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chore(release): v2.9.55 - fix Nutanix logo dark mode in V1 mosaic

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Inaki Fernandez
2026-06-25 12:17:29 +02:00
parent 730b3c1043 394ec2a741
commit 21b8ca6f6d
7 changed files with 296 additions and 287 deletions
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README.md
+5 -5
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@@ -142,7 +142,7 @@ Additionally, as of May 2026, Nubenetes has reached the **Platinum Operational T
| :--- | :--- |
| **Total Technical Resources (Links)** | **18657+** |
| **Specialized MD Pages** | **162** |
| **Total Commits** | **6499+** |
| **Total Commits** | **6500+** |
| **Primary AI Engine** | **Google Gemini (Agentic)** |
<!-- HEART_STATS_END -->
@@ -180,7 +180,7 @@ 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 | 2940 | 12,142 | **Agentic AI Surge** (May 2026 Inception) |
| 9 | 2026 | 2941 | 12,146 | **Agentic AI Surge** (May 2026 Inception) |
<!-- ANNUAL_GROWTH_END -->
<!-- ANNUAL_CHART_START -->
@@ -196,8 +196,8 @@ 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 --> 13000
bar [1445, 586, 8449, 2193, 1660, 123, 218, 20, 12142]
bar [350, 142, 2046, 531, 402, 30, 53, 5, 2940]
bar [1445, 586, 8449, 2193, 1660, 123, 218, 20, 12146]
bar [350, 142, 2046, 531, 402, 30, 53, 5, 2941]
```
<!-- ANNUAL_CHART_END -->
@@ -207,7 +207,7 @@ xychart-beta
| :--- | :---: | :---: | :--- |
| 2026-04 | 25 | 103 | Active Curation |
| 2026-05 | 2101 | 8,677 | **Agentic Inception (Gemini Era)** |
| 2026-06 | 814 | 3,361 | Active Curation |
| 2026-06 | 815 | 3,365 | Active Curation |
<!-- MONTHLY_SURGE_END -->
### 2.4. Content Distribution and Semantic Clustering
data/inventory.sql
+1 -1
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@@ -12452,7 +12452,7 @@ INSERT INTO "resources" VALUES('https://skamille.medium.com/an-incomplete-list-o
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INSERT INTO "resources" VALUES('https://skillbuilder.aws/course/external/view/elearning/48/aws-security-fundamentals-second-edition','explore.skillbuilder.aws: AWS Security Fundamentals (free)','','2021',4,'A foundational security course covering AWS shared responsibility models, identity boundaries, network segregation methods, and programmatic cryptographic mechanisms.','English','Interactive Course','Beginner',0,'online','manual',NULL,NULL,NULL,0,'2021-06-01T00:00:00+02:00',NULL,NULL,NULL,'["Cloud Infrastructure", "Training", "AWS Security"]','["[ENTERPRISE-STABLE]", "[GUIDE]"]','[]','["aws-training.md"]','{}','{}');
INSERT INTO "resources" VALUES('https://skillbuilder.aws/course/external/view/elearning/7854/aws-technical-essential-spanish-from-latin-america','explore.skillbuilder.aws: AWS Skill Builder - Introducción a AWS Data Pipeline (Español Latinoamérica) | AWS Technical Essentials (Spanish from Latin America)'' - Free','','2021',3,'Official localized AWS Skill Builder path delivering fundamental architectural and Data Pipeline instructions in Spanish. [SPANISH CONTENT]','Spanish','Interactive Course','Beginner',0,'online','manual',NULL,NULL,NULL,0,'2021-06-01T00:00:00+02:00',NULL,NULL,NULL,'["Cloud Infrastructure", "Training", "AWS Official"]','["[COMMUNITY-TOOL]", "[GUIDE]"]','[]','["aws-training.md"]','{}','{}');
INSERT INTO "resources" VALUES('https://skilledfield.com.au/monitoring-kubernetes-and-docker-container-logs','skilledfield.com.au: Monitoring Kubernetes and Docker Container Logs','','N/A',0,NULL,NULL,NULL,NULL,0,'duplicate','manual','52198432ca323827ac8c97a44f623ffd9d20da96c5bfb8ee72e924c305410143',100.0,1779034577,0,'2026-05-17T18:16:17.574546+02:00',NULL,NULL,NULL,'[]','[]','["docs/monitoring.md"]','[]','{}','{"duplicate_of": "https://skillfield.com.au/blog/monitoring-kubernetes-and-docker-container-logs"}');
data/inventory.yaml
+2 -1
View File
@@ -398384,7 +398384,7 @@ https://skillbuilder.aws:
resource_type: Platform
complexity: Intermediate
is_microservice: false
status: online
status: duplicate
addition_method: manual
content_hash: null
health_score: null
@@ -398405,6 +398405,7 @@ https://skillbuilder.aws:
- aws-training.md
- aws.md
youtube_mosaic: {}
duplicate_of: https://skillbuilder.aws/
https://skillbuilder.aws/course/external/view/elearning/48/aws-security-fundamentals-second-edition:
title: 'explore.skillbuilder.aws: AWS Security Fundamentals (free)'
description: ''
data/news_digest.json
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@@ -651,7 +651,7 @@
"date": "2026-06-01",
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"why": "It is the official authority hosting curricula and exams for the industry-standard CKA, CKAD, and CKS cloud-native certifications.",
"why": "As the official training arm of the Linux Foundation, it establishes and maintains the curricula for industry-standard CKA, CKAD, and CKS certifications.",
"category": "Certification & Training"
},
{
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"date": "2026-06-01",
"stars": 5,
"impact": "critical",
"why": "Crucial official cheat sheet for mastering command-line operations essential for passing CKA, CKAD, and CKS exams.",
"category": "Certification & Training"
},
{
"url": "https://cheatsheetseries.owasp.org/index.html",
"title": "cheatsheetseries.owasp.org: OWASP Cheat Sheet Series 🌟🌟",
"date": "2026-06-01",
"stars": 5,
"impact": "critical",
"why": "The definitive security reference mapping modern web application vulnerabilities, which is critical knowledge for the CKS certification.",
"why": "This is the canonical kubectl command reference and is the primary external document allowed for consultation during official Kubernetes exams.",
"category": "Certification & Training"
},
{
@@ -678,7 +669,7 @@
"date": "2026-06-01",
"stars": 4,
"impact": "high",
"why": "Provides high-quality, structured, and free modular training tracks focusing on complex Kubernetes cluster operations and architectural concepts.",
"why": "Provides highly polished, free, and modular training tracks covering advanced Kubernetes administration and security patterns.",
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{
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"date": "2026-06-01",
"stars": 4,
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"why": "Offers direct cloud-based sandbox environments and practice simulations for key CNCF certifications like CKA, CKAD, and CKS.",
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{
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"title": "==techiescamp/devops-projects==:Real-World DevOps Projects For Learning",
"date": "2026-06-18",
"stars": 5,
"impact": "high",
"why": "Provides real-world, end-to-end infrastructure blueprints and multi-tier pipelines that offer practical, hands-on learning for DevOps and cloud-native engineers.",
"why": "Offers comprehensive practice exams and cloud-based sandbox environments specifically tailored to prepare candidates for CNCF certifications.",
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},
{
@@ -705,7 +687,25 @@
"date": "2026-06-01",
"stars": 4,
"impact": "high",
"why": "Hosts the official Linux Foundation cloud-native course catalog, bridging system administration theory with hands-on command-line practice.",
"why": "Acts as the key academic partner hosting the Linux Foundation's official entry-level cloud-native and container courses.",
"category": "Certification & Training"
},
{
"url": "https://github.com/techiescamp/devops-projects",
"title": "==techiescamp/devops-projects==:Real-World DevOps Projects For Learning",
"date": "2026-06-18",
"stars": 5,
"impact": "high",
"why": "Provides structured, real-world infrastructure and CI/CD blueprints that allow engineers to practice hands-on platform engineering skills.",
"category": "Certification & Training"
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"title": "techstudyslack.com",
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"stars": 4,
"impact": "high",
"why": "A massive, active peer-led community offering study groups, real-time debugging, and mentoring for cloud and Kubernetes certification prep.",
"category": "Certification & Training"
},
{
@@ -714,16 +714,16 @@
"date": "2026-06-08",
"stars": 4,
"impact": "high",
"why": "An industry-standard mock microservice used widely in workshops to teach Kubernetes deployment patterns, telemetry, and progressive delivery.",
"why": "The definitive microservice tool used across the industry to learn and demonstrate Kubernetes features, instrumentation, and progressive delivery.",
"category": "Certification & Training"
},
{
"url": "https://techstudyslack.com",
"title": "techstudyslack.com",
"date": "2026-06-01",
"stars": 4,
"impact": "medium",
"why": "A highly active peer-to-peer community hub specifically dedicated to real-time debugging support and collaborative preparation for Kubernetes certifications.",
"url": "https://skillbuilder.aws/",
"title": "skillbuilder.aws: AWS Skill Builder",
"date": "2026-06-25",
"stars": 5,
"impact": "high",
"why": "The official learning portal for AWS, delivering structured paths and exam readiness assessments crucial for cloud architects and developers.",
"category": "Certification & Training"
},
{
@@ -732,7 +732,7 @@
"date": "2026-06-18",
"stars": 3,
"impact": "medium",
"why": "An opinionated command cheat sheet optimized for fast-paced troubleshooting and practical practice during hands-on Kubernetes exams.",
"why": "Curates opinionated, real-world troubleshooting commands that serve as an excellent study guide for the hands-on portions of container exams.",
"category": "Certification & Training"
}
],
@@ -1019,7 +1019,7 @@
"date": "2026-06-01",
"stars": 5,
"impact": "critical",
"why": "Ray is the industry-standard distributed compute framework essential for scaling heavy AI training and LLM workloads.",
"why": "A critical distributed computing framework that has become the standard for scaling heavy AI training and inference workloads natively on cloud infrastructure.",
"category": "MLOps & Data Science"
},
{
@@ -1028,7 +1028,7 @@
"date": "2026-05-17",
"stars": 0,
"impact": "critical",
"why": "OpenAI's scaling insights provide the ultimate blueprint for running massive-scale machine learning workloads on Kubernetes.",
"why": "An industry-defining engineering post outlining how to scale Kubernetes to massive heights to support large-scale AI training workloads.",
"category": "MLOps & Data Science"
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{
@@ -1037,7 +1037,7 @@
"date": "2026-06-13",
"stars": 5,
"impact": "high",
"why": "Metaflow bridges the gap between local data science development and scalable cloud-native production infrastructure.",
"why": "An enterprise-ready framework from Netflix that seamlessly integrates local data science development with scalable cloud-native compute.",
"category": "MLOps & Data Science"
},
{
@@ -1046,25 +1046,7 @@
"date": "2026-05-19",
"stars": 5,
"impact": "high",
"why": "Meta's official recipes establish standardized best practices for parameter-efficient fine-tuning and LLM optimization.",
"category": "MLOps & Data Science"
},
{
"url": "https://github.com/argilla-io/argilla",
"title": "rubrix",
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"stars": 5,
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},
{
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{
@@ -1073,7 +1055,7 @@
"date": "2026-06-18",
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"why": "An invaluable reference mapping out the tools, configurations, and architectures required to run machine learning workloads on Kubernetes.",
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{
@@ -1082,7 +1064,7 @@
"date": "2026-05-17",
"stars": 0,
"impact": "high",
"why": "It outlines a highly sophisticated, real-world architectural pattern for managing multi-tenant ML applications using Kubernetes sharding.",
"why": "Provides a highly novel engineering blueprint for automating multi-tenant ML application sharding natively inside Kubernetes clusters.",
"category": "MLOps & Data Science"
},
{
@@ -1091,7 +1073,25 @@
"date": "2026-05-17",
"stars": 0,
"impact": "high",
"why": "This guide provides a practical, cloud-native blueprint for running distributed LLM fine-tuning operations on Kubernetes.",
"why": "Details a highly practical and cloud-native approach to running distributed fine-tuning of large language models on Kubernetes.",
"category": "MLOps & Data Science"
},
{
"url": "https://medium.com/bakdata/scalable-machine-learning-with-kafka-streams-and-kserve-85308858d867",
"title": "medium.com/bakdata: Scalable Machine Learning with Kafka Streams and KServe",
"date": "2026-05-17",
"stars": 0,
"impact": "high",
"why": "Demonstrates a robust integration of Kafka event streaming with KServe for scalable, real-time ML model inference in Kubernetes environments.",
"category": "MLOps & Data Science"
},
{
"url": "https://engineering.fb.com/2026/05/26/ml-applications/silvertorch-index-as-model-new-retrieval-paradigm-recommendation-systems",
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"date": "2026-06-02",
"stars": 4,
"impact": "high",
"why": "Presents a paradigm-shifting approach from Meta that consolidates recommendation pipelines into unified, GPU-optimized PyTorch models.",
"category": "MLOps & Data Science"
},
{
@@ -1100,7 +1100,7 @@
"date": "2026-05-21",
"stars": 3,
"impact": "medium",
"why": "Envd solves the notorious ML pain point of environment reproducibility by generating isolated, CUDA-ready dev containers from Python declarations.",
"why": "An innovative tool that compiles Python definitions into containerized environments, ensuring reproducible GPU-enabled development workflows.",
"category": "MLOps & Data Science"
}
],
@@ -3065,7 +3065,7 @@
"date": "2026-06-01",
"stars": 5,
"impact": "critical",
"why": "As the official home for the CKA, CKAD, and CKS curricula, this is the single most critical training source for cloud-native professionals.",
"why": "It is the official training and curriculum provider for the industry-standard CKA, CKAD, and CKS certifications.",
"category": "Certification & Training"
},
{
@@ -3073,8 +3073,17 @@
"title": "kubernetes.io 🌟",
"date": "2026-06-01",
"stars": 5,
"impact": "high",
"why": "The canonical kubectl quick reference is an indispensable daily tool and exam aid for candidates preparing for hands-on CNCF certifications.",
"impact": "critical",
"why": "This canonical kubectl guide is the most critical quick-reference tool for practicing hands-on Kubernetes tasks during exam preparation.",
"category": "Certification & Training"
},
{
"url": "https://cheatsheetseries.owasp.org/index.html",
"title": "cheatsheetseries.owasp.org: OWASP Cheat Sheet Series 🌟🌟",
"date": "2026-06-01",
"stars": 5,
"impact": "critical",
"why": "It is the definitive guide for learning web application security mitigations, making it vital for cloud-native security and CKS preparation.",
"category": "Certification & Training"
},
{
@@ -3083,7 +3092,7 @@
"date": "2026-06-01",
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"impact": "high",
"why": "This VMware Tanzu-sponsored platform offers high-quality, free modular tracks specifically designed to teach advanced Kubernetes administration concepts.",
"why": "It offers structured, high-quality, and free Kubernetes educational pathways crucial for training production-ready platform engineers.",
"category": "Certification & Training"
},
{
@@ -3092,43 +3101,7 @@
"date": "2026-06-01",
"stars": 4,
"impact": "high",
"why": "Provides highly realistic exam simulators and sandbox environments specifically designed for preparing candidates to pass the CKA, CKAD, and CKS.",
"category": "Certification & Training"
},
{
"url": "https://www.edx.org",
"title": "edx.org",
"date": "2026-06-01",
"stars": 4,
"impact": "high",
"why": "Hosts the official introductory curricula from the Linux Foundation, acting as a primary starting point for university-grade cloud-native certificates.",
"category": "Certification & Training"
},
{
"url": "https://github.com/AdminTurnedDevOps/DevOps-The-Hard-Way-AWS",
"title": "==AdminTurnedDevOps/DevOps-The-Hard-Way-AWS==",
"date": "2025-04-27",
"stars": 5,
"impact": "high",
"why": "Offers a rigorous, step-by-step curriculum for learning real-world cloud operations, infrastructure as code, and security scanning on AWS.",
"category": "Certification & Training"
},
{
"url": "https://github.com/techiescamp/devops-projects",
"title": "==techiescamp/devops-projects==:Real-World DevOps Projects For Learning",
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"stars": 5,
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"why": "Provides comprehensive, real-world infrastructure blueprints and CI/CD templates essential for hands-on DevOps learning and portfolio building.",
"category": "Certification & Training"
},
{
"url": "https://cheatsheetseries.owasp.org/index.html",
"title": "cheatsheetseries.owasp.org: OWASP Cheat Sheet Series 🌟🌟",
"date": "2026-06-01",
"stars": 5,
"impact": "high",
"why": "Serves as the ultimate application security reference, heavily utilized in training for the Certified Kubernetes Security Specialist (CKS) exam.",
"why": "It delivers dedicated exam simulation sandboxes that directly help engineers pass Kubernetes certifications like CKA and CKS.",
"category": "Certification & Training"
},
{
@@ -3137,7 +3110,25 @@
"date": "2026-06-08",
"stars": 4,
"impact": "high",
"why": "The de facto reference microservice used by engineers to practice and test Kubernetes deployment patterns, service meshes, and observability tools.",
"why": "This application serves as the gold standard reference microservice for testing and learning Kubernetes orchestrations, health checks, and metrics.",
"category": "Certification & Training"
},
{
"url": "https://github.com/techiescamp/devops-projects",
"title": "==techiescamp/devops-projects==:Real-World DevOps Projects For Learning",
"date": "2026-06-18",
"stars": 5,
"impact": "high",
"why": "It provides invaluable real-world project templates for hands-on learning of Terraform, Ansible, and multi-tier CI/CD pipelines.",
"category": "Certification & Training"
},
{
"url": "https://github.com/AdminTurnedDevOps/DevOps-The-Hard-Way-AWS",
"title": "==AdminTurnedDevOps/DevOps-The-Hard-Way-AWS==",
"date": "2025-04-27",
"stars": 5,
"impact": "high",
"why": "This repository offers a comprehensive, step-by-step curriculum for mastering real-world AWS cloud operations and DevOps practices.",
"category": "Certification & Training"
},
{
@@ -3145,8 +3136,17 @@
"title": "knative-tutorial",
"date": "2026-01-15",
"stars": 5,
"impact": "medium",
"why": "Delivers a structured, practical tutorial for mastering Knative serving, eventing, and scale-to-zero serverless paradigms in Kubernetes.",
"impact": "high",
"why": "It is an essential hands-on learning asset for mastering serverless architectures, traffic splitting, and scale-to-zero using Knative on Kubernetes.",
"category": "Certification & Training"
},
{
"url": "https://github.com/spring-petclinic/spring-petclinic-microservices",
"title": "Spring PetClinic Microservices",
"date": "2026-05-17",
"stars": 5,
"impact": "high",
"why": "This acts as the premier reference architecture for training teams on how to deploy and configure Java microservices in a cloud-native ecosystem.",
"category": "Certification & Training"
}
],
@@ -3341,7 +3341,7 @@
"date": "2026-06-01",
"stars": 5,
"impact": "critical",
"why": "As the dominant distributed execution framework for AI, Ray is foundational for scaling compute-heavy workloads across cloud-native environments.",
"why": "Ray is the industry-standard distributed computing framework critical for scaling heavy AI training and Python workloads across cloud native environments.",
"category": "MLOps & Data Science"
},
{
@@ -3350,7 +3350,7 @@
"date": "2026-05-17",
"stars": 0,
"impact": "critical",
"why": "This landmark case study provides invaluable infrastructure blueprints for scaling Kubernetes to handle massive, state-of-the-art AI/ML training workloads.",
"why": "This landmark publication details how OpenAI pushed Kubernetes to its limits, establishing the blueprint for scaling massive AI training infrastructures.",
"category": "MLOps & Data Science"
},
{
@@ -3358,8 +3358,8 @@
"title": "==github.com/Netflix/metaflow== 🌟",
"date": "2026-06-13",
"stars": 5,
"impact": "critical",
"why": "Netflix's production-proven framework seamlessly bridges local data science development with enterprise-scale cloud infrastructure and orchestration.",
"impact": "high",
"why": "Metaflow bridges the developer experience gap by seamlessly connecting local Python code to production cloud scaling and execution.",
"category": "MLOps & Data Science"
},
{
@@ -3368,16 +3368,16 @@
"date": "2026-05-19",
"stars": 5,
"impact": "high",
"why": "Provides industry-standard templates for parameter-efficient fine-tuning and optimization, defining modern LLMOps deployment patterns.",
"why": "Meta's standard playbook offers critical fine-tuning and optimization templates for deploying large language models efficiently at scale.",
"category": "MLOps & Data Science"
},
{
"url": "https://medium.com/workday-engineering/implementing-a-fully-automated-sharding-strategy-on-kubernetes-for-multi-tenanted-machine-learning-4371c48122ae",
"title": "medium.com/workday-engineering: Implementing a Fully Automated Sharding' Strategy on Kubernetes for Multi-tenanted Machine Learning Applications",
"date": "2026-05-17",
"stars": 0,
"url": "https://engineering.fb.com/2026/05/26/ml-applications/silvertorch-index-as-model-new-retrieval-paradigm-recommendation-systems",
"title": "SilverTorch: Index as Model — A New Retrieval Paradigm for Recommendation Systems",
"date": "2026-06-02",
"stars": 4,
"impact": "high",
"why": "Solves critical multi-tenancy and resource isolation challenges for ML applications at enterprise scale using native Kubernetes sharding.",
"why": "Redefines recommendation systems by unifying vector retrieval, filtering, and scoring into a single PyTorch model, vastly improving GPU efficiency.",
"category": "MLOps & Data Science"
},
{
@@ -3386,16 +3386,7 @@
"date": "2026-06-18",
"stars": 4,
"impact": "high",
"why": "Serves as an essential technical reference mapping out configurations and architectural patterns for running diverse ML workloads on Kubernetes.",
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},
{
"url": "https://medium.com/@bchenjh/full-fine-tuning-of-llama2-on-kubernetes-a983e1eb2259",
"title": "medium.com/@bchenjh: Distributed full fine-tuning of Llama2 on Kubernetes",
"date": "2026-05-17",
"stars": 0,
"impact": "high",
"why": "Demonstrates a practical, cloud-native pattern for executing complex, distributed LLM fine-tuning directly on Kubernetes clusters.",
"why": "An invaluable reference architecture that maps out the complex ecosystem of machine learning tools running directly on Kubernetes.",
"category": "MLOps & Data Science"
},
{
@@ -3404,7 +3395,16 @@
"date": "2026-06-08",
"stars": 5,
"impact": "high",
"why": "A critical open-source platform that enables human-in-the-loop data curation, which is essential for continuous alignment of modern generative AI models.",
"why": "Argilla addresses the crucial LLM alignment phase by offering an open-source platform for continuous human-in-the-loop data curation.",
"category": "MLOps & Data Science"
},
{
"url": "https://medium.com/workday-engineering/implementing-a-fully-automated-sharding-strategy-on-kubernetes-for-multi-tenanted-machine-learning-4371c48122ae",
"title": "medium.com/workday-engineering: Implementing a Fully Automated Sharding' Strategy on Kubernetes for Multi-tenanted Machine Learning Applications",
"date": "2026-05-17",
"stars": 0,
"impact": "medium",
"why": "Provides a practical production case study on automating database and application sharding on Kubernetes for multi-tenant ML workloads.",
"category": "MLOps & Data Science"
},
{
@@ -3413,16 +3413,16 @@
"date": "2026-05-21",
"stars": 3,
"impact": "medium",
"why": "Simplifies the ML-to-cloud transition by automatically packaging Python declarations into highly reproducible, CUDA-enabled containers.",
"why": "Simplifies AI/ML engineering by translating declarative Python environments into reproducible, containerized CUDA configurations.",
"category": "MLOps & Data Science"
},
{
"url": "https://medium.com/bakdata/scalable-machine-learning-with-kafka-streams-and-kserve-85308858d867",
"title": "medium.com/bakdata: Scalable Machine Learning with Kafka Streams and KServe",
"date": "2026-05-17",
"stars": 0,
"url": "https://github.com/XuehaiPan/nvitop",
"title": "==github.com/XuehaiPan/nvitop== 🌟",
"date": "2026-05-25",
"stars": 4,
"impact": "medium",
"why": "Showcases a robust, event-driven architecture for scaling real-time model inference using KServe and Kafka on Kubernetes.",
"why": "A highly practical terminal-based monitoring tool that replaces nvidia-smi with interactive, real-time GPU profiling for developers.",
"category": "MLOps & Data Science"
}
],
@@ -5387,7 +5387,7 @@
"date": "2026-06-01",
"stars": 5,
"impact": "critical",
"why": "The definitive training and certification source that directly defines the curricula for the CKA, CKAD, and CKS benchmarks.",
"why": "This is the official curriculum custodian for the highly respected CKA, CKAD, and CKS certifications, directly shaping how modern cloud-native engineers are trained.",
"category": "Certification & Training"
},
{
@@ -5396,34 +5396,7 @@
"date": "2026-06-01",
"stars": 5,
"impact": "critical",
"why": "The canonical kubectl reference and the primary permitted documentation resource during official Linux Foundation Kubernetes exams.",
"category": "Certification & Training"
},
{
"url": "https://kube.academy",
"title": "kube.academy",
"date": "2026-06-01",
"stars": 4,
"impact": "high",
"why": "A highly polished, VMware-sponsored training platform that guides engineers through complex, real-world Kubernetes operational tracks.",
"category": "Certification & Training"
},
{
"url": "https://www.whizlabs.com",
"title": "Whizlabs",
"date": "2026-06-01",
"stars": 4,
"impact": "high",
"why": "A premier professional certification preparation engine offering hands-on cloud sandboxes for CKA, CKAD, and CKS exams.",
"category": "Certification & Training"
},
{
"url": "https://github.com/AdminTurnedDevOps/DevOps-The-Hard-Way-AWS",
"title": "==AdminTurnedDevOps/DevOps-The-Hard-Way-AWS==",
"date": "2025-04-27",
"stars": 5,
"impact": "high",
"why": "A rigorous, hands-on learning curriculum focused on configuring real-world AWS and DevOps infrastructure from the ground up.",
"why": "It serves as the definitive reference guide allowed during CNCF certification exams, making it an essential tool for training administrators and developers.",
"category": "Certification & Training"
},
{
@@ -5432,7 +5405,16 @@
"date": "2026-06-08",
"stars": 4,
"impact": "high",
"why": "The industry-standard microservice application used globally to train teams on Kubernetes deployment, health checks, and observability.",
"why": "This premier mock microservice is the industry-standard sandbox application used to teach and test Kubernetes deployment patterns, GitOps, and instrumentation.",
"category": "Certification & Training"
},
{
"url": "https://kube.academy",
"title": "kube.academy",
"date": "2026-06-01",
"stars": 4,
"impact": "high",
"why": "This platform delivers high-quality, free Kubernetes training paths curated by VMware Tanzu, making advanced cluster topics highly accessible.",
"category": "Certification & Training"
},
{
@@ -5441,25 +5423,34 @@
"date": "2026-06-18",
"stars": 5,
"impact": "high",
"why": "A highly practical, end-to-end compilation of DevOps blueprints that helps engineers transition from theoretical knowledge to real-world pipelines.",
"why": "It provides comprehensive, real-world infrastructure blueprints and CI/CD pipelines essential for hands-on, practical DevOps training.",
"category": "Certification & Training"
},
{
"url": "https://www.edx.org",
"title": "edx.org",
"url": "https://github.com/AdminTurnedDevOps/DevOps-The-Hard-Way-AWS",
"title": "==AdminTurnedDevOps/DevOps-The-Hard-Way-AWS==",
"date": "2025-04-27",
"stars": 5,
"impact": "high",
"why": "This rigorous, hands-on curriculum provides step-by-step practical guides for building and securing enterprise-grade infrastructure on AWS.",
"category": "Certification & Training"
},
{
"url": "https://www.whizlabs.com",
"title": "Whizlabs",
"date": "2026-06-01",
"stars": 4,
"impact": "high",
"why": "Hosts the official Linux Foundation cloud-native course catalog, providing structured, university-grade pathways for open-source engineering.",
"why": "It offers highly rated CKA, CKAD, and CKS exam simulations combined with cloud sandboxes, directly assisting engineers in acquiring certification.",
"category": "Certification & Training"
},
{
"url": "https://developer.hashicorp.com/terraform/cli/commands",
"title": "terraform.io: Terraform Commands",
"url": "https://cheatsheetseries.owasp.org/index.html",
"title": "cheatsheetseries.owasp.org: OWASP Cheat Sheet Series 🌟🌟",
"date": "2026-06-01",
"stars": 5,
"impact": "medium",
"why": "The official HashiCorp command reference essential for mastering advanced state management, a core focus of Terraform certifications.",
"impact": "high",
"why": "It is the gold-standard security reference used by engineers studying for security-centric cloud certifications like the CNCF's Certified Kubernetes Security Specialist.",
"category": "Certification & Training"
},
{
@@ -5467,8 +5458,17 @@
"title": "knative-tutorial",
"date": "2026-01-15",
"stars": 5,
"impact": "high",
"why": "An authoritative, hands-on tutorial curriculum designed to train developers on advanced cloud-native serverless paradigms using Knative.",
"impact": "medium",
"why": "This is a dedicated, hands-on guide for training developers in serverless patterns, traffic splitting, and scale-to-zero capabilities using Knative.",
"category": "Certification & Training"
},
{
"url": "https://developers.redhat.com/cheat-sheets/containers",
"title": "developers.redhat.com: Containers Cheat Sheet",
"date": "2026-06-18",
"stars": 4,
"impact": "medium",
"why": "It teaches modern daemonless and rootless container architectures using Podman and Buildah, keeping developers aligned with secure enterprise container runtimes.",
"category": "Certification & Training"
}
],
@@ -5663,16 +5663,7 @@
"date": "2026-06-01",
"stars": 5,
"impact": "critical",
"why": "It serves as the premier distributed execution framework for scaling compute-heavy AI and Python workloads across cloud-native infrastructure.",
"category": "MLOps & Data Science"
},
{
"url": "https://github.com/Netflix/metaflow",
"title": "==github.com/Netflix/metaflow== 🌟",
"date": "2026-06-13",
"stars": 5,
"impact": "critical",
"why": "Provides an enterprise-ready, human-centric framework to build and manage production-grade data science pipelines seamlessly integrated with cloud infrastructure.",
"why": "It serves as the foundational distributed compute engine for scaling modern AI training and inference on cloud-native platforms.",
"category": "MLOps & Data Science"
},
{
@@ -5681,7 +5672,16 @@
"date": "2026-05-17",
"stars": 0,
"impact": "critical",
"why": "An industry-defining case study on scaling Kubernetes cluster infrastructure to handle massive LLM and AI training workloads at unprecedented scale.",
"why": "It provides the definitive industry blueprint and engineering lessons for orchestrating massive-scale deep learning infrastructure on Kubernetes.",
"category": "MLOps & Data Science"
},
{
"url": "https://github.com/Netflix/metaflow",
"title": "==github.com/Netflix/metaflow== 🌟",
"date": "2026-06-13",
"stars": 5,
"impact": "critical",
"why": "It seamlessly bridges the gap between local data science development and robust, production-grade cloud execution environments.",
"category": "MLOps & Data Science"
},
{
@@ -5690,16 +5690,7 @@
"date": "2026-05-19",
"stars": 5,
"impact": "high",
"why": "Meta's standard template repository that democratizes and scales LLM fine-tuning (PEFT/LoRA) and optimization in production.",
"category": "MLOps & Data Science"
},
{
"url": "https://github.com/argilla-io/argilla",
"title": "rubrix",
"date": "2026-06-08",
"stars": 5,
"impact": "high",
"why": "An essential open-source data curation platform that bridges the gap between human feedback (HITL) and continuous LLM alignment.",
"why": "It standardizes enterprise-level optimization, quantization, and fine-tuning strategies for operationalizing open-source LLMs.",
"category": "MLOps & Data Science"
},
{
@@ -5708,16 +5699,16 @@
"date": "2026-06-18",
"stars": 4,
"impact": "high",
"why": "A comprehensive reference manual and architecture guide mapping out the entire ecosystem of running machine learning workloads on Kubernetes.",
"why": "It acts as a comprehensive architectural handbook for configuring, deploying, and managing complex machine learning stacks on Kubernetes.",
"category": "MLOps & Data Science"
},
{
"url": "https://github.com/postgresml/postgresml",
"title": "postgresml/postgresml 🌟",
"date": "2025-07-01",
"stars": 4,
"url": "https://github.com/argilla-io/argilla",
"title": "rubrix",
"date": "2026-06-08",
"stars": 5,
"impact": "high",
"why": "A Rust-based extension that shifts the ML paradigm by enabling native training and real-time inference directly within PostgreSQL.",
"why": "It establishes an open-source platform for human-in-the-loop data curation, which is vital for aligning and fine-tuning production LLMs.",
"category": "MLOps & Data Science"
},
{
@@ -5726,7 +5717,7 @@
"date": "2026-05-21",
"stars": 3,
"impact": "high",
"why": "Simplifies cloud-native MLOps by translating Python declarations into isolated, reproducible container definitions with native CUDA support.",
"why": "It dramatically simplifies the creation of reproducible, containerized development environments with complex CUDA dependencies.",
"category": "MLOps & Data Science"
},
{
@@ -5735,7 +5726,16 @@
"date": "2026-06-02",
"stars": 4,
"impact": "high",
"why": "Meta's paradigm-shifting architecture that consolidates vector retrieval, filtering, and scoring into a single GPU-optimized PyTorch model.",
"why": "It introduces a major architectural shift by consolidating recommendation pipeline retrieval and scoring into a single GPU-optimized model.",
"category": "MLOps & Data Science"
},
{
"url": "https://github.com/postgresml/postgresml",
"title": "postgresml/postgresml 🌟",
"date": "2025-07-01",
"stars": 4,
"impact": "medium",
"why": "It drives database-level ML optimization by enabling users to run Rust-powered training and inference directly inside PostgreSQL.",
"category": "MLOps & Data Science"
},
{
@@ -5744,7 +5744,7 @@
"date": "2026-05-25",
"stars": 4,
"impact": "medium",
"why": "An essential, interactive terminal-based GPU monitoring tool that serves as a modern, real-time replacement for nvidia-smi.",
"why": "It dramatically improves on-node GPU observability for MLOps engineers through an interactive, terminal-based resource monitor.",
"category": "MLOps & Data Science"
}
],
@@ -7010,9 +7010,9 @@
"method": "gemini"
},
"Certification & Training": {
"last_analyzed": "2026-06-24T18:31:05.858334+02:00",
"entry_hash": "9eede2f0a4c2e141",
"entry_count": 407,
"last_analyzed": "2026-06-25T12:04:08.750036+02:00",
"entry_hash": "6258ce94873fd671",
"entry_count": 408,
"method": "gemini"
},
"Data, Messaging & Storage": {
@@ -7034,9 +7034,9 @@
"method": "gemini"
},
"MLOps & Data Science": {
"last_analyzed": "2026-06-19T14:42:46.625835+02:00",
"entry_hash": "a42a6cd2912f546a",
"entry_count": 52,
"last_analyzed": "2026-06-25T12:04:22.942596+02:00",
"entry_hash": "331739211353b187",
"entry_count": 53,
"method": "gemini"
},
"OpenShift / Red Hat": {
@@ -7174,9 +7174,9 @@
"method": "gemini"
},
"Certification & Training": {
"last_analyzed": "2026-06-19T14:48:36.202631+02:00",
"entry_hash": "13e704c45e043287",
"entry_count": 440,
"last_analyzed": "2026-06-25T12:04:41.553698+02:00",
"entry_hash": "7153bd2c3ffa1ad0",
"entry_count": 441,
"method": "gemini"
},
"Infrastructure as Code": {
@@ -7192,9 +7192,9 @@
"method": "gemini"
},
"MLOps & Data Science": {
"last_analyzed": "2026-06-19T14:49:31.131308+02:00",
"entry_hash": "a42a6cd2912f546a",
"entry_count": 52,
"last_analyzed": "2026-06-25T12:04:53.382754+02:00",
"entry_hash": "331739211353b187",
"entry_count": 53,
"method": "gemini"
},
"OpenShift / Red Hat": {
@@ -7332,9 +7332,9 @@
"method": "gemini"
},
"Certification & Training": {
"last_analyzed": "2026-06-19T14:55:40.604373+02:00",
"entry_hash": "b5ba72dc2e4b6e90",
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"last_analyzed": "2026-06-25T12:05:11.373583+02:00",
"entry_hash": "16671ac3a8524104",
"entry_count": 443,
"method": "gemini"
},
"Infrastructure as Code": {
@@ -7350,9 +7350,9 @@
"method": "gemini"
},
"MLOps & Data Science": {
"last_analyzed": "2026-06-19T14:56:34.586247+02:00",
"entry_hash": "5647bc7694fadca0",
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"last_analyzed": "2026-06-25T12:05:26.860402+02:00",
"entry_hash": "55a12501e7102d13",
"entry_count": 54,
"method": "gemini"
},
"OpenShift / Red Hat": {
@@ -7440,6 +7440,6 @@
"method": "fallback_small"
}
},
"last_updated": "2026-06-25T11:44:53.567415+02:00"
"last_updated": "2026-06-25T12:05:27.864798+02:00"
}
}
docs/static/extra.css
Vendored
+8
View File
@@ -49,6 +49,14 @@ reset max-width with the following CSS: */
filter: brightness(1.2);
}
/* Dark-logo fix: invert black-on-transparent logos so they remain visible in dark mode */
[data-md-color-scheme="slate"] img[src*="nutanix_logo"] {
filter: invert(1);
}
[data-md-color-scheme="slate"] img[src*="nutanix_logo"]:hover {
filter: invert(1) brightness(1.2);
}
v2-docs/index.md
+3 -3
View File
@@ -81,9 +81,9 @@
2. **Standard Layer (Mapped)**: Resources identified as candidates for Elite status but pending deep AI analysis.
**Current Inventory Coverage:**
- **V1 Base Inventory**: 18655 total resources analyzed.
- **V2 Elite Selection**: 14487 candidates identified (77.66% density ratio).
- **AI Enrichment Coverage**: 14487 / 14487 (100.0%)
- **V1 Base Inventory**: 18657 total resources analyzed.
- **V2 Elite Selection**: 14489 candidates identified (77.66% density ratio).
- **AI Enrichment Coverage**: 14489 / 14489 (100.0%)
- **GitHub Metadata Coverage**: 1764 / 1764 (100.0%) - *Critical for Maturity Tagging*
- **Status**: The system is incrementally processing pending resources to complete the knowledge graph.
v2-docs/tech-digest.md
+60 -60
View File
@@ -302,46 +302,46 @@ search:
| Date | Resource | Impact | Why It Matters |
| :--- | :--- | :---: | :--- |
| 2026-06-01 | [Ray](https://docs.ray.io/en/latest) | 🔴 critical | Ray is the industry-standard distributed compute framework essential for scaling heavy AI training and LLM workloads. |
| 2026-05-17 | [openai.com: Scaling Kubernetes to 7,500 nodes 🌟](https://openai.com/research/scaling-kubernetes-to-7500-nodes) | 🔴 critical | OpenAI's scaling insights provide the ultimate blueprint for running massive-scale machine learning workloads on Kubernetes. |
| 2026-06-13 | [github.com/Netflix/metaflow 🌟](https://github.com/Netflix/metaflow) | 🟡 high | Metaflow bridges the gap between local data science development and scalable cloud-native production infrastructure. |
| 2026-05-19 | [github.com/meta-llama/llama-recipes](https://github.com/meta-llama/llama-cookbook) | 🟡 high | Meta's official recipes establish standardized best practices for parameter-efficient fine-tuning and LLM optimization. |
| 2026-06-08 | [rubrix](https://github.com/argilla-io/argilla) | 🟡 high | Argilla addresses the critical LLM challenge of data curation and continuous human-in-the-loop alignment. |
| 2026-06-02 | [SilverTorch: Index as Model — A New Retrieval Paradigm for Recommendation Systems](https://engineering.fb.com/2026/05/26/ml-applications/silvertorch-index-as-model-new-retrieval-paradigm-recommendation-systems) | 🟡 high | SilverTorch redefines recommendation engine architectures by unifying retrieval and scoring into a single GPU-optimized model. |
| 2026-06-18 | [mikeroyal/Kubernetes-Guide: Machine Learning 🌟](https://github.com/mikeroyal/Kubernetes-Guide/blob/main/README.md) | 🟡 high | This manual serves as an indispensable reference mapping the complex landscape of running machine learning workloads on Kubernetes. |
| 2026-05-17 | [medium.com/workday-engineering: Implementing a Fully Automated Sharding' Strategy on Kubernetes for Multi-tenanted Machine Learning Applications](https://medium.com/workday-engineering/implementing-a-fully-automated-sharding-strategy-on-kubernetes-for-multi-tenanted-machine-learning-4371c48122ae) | 🟡 high | It outlines a highly sophisticated, real-world architectural pattern for managing multi-tenant ML applications using Kubernetes sharding. |
| 2026-05-17 | [medium.com/@bchenjh: Distributed full fine-tuning of Llama2 on Kubernetes](https://medium.com/@bchenjh/full-fine-tuning-of-llama2-on-kubernetes-a983e1eb2259) | 🟡 high | This guide provides a practical, cloud-native blueprint for running distributed LLM fine-tuning operations on Kubernetes. |
| 2026-05-21 | [tensorchord/envd: Reproducible development environment for AI/ML 🌟](https://github.com/tensorchord/envd) | 🔵 medium | Envd solves the notorious ML pain point of environment reproducibility by generating isolated, CUDA-ready dev containers from Python declarations. |
| 2026-06-01 | [Ray](https://docs.ray.io/en/latest) | 🔴 critical | A critical distributed computing framework that has become the standard for scaling heavy AI training and inference workloads natively on cloud infrastructure. |
| 2026-05-17 | [openai.com: Scaling Kubernetes to 7,500 nodes 🌟](https://openai.com/research/scaling-kubernetes-to-7500-nodes) | 🔴 critical | An industry-defining engineering post outlining how to scale Kubernetes to massive heights to support large-scale AI training workloads. |
| 2026-06-13 | [github.com/Netflix/metaflow 🌟](https://github.com/Netflix/metaflow) | 🟡 high | An enterprise-ready framework from Netflix that seamlessly integrates local data science development with scalable cloud-native compute. |
| 2026-05-19 | [github.com/meta-llama/llama-recipes](https://github.com/meta-llama/llama-cookbook) | 🟡 high | Meta's official optimization and fine-tuning repository that sets the standard for deploying large language models efficiently in production. |
| 2026-06-18 | [mikeroyal/Kubernetes-Guide: Machine Learning 🌟](https://github.com/mikeroyal/Kubernetes-Guide/blob/main/README.md) | 🟡 high | An invaluable reference mapping out the tools, configurations, and architectures required to run machine learning workloads on Kubernetes. |
| 2026-05-17 | [medium.com/workday-engineering: Implementing a Fully Automated Sharding' Strategy on Kubernetes for Multi-tenanted Machine Learning Applications](https://medium.com/workday-engineering/implementing-a-fully-automated-sharding-strategy-on-kubernetes-for-multi-tenanted-machine-learning-4371c48122ae) | 🟡 high | Provides a highly novel engineering blueprint for automating multi-tenant ML application sharding natively inside Kubernetes clusters. |
| 2026-05-17 | [medium.com/@bchenjh: Distributed full fine-tuning of Llama2 on Kubernetes](https://medium.com/@bchenjh/full-fine-tuning-of-llama2-on-kubernetes-a983e1eb2259) | 🟡 high | Details a highly practical and cloud-native approach to running distributed fine-tuning of large language models on Kubernetes. |
| 2026-05-17 | [medium.com/bakdata: Scalable Machine Learning with Kafka Streams and KServe](https://medium.com/bakdata/scalable-machine-learning-with-kafka-streams-and-kserve-85308858d867) | 🟡 high | Demonstrates a robust integration of Kafka event streaming with KServe for scalable, real-time ML model inference in Kubernetes environments. |
| 2026-06-02 | [SilverTorch: Index as Model — A New Retrieval Paradigm for Recommendation Systems](https://engineering.fb.com/2026/05/26/ml-applications/silvertorch-index-as-model-new-retrieval-paradigm-recommendation-systems) | 🟡 high | Presents a paradigm-shifting approach from Meta that consolidates recommendation pipelines into unified, GPU-optimized PyTorch models. |
| 2026-05-21 | [tensorchord/envd: Reproducible development environment for AI/ML 🌟](https://github.com/tensorchord/envd) | 🔵 medium | An innovative tool that compiles Python definitions into containerized environments, ensuring reproducible GPU-enabled development workflows. |
=== "Last 6 Months"
| Date | Resource | Impact | Why It Matters |
| :--- | :--- | :---: | :--- |
| 2026-06-01 | [Ray](https://docs.ray.io/en/latest) | 🔴 critical | As the dominant distributed execution framework for AI, Ray is foundational for scaling compute-heavy workloads across cloud-native environments. |
| 2026-05-17 | [openai.com: Scaling Kubernetes to 7,500 nodes 🌟](https://openai.com/research/scaling-kubernetes-to-7500-nodes) | 🔴 critical | This landmark case study provides invaluable infrastructure blueprints for scaling Kubernetes to handle massive, state-of-the-art AI/ML training workloads. |
| 2026-06-13 | [github.com/Netflix/metaflow 🌟](https://github.com/Netflix/metaflow) | 🔴 critical | Netflix's production-proven framework seamlessly bridges local data science development with enterprise-scale cloud infrastructure and orchestration. |
| 2026-05-19 | [github.com/meta-llama/llama-recipes](https://github.com/meta-llama/llama-cookbook) | 🟡 high | Provides industry-standard templates for parameter-efficient fine-tuning and optimization, defining modern LLMOps deployment patterns. |
| 2026-05-17 | [medium.com/workday-engineering: Implementing a Fully Automated Sharding' Strategy on Kubernetes for Multi-tenanted Machine Learning Applications](https://medium.com/workday-engineering/implementing-a-fully-automated-sharding-strategy-on-kubernetes-for-multi-tenanted-machine-learning-4371c48122ae) | 🟡 high | Solves critical multi-tenancy and resource isolation challenges for ML applications at enterprise scale using native Kubernetes sharding. |
| 2026-06-18 | [mikeroyal/Kubernetes-Guide: Machine Learning 🌟](https://github.com/mikeroyal/Kubernetes-Guide/blob/main/README.md) | 🟡 high | Serves as an essential technical reference mapping out configurations and architectural patterns for running diverse ML workloads on Kubernetes. |
| 2026-05-17 | [medium.com/@bchenjh: Distributed full fine-tuning of Llama2 on Kubernetes](https://medium.com/@bchenjh/full-fine-tuning-of-llama2-on-kubernetes-a983e1eb2259) | 🟡 high | Demonstrates a practical, cloud-native pattern for executing complex, distributed LLM fine-tuning directly on Kubernetes clusters. |
| 2026-06-08 | [rubrix](https://github.com/argilla-io/argilla) | 🟡 high | A critical open-source platform that enables human-in-the-loop data curation, which is essential for continuous alignment of modern generative AI models. |
| 2026-05-21 | [tensorchord/envd: Reproducible development environment for AI/ML 🌟](https://github.com/tensorchord/envd) | 🔵 medium | Simplifies the ML-to-cloud transition by automatically packaging Python declarations into highly reproducible, CUDA-enabled containers. |
| 2026-05-17 | [medium.com/bakdata: Scalable Machine Learning with Kafka Streams and KServe](https://medium.com/bakdata/scalable-machine-learning-with-kafka-streams-and-kserve-85308858d867) | 🔵 medium | Showcases a robust, event-driven architecture for scaling real-time model inference using KServe and Kafka on Kubernetes. |
| 2026-06-01 | [Ray](https://docs.ray.io/en/latest) | 🔴 critical | Ray is the industry-standard distributed computing framework critical for scaling heavy AI training and Python workloads across cloud native environments. |
| 2026-05-17 | [openai.com: Scaling Kubernetes to 7,500 nodes 🌟](https://openai.com/research/scaling-kubernetes-to-7500-nodes) | 🔴 critical | This landmark publication details how OpenAI pushed Kubernetes to its limits, establishing the blueprint for scaling massive AI training infrastructures. |
| 2026-06-13 | [github.com/Netflix/metaflow 🌟](https://github.com/Netflix/metaflow) | 🟡 high | Metaflow bridges the developer experience gap by seamlessly connecting local Python code to production cloud scaling and execution. |
| 2026-05-19 | [github.com/meta-llama/llama-recipes](https://github.com/meta-llama/llama-cookbook) | 🟡 high | Meta's standard playbook offers critical fine-tuning and optimization templates for deploying large language models efficiently at scale. |
| 2026-06-02 | [SilverTorch: Index as Model — A New Retrieval Paradigm for Recommendation Systems](https://engineering.fb.com/2026/05/26/ml-applications/silvertorch-index-as-model-new-retrieval-paradigm-recommendation-systems) | 🟡 high | Redefines recommendation systems by unifying vector retrieval, filtering, and scoring into a single PyTorch model, vastly improving GPU efficiency. |
| 2026-06-18 | [mikeroyal/Kubernetes-Guide: Machine Learning 🌟](https://github.com/mikeroyal/Kubernetes-Guide/blob/main/README.md) | 🟡 high | An invaluable reference architecture that maps out the complex ecosystem of machine learning tools running directly on Kubernetes. |
| 2026-06-08 | [rubrix](https://github.com/argilla-io/argilla) | 🟡 high | Argilla addresses the crucial LLM alignment phase by offering an open-source platform for continuous human-in-the-loop data curation. |
| 2026-05-17 | [medium.com/workday-engineering: Implementing a Fully Automated Sharding' Strategy on Kubernetes for Multi-tenanted Machine Learning Applications](https://medium.com/workday-engineering/implementing-a-fully-automated-sharding-strategy-on-kubernetes-for-multi-tenanted-machine-learning-4371c48122ae) | 🔵 medium | Provides a practical production case study on automating database and application sharding on Kubernetes for multi-tenant ML workloads. |
| 2026-05-21 | [tensorchord/envd: Reproducible development environment for AI/ML 🌟](https://github.com/tensorchord/envd) | 🔵 medium | Simplifies AI/ML engineering by translating declarative Python environments into reproducible, containerized CUDA configurations. |
| 2026-05-25 | [github.com/XuehaiPan/nvitop 🌟](https://github.com/XuehaiPan/nvitop) | 🔵 medium | A highly practical terminal-based monitoring tool that replaces nvidia-smi with interactive, real-time GPU profiling for developers. |
=== "Last 12 Months"
| Date | Resource | Impact | Why It Matters |
| :--- | :--- | :---: | :--- |
| 2026-06-01 | [Ray](https://docs.ray.io/en/latest) | 🔴 critical | It serves as the premier distributed execution framework for scaling compute-heavy AI and Python workloads across cloud-native infrastructure. |
| 2026-06-13 | [github.com/Netflix/metaflow 🌟](https://github.com/Netflix/metaflow) | 🔴 critical | Provides an enterprise-ready, human-centric framework to build and manage production-grade data science pipelines seamlessly integrated with cloud infrastructure. |
| 2026-05-17 | [openai.com: Scaling Kubernetes to 7,500 nodes 🌟](https://openai.com/research/scaling-kubernetes-to-7500-nodes) | 🔴 critical | An industry-defining case study on scaling Kubernetes cluster infrastructure to handle massive LLM and AI training workloads at unprecedented scale. |
| 2026-05-19 | [github.com/meta-llama/llama-recipes](https://github.com/meta-llama/llama-cookbook) | 🟡 high | Meta's standard template repository that democratizes and scales LLM fine-tuning (PEFT/LoRA) and optimization in production. |
| 2026-06-08 | [rubrix](https://github.com/argilla-io/argilla) | 🟡 high | An essential open-source data curation platform that bridges the gap between human feedback (HITL) and continuous LLM alignment. |
| 2026-06-18 | [mikeroyal/Kubernetes-Guide: Machine Learning 🌟](https://github.com/mikeroyal/Kubernetes-Guide/blob/main/README.md) | 🟡 high | A comprehensive reference manual and architecture guide mapping out the entire ecosystem of running machine learning workloads on Kubernetes. |
| 2025-07-01 | [postgresml/postgresml 🌟](https://github.com/postgresml/postgresml) | 🟡 high | A Rust-based extension that shifts the ML paradigm by enabling native training and real-time inference directly within PostgreSQL. |
| 2026-05-21 | [tensorchord/envd: Reproducible development environment for AI/ML 🌟](https://github.com/tensorchord/envd) | 🟡 high | Simplifies cloud-native MLOps by translating Python declarations into isolated, reproducible container definitions with native CUDA support. |
| 2026-06-02 | [SilverTorch: Index as Model — A New Retrieval Paradigm for Recommendation Systems](https://engineering.fb.com/2026/05/26/ml-applications/silvertorch-index-as-model-new-retrieval-paradigm-recommendation-systems) | 🟡 high | Meta's paradigm-shifting architecture that consolidates vector retrieval, filtering, and scoring into a single GPU-optimized PyTorch model. |
| 2026-05-25 | [github.com/XuehaiPan/nvitop 🌟](https://github.com/XuehaiPan/nvitop) | 🔵 medium | An essential, interactive terminal-based GPU monitoring tool that serves as a modern, real-time replacement for nvidia-smi. |
| 2026-06-01 | [Ray](https://docs.ray.io/en/latest) | 🔴 critical | It serves as the foundational distributed compute engine for scaling modern AI training and inference on cloud-native platforms. |
| 2026-05-17 | [openai.com: Scaling Kubernetes to 7,500 nodes 🌟](https://openai.com/research/scaling-kubernetes-to-7500-nodes) | 🔴 critical | It provides the definitive industry blueprint and engineering lessons for orchestrating massive-scale deep learning infrastructure on Kubernetes. |
| 2026-06-13 | [github.com/Netflix/metaflow 🌟](https://github.com/Netflix/metaflow) | 🔴 critical | It seamlessly bridges the gap between local data science development and robust, production-grade cloud execution environments. |
| 2026-05-19 | [github.com/meta-llama/llama-recipes](https://github.com/meta-llama/llama-cookbook) | 🟡 high | It standardizes enterprise-level optimization, quantization, and fine-tuning strategies for operationalizing open-source LLMs. |
| 2026-06-18 | [mikeroyal/Kubernetes-Guide: Machine Learning 🌟](https://github.com/mikeroyal/Kubernetes-Guide/blob/main/README.md) | 🟡 high | It acts as a comprehensive architectural handbook for configuring, deploying, and managing complex machine learning stacks on Kubernetes. |
| 2026-06-08 | [rubrix](https://github.com/argilla-io/argilla) | 🟡 high | It establishes an open-source platform for human-in-the-loop data curation, which is vital for aligning and fine-tuning production LLMs. |
| 2026-05-21 | [tensorchord/envd: Reproducible development environment for AI/ML 🌟](https://github.com/tensorchord/envd) | 🟡 high | It dramatically simplifies the creation of reproducible, containerized development environments with complex CUDA dependencies. |
| 2026-06-02 | [SilverTorch: Index as Model — A New Retrieval Paradigm for Recommendation Systems](https://engineering.fb.com/2026/05/26/ml-applications/silvertorch-index-as-model-new-retrieval-paradigm-recommendation-systems) | 🟡 high | It introduces a major architectural shift by consolidating recommendation pipeline retrieval and scoring into a single GPU-optimized model. |
| 2025-07-01 | [postgresml/postgresml 🌟](https://github.com/postgresml/postgresml) | 🔵 medium | It drives database-level ML optimization by enabling users to run Rust-powered training and inference directly inside PostgreSQL. |
| 2026-05-25 | [github.com/XuehaiPan/nvitop 🌟](https://github.com/XuehaiPan/nvitop) | 🔵 medium | It dramatically improves on-node GPU observability for MLOps engineers through an interactive, terminal-based resource monitor. |
## Python, Java & Developer Ecosystem
@@ -782,46 +782,46 @@ search:
| Date | Resource | Impact | Why It Matters |
| :--- | :--- | :---: | :--- |
| 2026-06-01 | [The Linux Foundation Training](https://training.linuxfoundation.org/resources) | 🔴 critical | It is the official authority hosting curricula and exams for the industry-standard CKA, CKAD, and CKS cloud-native certifications. |
| 2026-06-01 | [kubernetes.io 🌟](https://kubernetes.io/docs/reference/kubectl/quick-reference) | 🔴 critical | Crucial official cheat sheet for mastering command-line operations essential for passing CKA, CKAD, and CKS exams. |
| 2026-06-01 | [cheatsheetseries.owasp.org: OWASP Cheat Sheet Series 🌟🌟](https://cheatsheetseries.owasp.org/index.html) | 🔴 critical | The definitive security reference mapping modern web application vulnerabilities, which is critical knowledge for the CKS certification. |
| 2026-06-01 | [kube.academy](https://kube.academy) | 🟡 high | Provides high-quality, structured, and free modular training tracks focusing on complex Kubernetes cluster operations and architectural concepts. |
| 2026-06-01 | [Whizlabs](https://www.whizlabs.com) | 🟡 high | Offers direct cloud-based sandbox environments and practice simulations for key CNCF certifications like CKA, CKAD, and CKS. |
| 2026-06-18 | [techiescamp/devops-projects:Real-World DevOps Projects For Learning](https://github.com/techiescamp/devops-projects) | 🟡 high | Provides real-world, end-to-end infrastructure blueprints and multi-tier pipelines that offer practical, hands-on learning for DevOps and cloud-native engineers. |
| 2026-06-01 | [edx.org](https://www.edx.org) | 🟡 high | Hosts the official Linux Foundation cloud-native course catalog, bridging system administration theory with hands-on command-line practice. |
| 2026-06-08 | [stefanprodan/podinfo](https://github.com/stefanprodan/podinfo) | 🟡 high | An industry-standard mock microservice used widely in workshops to teach Kubernetes deployment patterns, telemetry, and progressive delivery. |
| 2026-06-01 | [techstudyslack.com](https://techstudyslack.com) | 🔵 medium | A highly active peer-to-peer community hub specifically dedicated to real-time debugging support and collaborative preparation for Kubernetes certifications. |
| 2026-06-18 | [github.com/devoriales/kubectl-cheatsheet](https://github.com/devoriales/cheatsheets) | 🔵 medium | An opinionated command cheat sheet optimized for fast-paced troubleshooting and practical practice during hands-on Kubernetes exams. |
| 2026-06-01 | [The Linux Foundation Training](https://training.linuxfoundation.org/resources) | 🔴 critical | As the official training arm of the Linux Foundation, it establishes and maintains the curricula for industry-standard CKA, CKAD, and CKS certifications. |
| 2026-06-01 | [kubernetes.io 🌟](https://kubernetes.io/docs/reference/kubectl/quick-reference) | 🔴 critical | This is the canonical kubectl command reference and is the primary external document allowed for consultation during official Kubernetes exams. |
| 2026-06-01 | [kube.academy](https://kube.academy) | 🟡 high | Provides highly polished, free, and modular training tracks covering advanced Kubernetes administration and security patterns. |
| 2026-06-01 | [Whizlabs](https://www.whizlabs.com) | 🟡 high | Offers comprehensive practice exams and cloud-based sandbox environments specifically tailored to prepare candidates for CNCF certifications. |
| 2026-06-01 | [edx.org](https://www.edx.org) | 🟡 high | Acts as the key academic partner hosting the Linux Foundation's official entry-level cloud-native and container courses. |
| 2026-06-18 | [techiescamp/devops-projects:Real-World DevOps Projects For Learning](https://github.com/techiescamp/devops-projects) | 🟡 high | Provides structured, real-world infrastructure and CI/CD blueprints that allow engineers to practice hands-on platform engineering skills. |
| 2026-06-01 | [techstudyslack.com](https://techstudyslack.com) | 🟡 high | A massive, active peer-led community offering study groups, real-time debugging, and mentoring for cloud and Kubernetes certification prep. |
| 2026-06-08 | [stefanprodan/podinfo](https://github.com/stefanprodan/podinfo) | 🟡 high | The definitive microservice tool used across the industry to learn and demonstrate Kubernetes features, instrumentation, and progressive delivery. |
| 2026-06-25 | [skillbuilder.aws: AWS Skill Builder](https://skillbuilder.aws/) | 🟡 high | The official learning portal for AWS, delivering structured paths and exam readiness assessments crucial for cloud architects and developers. |
| 2026-06-18 | [github.com/devoriales/kubectl-cheatsheet](https://github.com/devoriales/cheatsheets) | 🔵 medium | Curates opinionated, real-world troubleshooting commands that serve as an excellent study guide for the hands-on portions of container exams. |
=== "Last 6 Months"
| Date | Resource | Impact | Why It Matters |
| :--- | :--- | :---: | :--- |
| 2026-06-01 | [The Linux Foundation Training](https://training.linuxfoundation.org/resources) | 🔴 critical | As the official home for the CKA, CKAD, and CKS curricula, this is the single most critical training source for cloud-native professionals. |
| 2026-06-01 | [kubernetes.io 🌟](https://kubernetes.io/docs/reference/kubectl/quick-reference) | 🟡 high | The canonical kubectl quick reference is an indispensable daily tool and exam aid for candidates preparing for hands-on CNCF certifications. |
| 2026-06-01 | [kube.academy](https://kube.academy) | 🟡 high | This VMware Tanzu-sponsored platform offers high-quality, free modular tracks specifically designed to teach advanced Kubernetes administration concepts. |
| 2026-06-01 | [Whizlabs](https://www.whizlabs.com) | 🟡 high | Provides highly realistic exam simulators and sandbox environments specifically designed for preparing candidates to pass the CKA, CKAD, and CKS. |
| 2026-06-01 | [edx.org](https://www.edx.org) | 🟡 high | Hosts the official introductory curricula from the Linux Foundation, acting as a primary starting point for university-grade cloud-native certificates. |
| 2025-04-27 | [AdminTurnedDevOps/DevOps-The-Hard-Way-AWS](https://github.com/AdminTurnedDevOps/DevOps-The-Hard-Way-AWS) | 🟡 high | Offers a rigorous, step-by-step curriculum for learning real-world cloud operations, infrastructure as code, and security scanning on AWS. |
| 2026-06-18 | [techiescamp/devops-projects:Real-World DevOps Projects For Learning](https://github.com/techiescamp/devops-projects) | 🟡 high | Provides comprehensive, real-world infrastructure blueprints and CI/CD templates essential for hands-on DevOps learning and portfolio building. |
| 2026-06-01 | [cheatsheetseries.owasp.org: OWASP Cheat Sheet Series 🌟🌟](https://cheatsheetseries.owasp.org/index.html) | 🟡 high | Serves as the ultimate application security reference, heavily utilized in training for the Certified Kubernetes Security Specialist (CKS) exam. |
| 2026-06-08 | [stefanprodan/podinfo](https://github.com/stefanprodan/podinfo) | 🟡 high | The de facto reference microservice used by engineers to practice and test Kubernetes deployment patterns, service meshes, and observability tools. |
| 2026-01-15 | [knative-tutorial](https://github.com/redhat-developer-demos/knative-tutorial) | 🔵 medium | Delivers a structured, practical tutorial for mastering Knative serving, eventing, and scale-to-zero serverless paradigms in Kubernetes. |
| 2026-06-01 | [The Linux Foundation Training](https://training.linuxfoundation.org/resources) | 🔴 critical | It is the official training and curriculum provider for the industry-standard CKA, CKAD, and CKS certifications. |
| 2026-06-01 | [kubernetes.io 🌟](https://kubernetes.io/docs/reference/kubectl/quick-reference) | 🔴 critical | This canonical kubectl guide is the most critical quick-reference tool for practicing hands-on Kubernetes tasks during exam preparation. |
| 2026-06-01 | [cheatsheetseries.owasp.org: OWASP Cheat Sheet Series 🌟🌟](https://cheatsheetseries.owasp.org/index.html) | 🔴 critical | It is the definitive guide for learning web application security mitigations, making it vital for cloud-native security and CKS preparation. |
| 2026-06-01 | [kube.academy](https://kube.academy) | 🟡 high | It offers structured, high-quality, and free Kubernetes educational pathways crucial for training production-ready platform engineers. |
| 2026-06-01 | [Whizlabs](https://www.whizlabs.com) | 🟡 high | It delivers dedicated exam simulation sandboxes that directly help engineers pass Kubernetes certifications like CKA and CKS. |
| 2026-06-08 | [stefanprodan/podinfo](https://github.com/stefanprodan/podinfo) | 🟡 high | This application serves as the gold standard reference microservice for testing and learning Kubernetes orchestrations, health checks, and metrics. |
| 2026-06-18 | [techiescamp/devops-projects:Real-World DevOps Projects For Learning](https://github.com/techiescamp/devops-projects) | 🟡 high | It provides invaluable real-world project templates for hands-on learning of Terraform, Ansible, and multi-tier CI/CD pipelines. |
| 2025-04-27 | [AdminTurnedDevOps/DevOps-The-Hard-Way-AWS](https://github.com/AdminTurnedDevOps/DevOps-The-Hard-Way-AWS) | 🟡 high | This repository offers a comprehensive, step-by-step curriculum for mastering real-world AWS cloud operations and DevOps practices. |
| 2026-01-15 | [knative-tutorial](https://github.com/redhat-developer-demos/knative-tutorial) | 🟡 high | It is an essential hands-on learning asset for mastering serverless architectures, traffic splitting, and scale-to-zero using Knative on Kubernetes. |
| 2026-05-17 | [Spring PetClinic Microservices](https://github.com/spring-petclinic/spring-petclinic-microservices) | 🟡 high | This acts as the premier reference architecture for training teams on how to deploy and configure Java microservices in a cloud-native ecosystem. |
=== "Last 12 Months"
| Date | Resource | Impact | Why It Matters |
| :--- | :--- | :---: | :--- |
| 2026-06-01 | [The Linux Foundation Training](https://training.linuxfoundation.org/resources) | 🔴 critical | The definitive training and certification source that directly defines the curricula for the CKA, CKAD, and CKS benchmarks. |
| 2026-06-01 | [kubernetes.io 🌟](https://kubernetes.io/docs/reference/kubectl/quick-reference) | 🔴 critical | The canonical kubectl reference and the primary permitted documentation resource during official Linux Foundation Kubernetes exams. |
| 2026-06-01 | [kube.academy](https://kube.academy) | 🟡 high | A highly polished, VMware-sponsored training platform that guides engineers through complex, real-world Kubernetes operational tracks. |
| 2026-06-01 | [Whizlabs](https://www.whizlabs.com) | 🟡 high | A premier professional certification preparation engine offering hands-on cloud sandboxes for CKA, CKAD, and CKS exams. |
| 2025-04-27 | [AdminTurnedDevOps/DevOps-The-Hard-Way-AWS](https://github.com/AdminTurnedDevOps/DevOps-The-Hard-Way-AWS) | 🟡 high | A rigorous, hands-on learning curriculum focused on configuring real-world AWS and DevOps infrastructure from the ground up. |
| 2026-06-08 | [stefanprodan/podinfo](https://github.com/stefanprodan/podinfo) | 🟡 high | The industry-standard microservice application used globally to train teams on Kubernetes deployment, health checks, and observability. |
| 2026-06-18 | [techiescamp/devops-projects:Real-World DevOps Projects For Learning](https://github.com/techiescamp/devops-projects) | 🟡 high | A highly practical, end-to-end compilation of DevOps blueprints that helps engineers transition from theoretical knowledge to real-world pipelines. |
| 2026-06-01 | [edx.org](https://www.edx.org) | 🟡 high | Hosts the official Linux Foundation cloud-native course catalog, providing structured, university-grade pathways for open-source engineering. |
| 2026-06-01 | [terraform.io: Terraform Commands](https://developer.hashicorp.com/terraform/cli/commands) | 🔵 medium | The official HashiCorp command reference essential for mastering advanced state management, a core focus of Terraform certifications. |
| 2026-01-15 | [knative-tutorial](https://github.com/redhat-developer-demos/knative-tutorial) | 🟡 high | An authoritative, hands-on tutorial curriculum designed to train developers on advanced cloud-native serverless paradigms using Knative. |
| 2026-06-01 | [The Linux Foundation Training](https://training.linuxfoundation.org/resources) | 🔴 critical | This is the official curriculum custodian for the highly respected CKA, CKAD, and CKS certifications, directly shaping how modern cloud-native engineers are trained. |
| 2026-06-01 | [kubernetes.io 🌟](https://kubernetes.io/docs/reference/kubectl/quick-reference) | 🔴 critical | It serves as the definitive reference guide allowed during CNCF certification exams, making it an essential tool for training administrators and developers. |
| 2026-06-08 | [stefanprodan/podinfo](https://github.com/stefanprodan/podinfo) | 🟡 high | This premier mock microservice is the industry-standard sandbox application used to teach and test Kubernetes deployment patterns, GitOps, and instrumentation. |
| 2026-06-01 | [kube.academy](https://kube.academy) | 🟡 high | This platform delivers high-quality, free Kubernetes training paths curated by VMware Tanzu, making advanced cluster topics highly accessible. |
| 2026-06-18 | [techiescamp/devops-projects:Real-World DevOps Projects For Learning](https://github.com/techiescamp/devops-projects) | 🟡 high | It provides comprehensive, real-world infrastructure blueprints and CI/CD pipelines essential for hands-on, practical DevOps training. |
| 2025-04-27 | [AdminTurnedDevOps/DevOps-The-Hard-Way-AWS](https://github.com/AdminTurnedDevOps/DevOps-The-Hard-Way-AWS) | 🟡 high | This rigorous, hands-on curriculum provides step-by-step practical guides for building and securing enterprise-grade infrastructure on AWS. |
| 2026-06-01 | [Whizlabs](https://www.whizlabs.com) | 🟡 high | It offers highly rated CKA, CKAD, and CKS exam simulations combined with cloud sandboxes, directly assisting engineers in acquiring certification. |
| 2026-06-01 | [cheatsheetseries.owasp.org: OWASP Cheat Sheet Series 🌟🌟](https://cheatsheetseries.owasp.org/index.html) | 🟡 high | It is the gold-standard security reference used by engineers studying for security-centric cloud certifications like the CNCF's Certified Kubernetes Security Specialist. |
| 2026-01-15 | [knative-tutorial](https://github.com/redhat-developer-demos/knative-tutorial) | 🔵 medium | This is a dedicated, hands-on guide for training developers in serverless patterns, traffic splitting, and scale-to-zero capabilities using Knative. |
| 2026-06-18 | [developers.redhat.com: Containers Cheat Sheet](https://developers.redhat.com/cheat-sheets/containers) | 🔵 medium | It teaches modern daemonless and rootless container architectures using Podman and Buildah, keeping developers aligned with secure enterprise container runtimes. |
## AWS