Merge pull request #3444 from anupras-mohapatra-arm/servers-and-cloud-computing

Gerrit LP editorial review + some skill updates

Author: jasonrandrews

.github/skills/code-sample-review/SKILL.md

@@ -46,7 +46,7 @@ Check for:
 ## Workflow
 
 1. Identify the review scope and whether the request is editorial, technical, or mixed.
-2. Inspect surrounding prose before judging a code block; code samples should be evaluated in context.
+2. Inspect surrounding prose before judging a code block; code samples should be evaluated in context. If you've previously read the page, use context and don't re-read it unless there's a change since the last read. 
 3. Depending on the type of review, suggest fixes as follows:
   - For review requests, report issues by file and line when possible, ordered by learner impact.
   - For edit requests, report issues and suggest focused changes that preserve technical intent and existing repository patterns.

.github/skills/link-text-review/SKILL.md

@@ -18,7 +18,7 @@ This skill focuses on anchor text and link clarity. For tables, notices, tab pan
 
 ## Workflow
 
-1. Identify the target file, directory, section, or selected text.
+1. Identify the target file, directory, section, or selected text. If you've previously read the page, use context and don't re-read it unless there's a change since the last read. 
 2. Read surrounding context before suggesting any changes.
 3. After understanding the context of the URL, suggest concise and natural rewrites to the anchor text based on `Quality rules`. 
 4. After the user accepts suggestions, make changes, then re-open or search changed lines to verify the Markdown link syntax is valid.

.github/skills/markdown-component-edit/SKILL.md

@@ -18,7 +18,7 @@ This skill is best when the user highlights text, names a section, or asks for a
 
 ## Workflow
 
-1. Use the user's highlighted, selected, or explicitly named text as the edit target. If the target is ambiguous, ask for the exact text, file, or section before editing. 
+1. Use the user's highlighted, selected, or explicitly named text as the edit target. If the target is ambiguous, ask for the exact text, file, or section before editing. If you've previously read the page, use context and don't re-read it unless there's a change since the last read. 
 2. Inspect nearby Markdown so the new component fits the surrounding flow.
 3. Verify internal links before adding or changing them when practical.
 4. Use `component rules` and the `component-patterns` reference and do one of the following:

.github/skills/metadata-description-update/SKILL.md

@@ -31,7 +31,7 @@ This skill is for search and discovery metadata. For draft visibility metadata,
 ## Workflow
 
 1. Identify whether the target is an install guide content page, a Learning Path `_index.md`, or a Learning Path content page.
-2. Read the title, existing description, headings, introduction, task flow, code or command context, and validation or conclusion.
+2. Read the title, existing description, headings, introduction, task flow, code or command context, and validation or conclusion. If you've previously read the page, use context and don't re-read it unless there's a change since the last read. 
 3. Add or revise the `description` field in front matter based on quality rules.
 4. After editing, re-open or search the files to verify each changed target has one `description` field.
 5. Report files changed and note any skipped files.

.github/skills/seo-geo-aeo-review/SKILL.md

@@ -23,8 +23,8 @@ For focused front matter `description` edits only, use `.github/skills/metadata-
 
 ## Workflow
 
-1. Identify the target content type and target developer intent.
-2. Read the title, front matter description, headings, introduction, prerequisites, main task flow, validation, conclusion, and further reading.
+1. Identify the target content type and target developer intent. 
+2. Read the title, front matter description, headings, introduction, prerequisites, main task flow, validation, conclusion, and further reading. If you've previously read a page, use context and don't re-read it unless there's a change since the last read. 
 3. State the page's owned task in one sentence. If the task is unclear or too broad, flag it.
 4. Review SEO signals:
    - The title is task-led and includes the main technology, platform, or tool.

.github/skills/writing-style-review/SKILL.md

@@ -10,7 +10,7 @@ Use this skill for granular prose, voice, readability, terminology, and style re
 ## Workflow
 
 1. Identify the target file, section, or selected text.
-2. Read surrounding context so style edits preserve the author's intent and the technical flow.
+2. Read surrounding context so style edits preserve the author's intent and the technical flow. If you've previously read the page, use context and don't re-read it unless there's a change since the last read. 
 3. Review the target against the guidelines defined in this skill.
 4. Depending on request type, do the following:
   - For review requests, report high-impact style issues by file and line when possible. 

content/learning-paths/servers-and-cloud-computing/gerrit-on-gcp/_index.md

@@ -1,11 +1,7 @@
 ---
-title: Deploy Gerrit on Google Cloud C4A
+title: Deploy Gerrit on a Google Cloud C4A instance 
 
-draft: true
-cascade:
-    draft: true
-
-description: Learn how to install and configure Gerrit on Google Cloud Axion C4A Arm64 instances and benchmark its performance
+description: Deploy Gerrit on an Ubuntu 24.04 arm64 Google Cloud C4A virtual machine powered by Google Axion processors, verify web access, and benchmark baseline performance.
 minutes_to_complete: 30
 
 who_is_this_for: This is an introductory topic for developers deploying Gerrit in Arm Linux environments, specifically using Google Cloud C4A virtual machines (VM) powered by Axion processors. 
@@ -20,8 +16,59 @@ prerequisites:
   - A [Google Cloud Platform (GCP)](https://cloud.google.com/free) account with billing enabled  
   - Basic familiarity with [Gerrit](https://gerrit-review.googlesource.com/Documentation/intro-gerrit-walkthrough-github.html)
 
+# START generated_summary_faq
+generated_summary_faq:
+  template_version: summary-faq-v3
+  generated_at: '2026-06-29T15:40:39Z'
+  generator: ai
+  ai_assisted: true
+  ai_review_required: true
+  model: gpt-5
+  prompt_template: summary-faq-v3
+  source_hash: 7b4d6c5bb04f6ab123243d184e404c074a68440084fd8b9100b2536db2e56a46
+  summary_generated_at: '2026-06-29T15:40:39Z'
+  summary_source_hash: 7b4d6c5bb04f6ab123243d184e404c074a68440084fd8b9100b2536db2e56a46
+  faq_generated_at: '2026-06-29T15:40:39Z'
+  faq_source_hash: 7b4d6c5bb04f6ab123243d184e404c074a68440084fd8b9100b2536db2e56a46
+  summary: >-
+    You'll deploy Gerrit on an Ubuntu 24.04 LTS `arm64` virtual
+    machine (VM) in Google Cloud using the C4A instance family powered by Google Axion processors (Arm
+    Neoverse-V2). First, you'll enable external access by creating a Google Cloud firewall
+    rule for TCP port 8080. Then, you'll provision a `c4a-standard-4` VM, and install Gerrit with the required
+    packages. You'll confirm a successful setup by loading the Gerrit web console, then establish
+    a baseline by running a benchmarking script that exercises common Gerrit operations.
+    The result is a functional Arm-based Gerrit deployment on Google Cloud with initial performance
+    data suitable for comparison and follow-up analysis.
+  faqs:
+  - question: Which Google Cloud port must be open to access the Gerrit web console?
+    answer: >-
+      Open TCP port `8080`. Create a firewall rule in the Google Cloud console to allow incoming
+      traffic on port `8080` so the Gerrit web interface is reachable.
+  - question: What virtual machine configuration should I use for this deployment?
+    answer: >-
+      Use a Google Axion C4A instance with the `c4a-standard-4` machine type (4 vCPUs, 16 GB memory).
+      The VM runs Ubuntu 24.04 LTS on arm64.
+  - question: What packages should I install before setting up Gerrit?
+    answer: >-
+      Update the system and install `wget`, `default-jdk`, `git`, and `net-tools`. The steps show running
+      apt update and apt upgrade before installing these tools.
+  - question: How do I verify that Gerrit is running after installation?
+    answer: >-
+      Confirm that the Gerrit web console loads on port `8080` after completing the install steps.
+      If it doesn't load, review the command outputs from the installation for errors.
+  - question: How do I run the benchmark and what should I expect?
+    answer: >-
+      Clone the `gerrit_test` repository into your VM and run the provided script with `SYNTH_PROFILE=production_like`
+      and `REQUIRE_GERRIT_METRICS=true`. The script exercises Gerrit functions and captures timing
+      and performance data for baseline measurement.
+# END generated_summary_faq
+
 author: Doug Anson
 
+generate_summary_faq: false
+rerun_summary: false
+rerun_faqs: false
+
 ##### Tags
 skilllevels: Introductory
 subjects: CI-CD
@@ -42,8 +89,8 @@ operatingsystems:
 # ================================================================================
 further_reading:
   - resource:
-      title: Google Cloud documentation
-      link: https://cloud.google.com/docs
+      title: Google Cloud documentation for C4A VMs
+      link: https://docs.cloud.google.com/compute/docs/general-purpose-machines#c4a_series
       type: documentation
 
   - resource:
@@ -65,3 +112,4 @@ weight: 1
 layout: "learningpathall"
 learning_path_main_page: "yes"
 ---
+

content/learning-paths/servers-and-cloud-computing/gerrit-on-gcp/background.md

@@ -1,23 +1,31 @@
 ---
 title: About Gerrit and Google Axion C4A
 
+description: Review how Gerrit and Google Cloud C4A virtual machines powered by Google Axion processors support the Arm-based deployment and benchmarking workflow.
+
 weight: 2
 
 layout: "learningpathall"
 ---
 
 ## Google Axion C4A Arm instances in Google Cloud
 
-Google Axion C4A is a family of Arm-based virtual machines built on Google’s custom Axion CPU, which is based on Arm Neoverse-V2 cores. Designed for high-performance and energy-efficient computing, these virtual machines offer strong performance for modern cloud workloads such as CI/CD pipelines, microservices, media processing, and general-purpose applications.
+C4A is a family of Arm-based virtual machines built on Google’s custom Axion CPU, which is based on Arm Neoverse-V2 cores. Designed for high-performance and energy-efficient computing, these virtual machines offer strong performance for modern cloud workloads.
 
-The C4A series provides a cost-effective alternative to x86 virtual machines while leveraging the scalability and performance benefits of the Arm architecture in Google Cloud.
+The C4A series provides a cost-effective alternative to x86 virtual machines while using the scalability and performance benefits of the Arm architecture in Google Cloud.
 
-To learn more about Google Axion, refer to the [Introducing Google Axion Processors, our new Arm-based CPUs](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu) blog.
+To learn more about Google Axion, see [Introducing Google Axion Processors, our new Arm-based CPUs](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu).
 
 ## Gerrit
 
-Gerrit is an open-source, web-based code review system for Git repositories that lets teams review proposed commits before they are merged into a codebase. It is especially useful for projects that want patchset-based reviews, inline comments, approval labels, fine-grained permissions, and integration with CI/CD systems before changes land. 
+Gerrit is an open-source, web-based code review system for Git repositories that lets teams review proposed commits before they are merged into a codebase. It's especially useful for projects that want patchset-based reviews, inline comments, approval labels, fine-grained permissions, and integration with CI/CD systems before changes land. 
+
+To learn more about how Gerrit fits into a development workflow and how to review, upload, and manage changes, start with the official Gerrit product overview and user guide.
+
+There's also a [Basic Gerrit Walkthrough — For GitHub Users](https://gerrit-review.googlesource.com/Documentation/intro-gerrit-walkthrough-github.html) which explains the core principles of code review in Gerrit compared to pull requests. 
+
+## What you've learned and what's next
 
-To learn more, start with the official Gerrit site and documentation, especially the product overview and user guide, which explain how Gerrit fits into a development workflow and how to review, upload, and manage changes. 
+You've now learned about Gerrit and the Google Axion C4A instance family that you'll use for benchmarking. 
 
-There is also a [Basic Gerrit Walkthrough — For GitHub Users](https://gerrit-review.googlesource.com/Documentation/intro-gerrit-walkthrough-github.html) which explains the core principles of code review in Gerrit compared to pull requests. 
+Next, you'll create a firewall rule on Google Cloud Platform to make your Gerrit deployment accessible.