Docs new landing page (#385)

* remove unneccessary text

* New intro text

* Added getting started blurp

* Added demos

* Added operator model

* fixed typo

* Update docs/modules/hdfs/pages/index.adoc

Co-authored-by: Malte Sander <[email protected]>

* Update docs/modules/hdfs/pages/index.adoc

Co-authored-by: Malte Sander <[email protected]>

---------

Co-authored-by: Malte Sander <[email protected]>

Author: fhennig

docs/modules/hdfs/images/hdfs_overview.drawio.svg

@@ -1,18 +1,25 @@
 = Stackable Operator for Apache HDFS
+:description: The Stackable Operator for Apache HDFS is a Kubernetes operator that can manage Apache HDFS clusters. Learn about its features, resources, dependencies and demos, and see the list of supported HDFS versions.
+:keywords: Stackable Operator, Hadoop, Apache HDFS, Kubernetes, k8s, operator, engineer, big data, metadata, storage, cluster, distributed storage
 
-The Stackable Operator for https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsUserGuide.html[Apache HDFS] is used to set up HFDS in high-availability mode. It depends on the xref:zookeeper:ROOT:index.adoc[] to operate a ZooKeeper cluster to coordinate the active and standby NameNodes.
+The Stackable Operator for https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsUserGuide.html[Apache HDFS] (Hadoop Distributed File System) is used to set up HFDS in high-availability mode. HDFS is a distributed file system designed to store and manage massive amounts of data across multiple machines in a fault-tolerant manner. The Operator depends on the xref:zookeeper:index.adoc[] to operate a ZooKeeper cluster to coordinate the active and standby NameNodes.
 
-NOTE: This operator only works with images from the https://repo.stackable.tech/#browse/browse:docker:v2%2Fstackable%2Fhadoop[Stackable] repository
+== Getting started
 
-== Roles
+Follow the xref:getting_started/index.adoc[Getting started guide] which will guide you through installing the Stackable HDFS and ZooKeeper Operators, setting up ZooKeeper and HDFS and writing a file to HDFS to verify that everything is set up correctly.
 
-Three xref:home:concepts:roles-and-role-groups.adoc[roles] of the HDFS cluster are implemented:
+Afterwards you can consult the xref:usage-guide/index.adoc[] to learn more about tailoring your HDFS configuration to your needs, or have a look at the <<demos, demos>> for some example setups.
+
+== Operator model
+
+The Operator manages the _HdfsCluster_ custom resource. The cluster implements three xref:home:concepts:roles-and-role-groups.adoc[roles]:
 
 * DataNode - responsible for storing the actual data.
 * JournalNode - responsible for keeping track of HDFS blocks and used to perform failovers in case the active NameNode fails. For details see: https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HDFSHighAvailabilityWithQJM.html
 * NameNode - responsible for keeping track of HDFS blocks and providing access to the data.
 
-== Kubernetes objects
+
+image::hdfs_overview.drawio.svg[A diagram depicting the Kubernetes resources created by the Stackable Operator for Apache HDFS]
 
 The operator creates the following K8S objects per role group defined in the custom resource.
 
@@ -28,15 +35,22 @@ In the custom resource you can specify the number of replicas per role group (Na
 * 1 JournalNode
 * 1 DataNode (should match at least the `clusterConfig.dfsReplication` factor)
 
+The Operator creates a xref:concepts:service_discovery.adoc[service discovery ConfigMap] for the HDFS instance. The discovery ConfigMap contains the `core-site.xml` file and the `hdfs-site.xml` file.
+
+== Dependencies
+
+HDFS depends on ZooKeeper for coordination between nodes. You can run a ZooKeeper cluster with the xref:zookeeper:index.adoc[]. Additionally, the xref:commons-operator:index.adoc[] and xref:secret-operator:index.adoc[] are needed.
+
+== [[demos]]Demos
+
+Two demos that use HDFS are available.
+
+**xref:stackablectl::demos/hbase-hdfs-load-cycling-data.adoc[]** loads a dataset of cycling data from S3 into HDFS and then uses HBase to analyze the data.
+
+**xref:stackablectl::demos/jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data.adoc[]** showcases the integration between HDFS and Jupyter. New York Taxi data is stored in HDFS and analyzed in a Jupyter notebook.
+
 == Supported Versions
 
 The Stackable Operator for Apache HDFS currently supports the following versions of HDFS:
 
 include::partial$supported-versions.adoc[]
-
-== Docker image
-
-[source]
-----
-docker pull docker.stackable.tech/stackable/hadoop:<version>
-----