fix callouts

modules/create-cluster-logging-cli.adoc

@@ -67,11 +67,17 @@ spec:
 However, an unmanaged deployment does not receive updates until OpenShift Logging is placed back into a managed state. Placing a deployment back into a managed state might revert any modifications you made.
 <3> Settings for configuring Elasticsearch. Using the custom resource (CR), you can configure shard replication policy and persistent storage.
 <4> Specify the length of time that Elasticsearch should retain each log source. Enter an integer and a time designation: weeks(w), hours(h/H), minutes(m) and seconds(s). For example, `7d` for seven days. Logs older than the `maxAge` are deleted. You must specify a retention policy for each log source or the Elasticsearch indices will not be created for that source.
-<5> Specify the number of Elasticsearch nodes. The maximum number of Elasticsearch control plane nodes is three. If you specify a `nodeCount` greater than `3`, {product-title} creates three Elasticsearch nodes that are master-eligible nodes, with the master, client, and data roles. The additional Elasticsearch nodes are created as data-only nodes, using client and data roles. Control plane nodes perform cluster-wide actions such as creating or deleting an index, shard allocation, and tracking nodes. Data nodes hold the shards and perform data-related operations such as CRUD, search, and aggregations. Data-related operations are I/O-, memory-, and CPU-intensive. It is important to monitor these resources and to add more data nodes if the current nodes are overloaded.
-+
---
+<5> Specify the number of Elasticsearch nodes.
+<6> Enter the name of an existing storage class for Elasticsearch storage. For best performance, specify a storage class that allocates block storage. If you do not specify a storage class, {product-title} deploys OpenShift Logging with ephemeral storage only.
+<7> Specify the CPU and memory requests for Elasticsearch as needed. If you leave these values blank, the OpenShift Elasticsearch Operator sets default values that are sufficient for most deployments. The default values are `16Gi` for the memory request and `1` for the CPU request.
+<8> Specify the CPU and memory requests for the Elasticsearch proxy as needed. If you leave these values blank, the OpenShift Elasticsearch Operator sets default values that should be sufficient for most deployments. The default values are  `256Mi` for the memory request and `100m` for the CPU request.
+<9> Settings for configuring Kibana. Using the CR, you can scale Kibana for redundancy and configure the CPU and memory for your Kibana pods. For more information, see *Configuring the log visualizer*.
+<10> Settings for configuring Fluentd. Using the CR, you can configure Fluentd CPU and memory limits. For more information, see *Configuring Fluentd*.
+
+The maximum number of Elasticsearch control plane nodes is three. If you specify a `nodeCount` greater than `3`, {product-title} creates three Elasticsearch nodes that are master-eligible nodes, with the master, client, and data roles. The additional Elasticsearch nodes are created as data-only nodes, using client and data roles. Control plane nodes perform cluster-wide actions such as creating or deleting an index, shard allocation, and tracking nodes. Data nodes hold the shards and perform data-related operations such as CRUD, search, and aggregations. Data-related operations are I/O-, memory-, and CPU-intensive. It is important to monitor these resources and to add more data nodes if the current nodes are overloaded.
+
 For example, if `nodeCount=4`, the following nodes are created:
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+
 .Example output
 [source,terminal]
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@@ -81,14 +87,8 @@ elasticsearch-cdm-x6kdekli-1   1/1     1            1           18h
 elasticsearch-cdm-x6kdekli-2   1/1     1            0           6m49s
 elasticsearch-cdm-x6kdekli-3   1/1     1            0           6m44s
 ----
-+
+
 The number of primary shards for the index templates is equal to the number of Elasticsearch data nodes.
---
-<6> Enter the name of an existing storage class for Elasticsearch storage. For best performance, specify a storage class that allocates block storage. If you do not specify a storage class, {product-title} deploys OpenShift Logging with ephemeral storage only.
-<7> Specify the CPU and memory requests for Elasticsearch as needed. If you leave these values blank, the OpenShift Elasticsearch Operator sets default values that are sufficient for most deployments. The default values are `16Gi` for the memory request and `1` for the CPU request.
-<8> Specify the CPU and memory requests for the Elasticsearch proxy as needed. If you leave these values blank, the OpenShift Elasticsearch Operator sets default values that should be sufficient for most deployments. The default values are  `256Mi` for the memory request and `100m` for the CPU request.
-<9> Settings for configuring Kibana. Using the CR, you can scale Kibana for redundancy and configure the CPU and memory for your Kibana pods. For more information, see *Configuring the log visualizer*.
-<10> Settings for configuring Fluentd. Using the CR, you can configure Fluentd CPU and memory limits. For more information, see *Configuring Fluentd*.
 
 . Apply the `ClusterLogging` object by running the following command:
 +