From 9184cb3f7238ea5d3eaa03464793db815d39b8e2 Mon Sep 17 00:00:00 2001 From: Nubenetes Bot Date: Thu, 25 Jun 2026 10:05:47 +0000 Subject: [PATCH] feat: sync V2 elite curated edition and README metrics [skip ci] --- README.md | 10 +- data/inventory.sql | 2 +- data/inventory.yaml | 3 +- data/news_digest.json | 434 ++++++++++++++++++++--------------------- v2-docs/index.md | 6 +- v2-docs/tech-digest.md | 120 ++++++------ 6 files changed, 288 insertions(+), 287 deletions(-) diff --git a/README.md b/README.md index 305bb1f8..8a06e3b8 100644 --- a/README.md +++ b/README.md @@ -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)** | @@ -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) | @@ -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] ``` @@ -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 | ### 2.4. Content Distribution and Semantic Clustering diff --git a/data/inventory.sql b/data/inventory.sql index 52684683..7be92a18 100644 --- a/data/inventory.sql +++ b/data/inventory.sql @@ -12452,7 +12452,7 @@ INSERT INTO "resources" VALUES('https://skamille.medium.com/an-incomplete-list-o INSERT INTO "resources" VALUES('https://skamille.medium.com/how-new-managers-fail-individual-contributors-839a13bda1c5','skamille.medium.com: How New Managers Fail Individual Contributors','','N/A',0,'A curated technical resource and architectural guide covering skamille.medium.com: How New Managers Fail Individual Contributors in the Kubernetes Tools ecosystem.','English','Reference','Intermediate',0,NULL,'manual','N/A',100.0,1779032834,0,'2026-05-17T17:47:14.775138+02:00',NULL,NULL,NULL,'["Architectural Foundations", "Kubernetes Tools", "General Reference"]','["[COMMUNITY-TOOL]"]','["docs/project-management-methodology.md"]','["project-management-methodology.md"]','{}','{}'); INSERT INTO "resources" VALUES('https://skamille.medium.com/make-boring-plans-9438ce5cb053','skamille.medium.com: Make Boring Plans','','N/A',0,'A curated technical resource and architectural guide covering skamille.medium.com: Make Boring Plans in the Kubernetes Tools ecosystem.','English','Reference','Intermediate',0,NULL,'manual','N/A',100.0,1779031341,0,'2026-05-17T17:22:21.297942+02:00',NULL,NULL,NULL,'["Architectural Foundations", "Kubernetes Tools", "General Reference"]','["[COMMUNITY-TOOL]"]','["docs/introduction.md"]','["introduction.md"]','{}','{}'); INSERT INTO "resources" VALUES('https://skildops.medium.com/backup-an-entire-kubernetes-cluster-using-velero-to-aws-s3-73d76d51d4bc','skildops.medium.com: Backup an entire Kubernetes cluster using Velero to'' AWS S3','','N/A',0,'A curated technical resource and architectural guide covering skildops.medium.com: Backup an entire Kubernetes cluster using Velero to'' AWS S3 in the Kubernetes Tools ecosystem.','English','Reference','Intermediate',0,NULL,'manual','N/A',100.0,1779031651,0,'2026-05-17T17:27:31.931120+02:00',NULL,NULL,NULL,'["Architectural Foundations", "Kubernetes Tools", "General Reference"]','["[COMMUNITY-TOOL]"]','["docs/kubernetes-backup-migrations.md"]','["kubernetes-backup-migrations.md"]','{}','{}'); -INSERT INTO "resources" VALUES('https://skillbuilder.aws','explore.skillbuilder.aws/learn: AWS Skill Builder 🌟','','2023',0,'The official AWS digital learning portal offering over 600 free and paid cloud training courses. Provides comprehensive, hands-on labs, game-based learning (Cloud Quest), and official certification exam preparation tracks maintained directly by AWS engineering teams.','English','Platform','Intermediate',0,'online','manual',NULL,NULL,NULL,0,'2023-06-01T00:00:00+02:00',NULL,NULL,NULL,'["Cloud Computing", "AWS", "Official Training"]','["[COMMUNITY-TOOL]"]','[]','["aws-training.md", "aws.md"]','{}','{}'); +INSERT INTO "resources" VALUES('https://skillbuilder.aws','explore.skillbuilder.aws/learn: AWS Skill Builder 🌟','','2023',0,'The official AWS digital learning portal offering over 600 free and paid cloud training courses. Provides comprehensive, hands-on labs, game-based learning (Cloud Quest), and official certification exam preparation tracks maintained directly by AWS engineering teams.','English','Platform','Intermediate',0,'duplicate','manual',NULL,NULL,NULL,0,'2023-06-01T00:00:00+02:00',NULL,NULL,NULL,'["Cloud Computing", "AWS", "Official Training"]','["[COMMUNITY-TOOL]"]','[]','["aws-training.md", "aws.md"]','{}','{"duplicate_of": "https://skillbuilder.aws/"}'); 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 - IntroducciΓ³n a AWS Data Pipeline (EspaΓ±ol LatinoamΓ©rica) | 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"}'); diff --git a/data/inventory.yaml b/data/inventory.yaml index d48937ce..caa1ca87 100644 --- a/data/inventory.yaml +++ b/data/inventory.yaml @@ -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: '' diff --git a/data/news_digest.json b/data/news_digest.json index a5c93172..be92e97a 100644 --- a/data/news_digest.json +++ b/data/news_digest.json @@ -651,7 +651,7 @@ "date": "2026-06-01", "stars": 5, "impact": "critical", - "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" }, { @@ -660,16 +660,7 @@ "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.", "category": "Certification & Training" }, { @@ -687,16 +678,7 @@ "date": "2026-06-01", "stars": 4, "impact": "high", - "why": "Offers direct cloud-based sandbox environments and practice simulations for key CNCF certifications like CKA, CKAD, and CKS.", - "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 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.", "category": "Certification & Training" }, { @@ -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" + }, + { + "url": "https://techstudyslack.com", + "title": "techstudyslack.com", + "date": "2026-06-01", + "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" }, { @@ -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", - "date": "2026-06-08", - "stars": 5, - "impact": "high", - "why": "Argilla addresses the critical LLM challenge of data curation and continuous human-in-the-loop alignment.", - "category": "MLOps & Data Science" - }, - { - "url": "https://engineering.fb.com/2026/05/26/ml-applications/silvertorch-index-as-model-new-retrieval-paradigm-recommendation-systems", - "title": "SilverTorch: Index as Model β€” A New Retrieval Paradigm for Recommendation Systems", - "date": "2026-06-02", - "stars": 4, - "impact": "high", - "why": "SilverTorch redefines recommendation engine architectures by unifying retrieval and scoring into a single GPU-optimized model.", + "why": "Meta's official optimization and fine-tuning repository that sets the standard for deploying large language models efficiently in production.", "category": "MLOps & Data Science" }, { @@ -1073,7 +1055,7 @@ "date": "2026-06-18", "stars": 4, "impact": "high", - "why": "This manual serves as an indispensable reference mapping the complex landscape of running machine learning workloads on Kubernetes.", + "why": "An invaluable reference mapping out the tools, configurations, and architectures required to run machine learning workloads on Kubernetes.", "category": "MLOps & Data Science" }, { @@ -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", + "title": "SilverTorch: Index as Model β€” A New Retrieval Paradigm for Recommendation Systems", + "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", "stars": 4, "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", - "date": "2026-06-18", - "stars": 5, - "impact": "high", - "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 β€” 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.", - "category": "MLOps & Data Science" - }, - { - "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", - "entry_count": 442, + "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", - "entry_count": 53, + "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" } } \ No newline at end of file diff --git a/v2-docs/index.md b/v2-docs/index.md index 8bf5dc29..19556b7f 100644 --- a/v2-docs/index.md +++ b/v2-docs/index.md @@ -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. diff --git a/v2-docs/tech-digest.md b/v2-docs/tech-digest.md index f828a5d9..b683a6ad 100644 --- a/v2-docs/tech-digest.md +++ b/v2-docs/tech-digest.md @@ -302,46 +302,46 @@ search: | Date | Resource | Impact | Why It Matters | | :--- | :--- | :---: | :--- | - | 2026-06-01 | [Ray](https://docs.ray.io/en/latest) | πŸ”΄ 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) | πŸ”΄ 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 β€” 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) | πŸ”΅ 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) | πŸ”΄ 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) | πŸ”΄ 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 β€” 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) | πŸ”΅ 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) | πŸ”΄ 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) | πŸ”΄ 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) | πŸ”΄ 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) | πŸ”΅ 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) | πŸ”΅ 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) | πŸ”΄ 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) | πŸ”΄ 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 β€” 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) | πŸ”΅ 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) | πŸ”΅ 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) | πŸ”΅ 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) | πŸ”΄ 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) | πŸ”΄ 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) | πŸ”΄ 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 β€” 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) | πŸ”΅ 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) | πŸ”΄ 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) | πŸ”΄ 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) | πŸ”΄ 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 β€” 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) | πŸ”΅ 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) | πŸ”΅ 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) | πŸ”΄ 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) | πŸ”΄ 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) | πŸ”΄ 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) | πŸ”΅ 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) | πŸ”΅ 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) | πŸ”΄ 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) | πŸ”΄ 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) | πŸ”΅ 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) | πŸ”΄ 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) | πŸ”΅ 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) | πŸ”΄ 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) | πŸ”΄ 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) | πŸ”΄ 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) | πŸ”΄ 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) | πŸ”΄ 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) | πŸ”΅ 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) | πŸ”΄ 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) | πŸ”΄ 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) | πŸ”΅ 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) | πŸ”΅ medium | It teaches modern daemonless and rootless container architectures using Podman and Buildah, keeping developers aligned with secure enterprise container runtimes. | ## AWS