merge: merge develop into master adding dark mode styles for arsys logo

.github/workflows/03.3.agentic_v2_videos.yml

@@ -78,7 +78,7 @@ jobs:
         run: |
           git config --global user.name "Nubenetes Bot"
           git config --global user.email "bot@nubenetes.com"
-          git add data/inventory.yaml v2-docs/videos.md
+          git add data/inventory.yaml v2-docs/videos/
           if git diff --staged --quiet; then
             echo "No automated changes to commit."
           else

.github/workflows/04.1.agentic_v2_publish.yml

@@ -63,6 +63,12 @@ jobs:
         run: |
           python -u src/v2_video_portal.py
 
+      - name: Execute Mosaic Reorganization
+        env:
+          PYTHONPATH: ${{ github.workspace }}
+        run: |
+          python src/reorganize_mosaic.py
+
       - name: Run V2 Publisher (Render-Only)
         env:
           PYTHONPATH: ${{ github.workspace }}

GEMINI.md

@@ -61,7 +61,10 @@ This file contains the accumulated instructions and long-term vision for the aut
     - **URL Protocol Integrity**: All URLs MUST use the complete and correct protocol prefix (`https://` or `http://`). AI agents MUST ensure that automated edits or mass cleanup tasks NEVER corrupt the protocol (e.g., by reducing `https://` to `https:/`).
     - **Manual Priority**: AI agents MUST NOT overwrite existing manual descriptions or stars in the V1 archive files. Enrichment is strictly for the YAML database and the V2 portal.
 
-23. **YouTube Mosaic Exemption**: In `docs/index.md` and `v2-docs/index.md`, only the primary visual mosaic block (the specific `<center>` block containing the highest density of YouTube links) is exempt from automated health checks and MUST NOT be included in `data/inventory.yaml`. This is a fixed visual asset. However, all other YouTube resources in these files—including links appearing before the mosaic and those in the collapsible "Top Videos" section—MUST be checked by the link cleaner and properly tracked in the inventory.
+23. **YouTube Mosaic Management & Dual Layout Mandate**: The YouTube channels visual mosaic in `docs/index.md` (V1) and `v2-docs/index.md` (V2) must be generated dynamically from the centralized metadata database `data/inventory.yaml` (using the `youtube_mosaic` metadata block). The layouts for V1 and V2 must remain strictly distinct to satisfy the dual-edition mandate:
+    - **V1 Exhaustive Layout**: Must be rendered as a single flat, historically ordered sequence of channel logos (11 per row) using simple inline width styling (`{: style="width:7%"}`). Newly discovered channels must be appended at the end of the flat list (ordered using the `youtube_mosaic.order_v1` field).
+    - **V2 Elite Layout**: Must be rendered as an advanced categorized dashboard grouped into custom border-outlined card containers with neon colors corresponding to technical dimensions, optimized dimensions (`width: 48px; height: 48px`), and class hooks (`.channel-logo`) (ordered using the `youtube_mosaic.order_v2` field).
+    - **Automation & Persistence**: The automated Publisher and Optimizer bot workflows must execute `src/reorganize_mosaic.py` to regenerate both visual blocks from the database during every pipeline run, ensuring the layout difference persists over the entire lifecycle.
 
 24. **Canonical URL Normalization & Semantic Deduplication**: To prevent duplication and fragmented metadata, all agents MUST normalize URLs before any inventory operation.
     - **Tracking Stripping**: Systematically remove UTM parameters, social media trackers (X.com, LinkedIn), and URL fragments (except technical ones).

README.md

@@ -138,9 +138,9 @@ Additionally, as of May 2026, Nubenetes has reached the **Platinum Operational T
 <!-- HEART_STATS_START -->
 | Metric | Value |
 | :--- | :--- |
-| **Total Technical Resources (Links)** | **17996+** |
+| **Total Technical Resources (Links)** | **18004+** |
 | **Specialized MD Pages** | **161** |
-| **Total Commits** | **5611+** |
+| **Total Commits** | **5627+** |
 | **Primary AI Engine** | **Google Gemini (Agentic)** |
 <!-- HEART_STATS_END -->
 
@@ -178,7 +178,7 @@ The growth of Nubenetes reflects the acceleration of the Cloud Native ecosystem.
 | 6 | 2023 | 30 | 123 | Maintenance & Refinement |
 | 7 | 2024 | 53 | 218 | Curation Strategy Pivot |
 | 8 | 2025 | 5 | 20 | Stability & Research Phase |
-| 9 | 2026 | 2052 | 8,474 | **Agentic AI Surge** (May 2026 Inception) |
+| 9 | 2026 | 2068 | 8,540 | **Agentic AI Surge** (May 2026 Inception) |
 <!-- ANNUAL_GROWTH_END -->
 
 <!-- ANNUAL_CHART_START -->
@@ -194,8 +194,8 @@ xychart-beta
     title "Nubenetes Annual Growth Metrics (2018–2026)"
     x-axis ["2018", "2019", "2020", "2021", "2022", "2023", "2024", "2025", "2026"]
     y-axis "Volume (Commits / Estimated New Refs)" 0 --> 9000
-    bar [1445, 586, 8449, 2193, 1660, 123, 218, 20, 8474]
-    bar [350, 142, 2046, 531, 402, 30, 53, 5, 2052]
+    bar [1445, 586, 8449, 2193, 1660, 123, 218, 20, 8540]
+    bar [350, 142, 2046, 531, 402, 30, 53, 5, 2068]
 ```
 <!-- ANNUAL_CHART_END -->
 
@@ -204,7 +204,7 @@ xychart-beta
 | Month | Commits | Est. New Refs | Status |
 | :--- | :---: | :---: | :--- |
 | 2026-04 | 25 | 103 | Active Curation |
-| 2026-05 | 2027 | 8,371 | **Agentic Inception (Gemini Era)** |
+| 2026-05 | 2043 | 8,437 | **Agentic Inception (Gemini Era)** |
 <!-- MONTHLY_SURGE_END -->
 
 ### 2.4. Content Distribution and Semantic Clustering
@@ -217,7 +217,7 @@ This chart shows the high-level distribution across the primary domains of Cloud
 <!-- PILLAR_CHART_START -->
 ```mermaid
 pie title Nubenetes Major Ecosystem Pillars
-    "Specialized Topics" : 3596
+    "Specialized Topics" : 3604
     "Kubernetes Ecosystem" : 3500
     "Developer Ecosystem" : 3000
     "Public/Private Cloud" : 2500
@@ -238,10 +238,10 @@ Reflecting Nubenetes' mission of global access while maintaining technical Engli
 <!-- SUB_ECO_CHART_START -->
 ```mermaid
 pie title Linguistic Diversity (Global Access)
-    "English" : 16196
-    "Spanish" : 1079
-    "French" : 179
-    "Others" : 539
+    "English" : 16203
+    "Spanish" : 1080
+    "French" : 180
+    "Others" : 540
 ```
 <!-- SUB_ECO_CHART_END -->
 
@@ -409,7 +409,31 @@ By separating these domains, Nubenetes ensures **100% Resilience**:
 
 ---
 
-### 5.6. Multi-Language Support Policy
+### 5.6. Dynamic YouTube Mosaic Engine
+Nubenetes manages the YouTube channel visual mosaic dynamically to support distinct V1 and V2 layout requirements from a single database source:
+
+- **Unified Schema (`data/inventory.yaml`)**: All channel metadata is stored under the `youtube_mosaic` key in the centralized inventory file:
+
+  ```yaml
+  https://www.youtube.com/@GoogleGemini:
+    title: Google Gemini
+    status: online
+    youtube_mosaic:
+      category: ai_advanced_tech        # Category grouping ID (V2)
+      image: images/google_gemini_logo.png
+      order_v1: 122                     # Flat sequence index (V1)
+      order_v2: 0                       # Category sorting index (V2)
+  ```
+
+- **Layout Generators (`src/reorganize_mosaic.py`)**:
+  * **V1 Flat Layout**: Sorts all channels globally by `order_v1` and formats them into a flat grid of 11 logos per row using simple inline width styling (`{: style="width:7%"}`). Newly added channels are appended at the end of the flat mosaic.
+  * **V2 Categorized Layout**: Groups channels by category, sorts them by `order_v2` within each group, and renders them inside custom cards with border-outline colors (e.g., purple for AI) matching the dimensions.
+
+- **Workflow Integration**: The mosaic generation is fully integrated into the **V2 Publisher** workflow (`04.1. V2 Publisher`). During any manual or automated run (cron jobs, PR merges), `src/reorganize_mosaic.py` runs automatically to rebuild both visual sections, preserving their layout differences across the entire codebase lifecycle.
+
+---
+
+### 5.7. Multi-Language Support Policy
 To embrace the diverse global Cloud Native community while maintaining international discoverability, Nubenetes implements a dual-layer linguistic strategy powered by a **Data-First Architecture**:
 
 - **Linguistic Data Persistence**: Language detection is treated as a core metadata attribute. The centralized database ([`data/inventory.yaml`](data/inventory.yaml)) stores resources using specific fields:

data/inventory.yaml

@@ -290014,3 +290014,20 @@ https://…:
   v2_locations:
   - kubernetes-troubleshooting.md
   year: N/A
+https://www.youtube.com/@arsys:
+  content_hash: ''
+  description: Canal oficial de YouTube de Arsys, proveedor de servicios de cloud
+    hosting e infraestructura tecnológica en España.
+  health_score: 100.0
+  last_checked: 0.0
+  status: online
+  title: Arsys
+  v1_locations:
+  - docs/index.md
+  v2_locations:
+  - index.md
+  youtube_mosaic:
+    category: cloud_providers
+    image: images/arsys_logo.svg
+    order_v1: 133
+    order_v2: 14

docs/images/arsys_logo.svg

@@ -0,0 +1,44 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg version="1.1" id="Ebene_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 width="315.134px" height="88.15px" viewBox="140.08 380.418 315.134 88.15" enable-background="new 140.08 380.418 315.134 88.15"
+	 xml:space="preserve">
+<title>logos</title>
+<style type="text/css">
+  path { fill: #2c3e50; }
+  @media (prefers-color-scheme: dark) {
+    path { fill: #ffffff; }
+  }
+</style>
+<path d="M379.988,380.625c-3.113-0.493-6.072,1.525-6.746,4.604l-14.486,47.623l-15.873-52.346h-16.51l23.811,64.568
+	c1.842,3.318,1.076,7.476-1.824,9.922c-2.383,1.864-4.684,1.864-9.645,1.825h-1.191v11.747h3.969c6.867,0,11.906-0.278,14.764-2.699
+	c3.424-2.924,5.967-6.744,7.342-11.032l26.43-74.172h-10.039V380.625z M403.798,386.617c-4.648,3.81-7.283,9.549-7.143,15.557
+	c-0.211,4.355,1.535,8.576,4.762,11.509l0,0c2.977,2.977,9.168,5.636,18.375,7.938l0,0c2.301,0.683,4.648,1.2,7.023,1.548
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+	c2.314,0.685,4.675,1.201,7.064,1.548c3.333,0.715,13.255,2.817,13.255,9.445c-0.016,2.966-1.686,5.675-4.326,7.024
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+	h9.445c-0.697-5.342-3.375-10.228-7.5-13.691c-6.324-4.183-13.82-6.227-21.391-5.834c-7.075-0.285-14.048,1.765-19.843,5.834
+	 M241.247,382.767c-4.999,1.119-9.748,3.15-14.009,5.993c-4.54,2.342-7.975,6.376-9.564,11.23
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+	 M158.741,439.478L158.741,439.478c-2.188-2.052-3.4-4.938-3.333-7.937c-0.244-2.814,0.774-5.591,2.778-7.58
+	c2.507-2,5.462-3.361,8.611-3.969l0,0l6.826-1.39c3.81-0.76,7.532-1.903,11.112-3.412l3.016-1.39v10.16
+	c0.952,7.342-1.429,10.992-5.437,13.572c-4.028,3.452-9.227,5.228-14.525,4.961C164.514,442.578,161.312,441.511,158.741,439.478"/>
+</svg>

docs/index.md

@@ -352,7 +352,7 @@ A curated list of awesome references collected since 2018. Microservices archite
 [![ContinuousDeliveryFoundation](images/ContinuousDeliveryFoundation.jpg){: style="width:7%"}](https://www.youtube.com/c/ContinuousDeliveryFoundation) [![tina huang](images/tinahuang.jpg){: style="width:7%"}](https://www.youtube.com/c/TinaHuang1) [![azure devops](images/azure_devops_youtube.jpg){: style="width:7%"}](https://www.youtube.com/c/AzureDevOps) [![azure cloud native](images/azure_cloud_native.jpg){: style="width:7%"}](https://www.youtube.com/channel/UC2Pk9GcHhlVV0R9CQIU6gLw) [![alibaba cloud](images/alibaba_cloud.jpg){: style="width:7%"}](https://www.youtube.com/c/AlibabaCloud) [![linode cloud](images/linode_cloud.jpg){: style="width:7%"}](https://www.youtube.com/c/linode) [![gaia-x](images/gaia_x.jpg){: style="width:7%"}](https://www.youtube.com/channel/UCB5WMc2FfrxKzfd7XIODoMw) [![gps](images/gps.jpg){: style="width:7%"}](https://www.youtube.com/c/MadeByGPS) [![keptn](images/keptn_logo.jpg){: style="width:7%"}](https://www.youtube.com/c/keptn) [![anais urlichs](images/anais_urlichs.jpg){: style="width:7%"}](https://www.youtube.com/c/AnaisUrlichs) [![the digital life](images/the_digital_life.jpg){: style="width:7%"}](https://www.youtube.com/c/TheDigitalLifeTech)<br/>
 [![Azure Terraformer](images/azure-terraformer.jpg){: style="width:7%"}](https://www.youtube.com/@azure-terraformer) [![Ned in the Cloud](images/nedinthecloud.jpg){: style="width:7%"}](https://www.youtube.com/@NedintheCloud) [![netbox](images/netboxlabs_logo.jpg){: style="width:7%"}](https://www.youtube.com/@NetBoxLabs) [![Tech with Helen](images/techwithhelen.jpg){: style="width:7%"}](https://www.youtube.com/@techwithhelen) [![bytebytego](images/bytebytego.jpg){: style="width:7%"}](https://www.youtube.com/@ByteByteGo) [![dotcsv](images/dotcsv.jpg){: style="width:7%"}](https://www.youtube.com/@DotCSV) [![midulive](images/midulive.jpg){: style="width:7%"}](https://www.youtube.com/@midulive) [![returngis](images/returngis_logo.jpg){: style="width:7%"}](https://www.youtube.com/@returngis) [![kubefm](images/kubefm_logo.jpg){: style="width:7%"}](https://www.youtube.com/@kubefm) [![Olena Kutsenko](images/olena_kutsenko.jpg){: style="width:7%"}](https://www.youtube.com/@OlenaKutsenko) [![mouredev](images/mouredev.jpg){: style="width:7%"}](https://www.youtube.com/@mouredev)<br/>
 [![CloudNativeMadrid](images/cloudnativemadrid_logo.jpg){: style="width:7%"}](https://www.youtube.com/@CloudNativeMadrid) [![kyndryl](images/kyndryl_logo.jpg){: style="width:7%"}](https://www.youtube.com/@kyndryl) [![itopstalk](images/itopstalk_logo.png){: style="width:7%"}](https://www.youtube.com/@ITOpsTalk) [![gcp videos new](images/gcp_logo_v2.png){: style="width:7%"}](https://www.youtube.com/@googlecloudtech) [![Google Gemini](images/google_gemini_logo.png){: style="width:7%"}](https://www.youtube.com/@GoogleGemini) [![Google DeepMind](images/google_deepmind_logo.png){: style="width:7%"}](https://www.youtube.com/@googledeepmind) [![Anthropic](images/anthropic_logo.png){: style="width:7%"}](https://www.youtube.com/@anthropic-ai) [![Microsoft Copilot](images/microsoft_copilot_logo.png){: style="width:7%"}](https://www.youtube.com/@Microsoft.Copilot) [![OpenAI](images/openai_logo.png){: style="width:7%"}](https://www.youtube.com/OpenAI) [![Meta AI](images/meta_ai_logo.png){: style="width:7%"}](https://www.youtube.com/@aiatmeta) [![Microsoft Reactor](images/microsoft_reactor_logo.png){: style="width:7%"}](https://www.youtube.com/@MicrosoftReactor)<br/>
-[![Playwright](images/playwright_logo.png){: style="width:7%"}](https://www.youtube.com/@Playwrightdev)
+[![Playwright](images/playwright_logo.png){: style="width:7%"}](https://www.youtube.com/@Playwrightdev) [![Arsys](images/arsys_logo.svg){: style="width:7%"}](https://www.youtube.com/@arsys)
 
 </center>
 

docs/static/extra.css

@@ -49,4 +49,10 @@ reset max-width with the following CSS: */
   filter: brightness(1.2);
 }
 
+/* Invert Arsys logo in dark mode */
+[data-md-color-scheme="slate"] img[src*="arsys_logo.svg"] {
+  filter: invert(1) brightness(2);
+}
+
+
 

src/memory/health_learning.json

@@ -1,3 +1,12 @@
 {
-  "blacklisted_domains": []
+  "blacklisted_domains": [],
+  "youtube_mosaic_layout_mandate": {
+    "v1_exhaustive": "Flat list of logos (11 per row) using order_v1 and inline width:7%",
+    "v2_elite": "Categorized neon-bordered card dashboard using order_v2 and width:48px",
+    "central_database": "data/inventory.yaml under the youtube_mosaic key",
+    "automation_scripts": [
+      "src/reorganize_mosaic.py",
+      "src/v2_optimizer.py"
+    ]
+  }
 }

src/v2_video_portal.py

@@ -149,7 +149,7 @@ def generate_v2_videos():
         "",
         "Welcome to the **Nubenetes Elite Video Hub**. Discover highly-curated architectural video resources organized into logical learning paths:",
         "",
-        "### Learning Dimensions",
+        "## Learning Dimensions",
         "- 🤖 [**AI Agents and MCP**](./ai-agents.md) — Dive into agentic architectures, tool integration, and Model Context Protocol setups.",
         "- 🛠️ [**DevOps, IaC, and SRE**](./devops-iac.md) — Platform engineering, infrastructure automation with Terraform, SRE, and compliance workflows utilizing AI assistants.",
         "- ☁️ [**Cloud Native Core**](./cloud-native.md) — Architectural strategies, Kubernetes operations, networking, and MLOps platforms.",

v2-docs/demos.md

@@ -108,7 +108,7 @@
   - [Automated API testing for the KIE Server 🌟](https://developers.redhat.com/blog/2020/05/01/automated-api-testing-for-the-kie-server)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
   - [SysAdmin Casts](https://sysadmincasts.com)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
   - [DEVOPS Library](https://devopslibrary.com)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
-  - [youtube: Cloud Quick POCs](https://www.youtube.com/channel/UCv9MUffHWyo2GgLIDLVu0KQ)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
+  - [cloud quick POCs](https://www.youtube.com/channel/UCv9MUffHWyo2GgLIDLVu0KQ)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
   - [DevStack](https://devstack.in)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
   - [kubernetes-advocate.medium.com 🌟](https://kubernetes-advocate.medium.com)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
   - [github.com/wardviaene (kubernetes, terraform, ansible, docker, etc) 🌟](https://github.com/wardviaene)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>

v2-docs/videos/ai-agents.md

@@ -7,8 +7,8 @@ Welcome to the **AI Agents and MCP** section of the V2 Video Hub. Explore curate
 1. [Red Hat OpenShift](#red-hat-openshift)
 2. [Generative AI and Large Language Models](#generative-ai-and-large-language-models)
 3. [Red Hat OpenShift AI](#red-hat-openshift-ai)
-4. [Neural Networks](#neural-networks)
-5. [Claude Code](#claude-code)
+4. [Claude Code](#claude-code)
+5. [Neural Networks](#neural-networks)
 6. [LLM Architecture and Post-Training](#llm-architecture-and-post-training)
 7. [Agentic DevOps](#agentic-devops)
 
@@ -48,18 +48,6 @@ Welcome to the **AI Agents and MCP** section of the V2 Video Hub. Explore curate
 
     </center>
 
-## Neural Networks
-
-??? note "🎬 ¿Qué es una Red Neuronal? Parte 1 : La Neurona | DotCSV [SPANISH CONTENT]"
-    !!! info "Architectural Summary"
-        This video deconstructs the foundational mathematical and algorithmic mechanics of a single artificial neuron, illustrating its direct relationship with linear regression, weights, biases, and activation functions. In a 2026 cloud-native landscape, mastering these core neural principles is critical for platform architects optimizing distributed micro-models and real-time AI inference engines deployed on Kubernetes-driven edge and cloud infrastructure. This granular understanding enables more efficient hardware acceleration profiling (GPUs/vGPUs/TPUs) and smarter resource allocation for decentralized machine learning pipelines.
-
-    <center markdown="1">
-
-    <iframe width="720" height="405" src="https://www.youtube.com/embed/MRIv2IwFTPg?si=F07g869i6yIfqRdg" title="¿Qué es una Red Neuronal? Parte 1 : La Neurona | DotCSV" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen loading="lazy" style="border: 1px solid var(--md-typeset-table-color); border-radius: 8px;"></iframe>
-
-    </center>
-
 ## Claude Code
 
 ??? note "🎬 Mastering Claude Code in 30 minutes"
@@ -72,6 +60,18 @@ Welcome to the **AI Agents and MCP** section of the V2 Video Hub. Explore curate
 
     </center>
 
+## Neural Networks
+
+??? note "🎬 ¿Qué es una Red Neuronal? Parte 1 : La Neurona | DotCSV [SPANISH CONTENT]"
+    !!! info "Architectural Summary"
+        This video deconstructs the foundational mathematical and algorithmic mechanics of a single artificial neuron, illustrating its direct relationship with linear regression, weights, biases, and activation functions. In a 2026 cloud-native landscape, mastering these core neural principles is critical for platform architects optimizing distributed micro-models and real-time AI inference engines deployed on Kubernetes-driven edge and cloud infrastructure. This granular understanding enables more efficient hardware acceleration profiling (GPUs/vGPUs/TPUs) and smarter resource allocation for decentralized machine learning pipelines.
+
+    <center markdown="1">
+
+    <iframe width="720" height="405" src="https://www.youtube.com/embed/MRIv2IwFTPg?si=F07g869i6yIfqRdg" title="¿Qué es una Red Neuronal? Parte 1 : La Neurona | DotCSV" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen loading="lazy" style="border: 1px solid var(--md-typeset-table-color); border-radius: 8px;"></iframe>
+
+    </center>
+
 ## LLM Architecture and Post-Training
 
 ??? note "🎬 Stanford CS229: Building Large Language Models (LLMs)"