to service requests. To combat this the pool of nodes will detect when a node isn't able to service requests due to transport or API errors.
-
-After a node has been timed out it will be moved back to the set of "alive" nodes but only after the node returns a successful response will the node be marked as "alive" in terms of consecutive errors.
-
-The `dead_node_backoff_factor` and `max_dead_node_backoff` parameters can be used to configure how long the node pool will put the node into timeout with each consecutive failure. Both parameters use a unit of seconds.
-
-The calculation is equal to `min(dead_node_backoff_factor * (2 ** (consecutive_failures - 1)), max_dead_node_backoff)`.
-
-
 [discrete]
 [[serializer]]
 === Serializers
@@ -365,7 +248,7 @@ You can define custom serializers via the `serializers` parameter:
 
 [source,python]
 ------------------------------------
-from elasticsearch import Elasticsearch, JsonSerializer
+from elasticsearch_serverless import Elasticsearch, JsonSerializer
 
 class JsonSetSerializer(JsonSerializer):
     """Custom JSON serializer that handles Python sets"""
@@ -395,7 +278,7 @@ For all of the built-in HTTP node implementations like `urllib3`, `requests`, an
 
 [source,python]
 ------------------------------------
-from elasticsearch import Elasticsearch
+from elasticsearch_serverless import Elasticsearch
 
 es = Elasticsearch(
     ...,
@@ -407,7 +290,7 @@ You can also specify a custom node implementation via the `node_class` parameter
 
 [source,python]
 ------------------------------------
-from elasticsearch import Elasticsearch
+from elasticsearch_serverless import Elasticsearch
 from elastic_transport import Urllib3HttpNode
 
 class CustomHttpNode(Urllib3HttpNode):
@@ -420,14 +303,14 @@ es = Elasticsearch(
 ------------------------------------
 
 [discrete]
-==== HTTP connections per node
+==== HTTP connections
 
-Each node contains its own pool of HTTP connections to allow for concurrent requests. This value is configurable via the `connections_per_node` parameter:
+The client maintains a pool of HTTP connections to the Elasticsearch Serverless project to allow for concurrent requests. This value is configurable via the `connections` parameter:
 
 [source,python]
 ------------------------------------
 es = Elasticsearch(
     ...,
-    connections_per_node=5
+    connections=5
 )
 ------------------------------------