docs: add links to GitHub and feature tracker (#445)

* formatting

* add links

* fix CRD links

* fix CRD links

* fix CRD links

Author: fhennig

docs/modules/hive/pages/index.adoc

@@ -1,72 +1,82 @@
 = Stackable Operator for Apache Hive
 :description: The Stackable Operator for Apache Hive is a Kubernetes operator that can manage Apache Hive metastores. Learn about its features, resources, dependencies and demos, and see the list of supported Hive versions.
 :keywords: Stackable Operator, Hadoop, Apache Hive, Kubernetes, k8s, operator, engineer, big data, metadata, storage, query
-
-This is an operator for Kubernetes that can manage https://hive.apache.org[Apache Hive] metastores.  The Apache Hive
-metastore (HMS) was originally developed as part of Apache Hive. It stores information on the location of tables and
-partitions in file and blob storages such as xref:hdfs:index.adoc[Apache HDFS] and S3 and is now used by other tools
-besides Hive as well to access tables in files. This Operator does not support deploying Hive itself, but
-xref:trino:index.adoc[Trino] is recommended as an alternative query engine.
+:hive: https://hive.apache.org
+:github: https://github.com/stackabletech/hive-operator/
+:crd: {crd-docs-base-url}/hive-operator/{crd-docs-version}/
+:crd-hivecluster: {crd-docs}/hive.stackable.tech/hivecluster/v1alpha1/
+:feature-tracker: https://features.stackable.tech/unified
+
+[.link-bar]
+* {github}[GitHub {external-link-icon}^]
+* {feature-tracker}[Feature Tracker {external-link-icon}^]
+* {crd}[CRD documentation {external-link-icon}^]
+
+This is an operator for Kubernetes that can manage {hive}[Apache Hive] metastores.
+The Apache Hive metastore (HMS) was originally developed as part of Apache Hive.
+It stores information on the location of tables and partitions in file and blob storages such as xref:hdfs:index.adoc[Apache HDFS] and S3 and is now used by other tools besides Hive as well to access tables in files.
+This operator does not support deploying Hive itself, but xref:trino:index.adoc[Trino] is recommended as an alternative query engine.
 
 == Getting started
 
-Follow the xref:getting_started/index.adoc[Getting started guide] which will guide you through installing the Stackable
-Hive Operator and its dependencies. It walks you through setting up a Hive metastore and connecting it to a demo
-Postgres database and a Minio instance to store data in.
+Follow the xref:getting_started/index.adoc[Getting started guide] which will guide you through installing the Stackable Hive operator and its dependencies.
+It walks you through setting up a Hive metastore and connecting it to a demo Postgres database and a Minio instance to store data in.
 
-Afterwards you can consult the xref:usage-guide/index.adoc[] to learn more about tailoring your Hive metastore
-configuration to your needs, or have a look at the <<demos, demos>> for some example setups with either
-xref:trino:index.adoc[Trino] or xref:spark-k8s:index.adoc[Spark].
+Afterwards you can consult the xref:usage-guide/index.adoc[] to learn more about tailoring your Hive metastore configuration to your needs, or have a look at the <<demos, demos>> for some example setups with either xref:trino:index.adoc[Trino] or xref:spark-k8s:index.adoc[Spark].
 
 == Operator model
 
-The Operator manages the _HiveCluster_ custom resource. The cluster implements a single `metastore`
-xref:concepts:roles-and-role-groups.adoc[role].
+The operator manages the _HiveCluster_ custom resource.
+The cluster implements a single `metastore` xref:concepts:roles-and-role-groups.adoc[role].
 
-image::hive_overview.drawio.svg[A diagram depicting the Kubernetes resources created by the Stackable Operator for Apache Hive]
+image::hive_overview.drawio.svg[A diagram depicting the Kubernetes resources created by the Stackable operator for Apache Hive]
 
-For every role group the Operator creates a ConfigMap and StatefulSet which can have multiple replicas (Pods). Every
-role group is accessible through its own Service, and there is a Service for the whole cluster.
+For every role group the operator creates a ConfigMap and StatefulSet which can have multiple replicas (Pods).
+Every role group is accessible through its own Service, and there is a Service for the whole cluster.
 
-The Operator creates a xref:concepts:service_discovery.adoc[service discovery ConfigMap] for the Hive metastore
-instance. The discovery ConfigMap contains information on how to connect to the HMS.
+The operator creates a xref:concepts:service_discovery.adoc[service discovery ConfigMap] for the Hive metastore instance.
+The discovery ConfigMap contains information on how to connect to the HMS.
 
 == Dependencies
 
-The Stackable Operator for Apache Hive depends on the Stackable xref:commons-operator:index.adoc[commons],
-xref:secret-operator:index.adoc[secret] and xref:listener-operator:index.adoc[listener] operators.
+The Stackable operator for Apache Hive depends on the Stackable xref:commons-operator:index.adoc[commons], xref:secret-operator:index.adoc[secret] and  xref:listener-operator:index.adoc[listener] operators.
 
 == Required external component: An SQL database
 
-The Hive metastore requires a database to store metadata. Consult the xref:required-external-components.adoc[required
-external components page] for an overview of the supported databases and minimum supported versions.
+The Hive metastore requires an SQL database to store metadata.
+Consult the xref:required-external-components.adoc[required external components page] for an overview of the supported databases and minimum supported versions.
 
-==  [[demos]]Demos
+== [[demos]]Demos
 
 Three demos make use of the Hive metastore.
 
-The xref:demos:spark-k8s-anomaly-detection-taxi-data.adoc[] and xref:demos:trino-taxi-data.adoc[] use the HMS to store
-metadata information about taxi data. The first demo then analyzes the data using xref:spark-k8s:index.adoc[Apache Spark]
-and the second one using xref:trino:index.adoc[Trino].
+The xref:demos:spark-k8s-anomaly-detection-taxi-data.adoc[] and xref:demos:trino-taxi-data.adoc[] use the HMS to store metadata information about taxi data.
+The first demo then analyzes the data using xref:spark-k8s:index.adoc[Apache Spark] and the second one using xref:trino:index.adoc[Trino].
 
-The xref:demos:data-lakehouse-iceberg-trino-spark.adoc[] demo is the biggest demo available. It uses both Spark and
-Trino for analysis.
+The xref:demos:data-lakehouse-iceberg-trino-spark.adoc[] demo is the biggest demo available.
+It uses both Spark and Trino for analysis.
 
 == Why is the Hive query engine not supported?
 
-Only the metastore is supported, not Hive itself. There are several reasons why running Hive on Kubernetes may not be an
-optimal solution. The most obvious reason is that Hive requires YARN as an execution framework, and YARN assumes much of
-the same role as Kubernetes - i.e. assigning resources. For this reason we provide xref:trino:index.adoc[Trino] as a
-query engine in the Stackable Data Platform instead of Hive. Trino still uses the Hive Metastore, hence the inclusion of
-this operator as well. Trino should offer all the capabilities Hive offers including a lot of additional functionality,
-such as connections to other data sources.
+Only the metastore is supported, not Hive itself.
+There are several reasons why running Hive on Kubernetes may not be an optimal solution.
+The most obvious reason is that Hive requires YARN as an execution framework, and YARN assumes much of the same role as Kubernetes - i.e. assigning resources.
+For this reason we provide xref:trino:index.adoc[Trino] as a query engine in the Stackable Data Platform instead of Hive.
+Trino still uses the Hive Metastore, hence the inclusion of this operator as well.
+Trino should offer all the capabilities Hive offers including a lot of additional functionality, such as connections to other data sources.
 
 Additionally, Tables in the HMS can also be accessed from xref:spark-k8s:index.adoc[Apache Spark].
 
 == Supported versions
 
-The Stackable Operator for Apache Hive currently supports the Hive versions listed below.
+The Stackable operator for Apache Hive currently supports the Hive versions listed below.
 To use a specific Hive version in your HiveCluster, you have to specify an image - this is explained in the xref:concepts:product-image-selection.adoc[] documentation.
 The operator also supports running images from a custom registry or running entirely customized images; both of these cases are explained under xref:concepts:product-image-selection.adoc[] as well.
 
 include::partial$supported-versions.adoc[]
+
+== Useful links
+
+* The {github}[hive-operator {external-link-icon}^] GitHub repository
+* The operator feature overview in the {feature-tracker}[feature tracker {external-link-icon}^]
+* The {crd-hivecluster}[HiveCluster {external-link-icon}^] CRD documentation