Adding CI

Author: cardil

.github/workflows/docs.yml

@@ -5,6 +5,9 @@ on:
     branches:
       - master
       - main
+  pull_request:
+    branches:
+      - *
 env:
   SITE_DIR: "gh-pages"
 jobs:
@@ -13,7 +16,7 @@ jobs:
     runs-on: [ubuntu-latest]
     steps:
       - name: Checkout
-        uses: actions/checkout@v2
+        uses: actions/checkout@v4
       - name: "Generate site using antora site action"
         uses: kameshsampath/antora-site-action@master
         with:
@@ -27,9 +30,10 @@ jobs:
     runs-on: [ubuntu-latest]
     needs: [build_site]
     name: "Deploy GitHub Pages"
+    if: github.event_name != 'pull_request'
     steps:
       - name: Checkout
-        uses: actions/checkout@v2
+        uses: actions/checkout@v4
       - name: Download generated site
         uses: actions/download-artifact@v4
         with:

documentation/modules/ROOT/pages/01-pattern.adoc

@@ -19,9 +19,9 @@ The core of this solution is an event mesh—a dynamic, flexible layer that
 routes, retries, and processes asynchronous events across distributed 
 components. Using _Knative Eventing_ and _CloudEvents_, this pattern enables:
 
- * *Reliable delivery* of events with retry mechanisms.
- * Simplified *asynchronous workflows*.
- * *Decoupling* of services to improve scalability, testability and resilience.
+ - *Reliable delivery* of events with retry mechanisms.
+ - Simplified *asynchronous workflows*.
+ - *Decoupling* of services to improve scalability, testability and resilience.
 
 The approach of Cabs engineering team is to extract well-defined services, using
 the _CQRS_ pattern to  identify _Commands_ from _Queries_, and model the 

documentation/modules/ROOT/pages/02-architecture.adoc

@@ -1,4 +1,4 @@
-= Solution Pattern: Name Template
+= Building Apps around the Event Mesh
 :sectnums:
 :sectlinks:
 :doctype: book
@@ -7,12 +7,18 @@
 
 Introduction for the architecture of this solution pattern.
 
-== Common Challenges 
-
 [#tech_stack]
 == Technology Stack
 
-// Change links and text here as you see fit.
+
+The solution employs Command Query Responsibility Segregation (CQRS) to separate commands and queries:
+
+Commands are modeled as asynchronous events and handled by the event mesh.
+
+Queries are synchronous operations safe to retry.
+
+
+
 * Red Hat supported products
 ** https://www.redhat.com/en/technologies/cloud-computing/openshift[Red Hat OpenShift]
 ** Red Hat Application Foundation