setup: add information about cluster

setup.md

@@ -7,8 +7,8 @@ title: Setup
 This lesson teaches the principles of containerised scientific workflows by means of using the
 [REANA](http://www.reana.io/) reproducible analysis platform.
 
-The participants should either install [reana-client](https://pypi.org/project/reana-client/) on
-their laptops:
+As a participant, you should either install [reana-client](https://pypi.org/project/reana-client/)
+on your laptop:
 
 ```bash
 virtualenv ~/.virtualenvs/reana
@@ -17,15 +17,15 @@ pip install reana-client
 ```
 {: .source}
 
-Alternatively, the participants can log into CERN's LXPLUS cluster using `ssh lxplus.cern.ch` and
-activate a pre-existing environment there:
+Alternatively, you can also log into CERN's LXPLUS cluster using `ssh lxplus.cern.ch` and activate a
+pre-existing environment there:
 
 ```bash
 source /afs/cern.ch/user/r/reana/public/reana/bin/activate
 ```
 {: .source}
 
-After installation of `reana-client`, please check whether the client works by asking for its
+After the installation of `reana-client`, please check whether your client works by asking for its
 version:
 
 ```bash
@@ -38,6 +38,18 @@ reana-client version
 ```
 {: .output}
 
----
+### REANA cluster
+
+This lesson will use the [reana.cern.ch](https://reana.cern.ch) cluster instance to run the client
+workflows.
+
+Please verify whether you can log into [reana.cern.ch](https://reana.cern.ch) using your CERN
+account.
+
+### Advanced alternative
+
+Alternatively, if you do not have access to CERN computing cluster and if you are a Docker and
+Kubernetes power user who would like to follow this lesson at home, you could also [install your own
+REANA cluster](https://docs.reana.io/administration/deployment/deploying-locally/#for-researchers).
 
 {% include links.md %}