Best of Kubernetes — June 2025

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   Javarevisited·46w

   How I Finally Understood Docker and Kubernetes

   A developer shares their journey from confusion to understanding Docker and Kubernetes by focusing on practical problems rather than technical jargon. Docker is explained as a way to package applications with their dependencies into portable containers, while Kubernetes is presented as a system for managing multiple containers in coordination. The author emphasizes learning through hands-on experience with simple projects, starting with single containers and gradually building up to multi-container systems with deployments and services.

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   ByteByteGo·45w

   Shopify Tech Stack

   Shopify processes massive scale with 173 billion requests on Black Friday using a tech stack built on Ruby on Rails, React, MySQL, and Kafka. The platform uses a modular monolith architecture with strict component boundaries, database sharding through isolated pods, and extensive tooling investments including YJIT compiler and Sorbet type checker. The infrastructure handles 284 million requests per minute at peak, 66 million Kafka messages per second, and processes 216 million ML embeddings daily for semantic search, all while maintaining developer productivity through comprehensive CI/CD pipelines and observability tools.

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   Article

   Devtron·45w

   CI/CD Best Practices for Microservice Architecture

   Traditional CI/CD pipelines fail to scale with microservices architecture. Each microservice requires isolated pipelines with independent versioning, progressive deployment strategies like canary and blue/green deployments, proper access controls, and comprehensive observability. Key principles include service-level pipeline isolation, semantic versioning, GitOps workflows, role-based access control, standardized templates, security scanning, and tracking DORA metrics. Platforms like Devtron help teams achieve 40% MTTR reduction, 3x deployment frequency increase, and faster service onboarding through Kubernetes-native CI/CD automation.

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   Article

   ByteByteGo·42w

   EP169: RAG vs Agentic RAG

   RAG (Retrieval Augmented Generation) combines information retrieval with large language models, but traditional RAG has limitations in adaptability and real-time processing. Agentic RAG introduces AI agents that make decisions, select tools, and refine queries for more accurate responses. The comparison covers Kubernetes fundamentals including control planes, nodes, and key resources like Pods and Deployments. Six space-efficient data structures are highlighted: Bloom Filter, HyperLogLog, Cuckoo Filter, Minhash, SkipList, and Count-Min Sketch. Database normalization forms from 1NF to 4NF are explained for eliminating redundancy and enforcing data integrity.

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   Article

   System Design Codex·43w

   Kubernetes Scaling Strategies

   Kubernetes offers three main scaling strategies for containerized applications: Horizontal Pod Autoscaling (HPA) increases or decreases pod replicas based on resource usage like CPU and memory; Vertical Pod Autoscaling (VPA) adjusts individual pod resource limits and requests; and Cluster Autoscaling manages the number of worker nodes in the cluster. HPA works best for stateless applications, VPA suits workloads with variable resource needs, and Cluster Autoscaler ensures infrastructure scales with demand. Each strategy addresses different scaling needs and can be combined for comprehensive auto-scaling solutions.

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   Article

   KodeKloud's Squad·46w

   CI/CD: GitOps vs DevOPs Approach

   GitOps represents an evolution in CI/CD practices that centralizes Git as the single source of truth for both infrastructure and application configurations. Unlike traditional DevOps approaches, GitOps uses declarative, version-controlled infrastructure that automatically syncs with clusters, eliminating manual kubectl commands. This approach provides better auditability, reproducibility, and safety by making Git merges equivalent to deployments, while reducing human error and increasing automation visibility.

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   Article

   Nordic APIs·45w

   Top 10 API Gateways in 2025

   A comprehensive comparison of 10 leading API gateways in 2025, including Kong Gateway, Zuplo, Tyk, Gravitee, MuleSoft, Axway, Sensedia, Azure APIM, WSO2, and IBM API Connect. Each solution is evaluated based on core features, use cases, and target audiences, with considerations for deployment models, protocol requirements, ecosystem integration, and compliance needs. The guide emphasizes that API gateways have evolved beyond simple routing to become control planes for security, observability, and developer experience.

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   Article

   Machine Learning Mastery·46w

   10 MLOps Tools for Machine Learning Practitioners to Know

   MLOps combines machine learning with DevOps practices to streamline model lifecycle management from training to deployment. Ten essential tools are highlighted: MLflow for experiment tracking, Weights & Biases for visualization, Comet for monitoring, Airflow for workflow automation, Kubeflow for Kubernetes-based pipelines, DVC for data versioning, Metaflow for Python workflows, Pachyderm for data pipelines, Evidently AI for model monitoring, and TensorFlow Extended for complete ML pipelines. These tools address different aspects of MLOps including experiment tracking, workflow automation, data versioning, and model monitoring to help teams build reliable, production-ready machine learning systems.

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   Article

   freeCodeCamp·46w

   From Commit to Production: Hands-On GitOps Promotion with GitHub Actions, Argo CD, Helm, and Kargo

   A comprehensive guide to building a production-ready CI/CD pipeline using GitOps principles with GitHub Actions, ArgoCD, Helm, and Kargo. The tutorial demonstrates how to structure repositories for microservices, implement automated environment promotions, and manage multi-stage deployments using the Craftista e-commerce application as a real-world example. It covers semantic versioning, polyrepo architecture, and automated promotion workflows from development through production environments.

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    Article

    freeCodeCamp·43w

    Kubernetes Networking Tutorial: A Guide for Developers

    Kubernetes networking enables containerized workloads to communicate through a flat network model where each pod gets a unique IP address without NAT. The tutorial covers core concepts including CNI plugins (Flannel, Calico, Cilium), kube-proxy for service load balancing, CoreDNS for service discovery, and network policies for security. It explains pod-to-pod, pod-to-service, and external-to-service communication patterns, along with practical troubleshooting techniques for common networking issues like unreachable pods and services.

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    Article

    Community Picks·44w

    Self-host and scale web apps without Kubernetes complexity

    Uncloud offers a simplified alternative to Kubernetes for deploying and scaling containerized applications. It enables developers to take Docker Compose apps to production with features like zero-downtime deployments, automatic HTTPS, and cross-machine scaling using simple command-line operations. The platform focuses on reducing complexity while maintaining reliability for self-hosted applications.

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    Video

    TechWorld with Nana·45w

    Complete Cloud Engineer Roadmap | From Beginner to Advanced

    A comprehensive roadmap for becoming a cloud engineer, starting with foundational skills like Linux, networking, and programming basics. The guide progresses through cloud concepts, core services (compute, storage, networking), infrastructure as code with Terraform, containerization with Docker and Kubernetes, CI/CD pipelines, monitoring and observability, and security best practices. Emphasizes hands-on learning through progressive projects, from deploying static websites to building complete automated deployment pipelines with proper monitoring and security controls.

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    Video

    TechWorld with Nana·43w

    I Analyzed 100+ DevOps Job Posts from 6 Different Countries | Skills Companies ACTUALLY Want

    Analysis of 100+ DevOps job postings across 6 countries reveals consistent skill requirements: CI/CD pipelines are fundamental, cloud platforms (AWS/Azure/GCP) are essential, Docker and Kubernetes are standard, and scripting languages (Python/Bash) are required. Junior positions need basic familiarity while senior roles demand deep expertise in automation tools like Terraform and Ansible. Security knowledge becomes crucial at senior levels. The research shows DevOps skills are globally transferable with significant salary differences between junior and senior positions.

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    Article

    Medium·42w

    Hello, I am a DevOps Engineer and I Broke Production Today.

    A DevOps engineer shares personal stories of production failures, including DNS migration issues, database credential mix-ups, and Kubernetes scheduling problems. The post emphasizes that failures are valuable learning experiences that build expertise and resilience. It advocates for implementing proper logging, monitoring, testing environments, and post-mortem processes to handle incidents effectively. The author argues that experienced engineers are defined not by avoiding mistakes, but by learning from them and building antifragile systems.

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    Article

    Spacelift·46w

    20+ Top Most Popular DevOps Platforms in 2025

    A comprehensive overview of 20+ popular DevOps platforms in 2025, including GitLab, GitHub, AWS, Kubernetes, Jenkins, and specialized tools like Spacelift for infrastructure orchestration. The guide covers key features, pricing, and use cases for each platform, helping teams choose between all-in-one solutions versus specialized tools for different DevOps lifecycle stages like CI/CD, infrastructure management, monitoring, and deployment automation.

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    Article

    SitePoint·43w

    ArgoCD: A Practical Guide to GitOps on Kubernetes — SitePoint

    ArgoCD is a declarative GitOps continuous delivery tool for Kubernetes that uses Git repositories as the single source of truth for application deployments. Unlike traditional push-based CI/CD systems, ArgoCD runs inside the cluster and pulls changes from Git, making it more secure by not exposing cluster credentials. The tool consists of three main components: API Server, Repository Server, and Application Controller, which work together to monitor applications and maintain desired state. Major enterprises like LoveHolidays and CVTE have successfully adopted ArgoCD to handle massive-scale deployments, with LoveHolidays managing over 1500 production deployments monthly. The guide includes a practical demonstration showing how to set up ArgoCD on a minikube cluster and configure automatic syncing of application changes from Git repositories.

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    Article

    KodeKloud's Squad·44w

    Periodic Table of Cloud & DevOps Tools

    A comprehensive visual guide showcasing 80+ DevOps and cloud tools organized across 12 domains, highlighting how the DevOps landscape has evolved beyond traditional tools like Jenkins and Docker. The guide emphasizes modern practices including GitOps workflows, built-in security, platform engineering, comprehensive observability, and cloud-native architectures. Rather than mastering all tools, the recommendation is to understand one tool per category and its role in the broader ecosystem.

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    Netguru·44w

    What is Golang: Why Top Tech Companies Choose Go in 2025

    Go programming language has gained significant adoption among major tech companies due to its simplicity, efficient concurrency model through goroutines, and fast compilation to native code. Originally created by Google to solve build time and complexity issues with C++ and Java, Go emphasizes composition over inheritance and provides built-in concurrency primitives. The language powers critical infrastructure tools like Kubernetes, Docker, and Terraform, while offering excellent performance with low memory footprint and fast startup times. Companies value Go for its ease of developer onboarding, reduced operational overhead through static binaries, and comprehensive built-in tooling. With recent additions like generics and a growing ecosystem, Go continues to be the preferred choice for cloud-native applications, microservices, and high-concurrency systems.

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    Grafana Labs·44w

    Configure and customize Kubernetes Monitoring easier with Alloy Operator

    Grafana Labs introduces version 3.0 of the Kubernetes Monitoring Helm chart featuring Alloy Operator, which simplifies configuration by dynamically setting up telemetry data collection based on selected features. The new approach reduces the massive values.yaml file from nearly 3,000 lines and eliminates complex subchart management. Key improvements include automatic configuration of Alloy collectors when features are enabled, built-in tail sampling support for distributed tracing, and dynamic deployment of required Alloy instances. The operator uses Helm-based architecture to manage Alloy objects while maintaining security through proper encapsulation and minimal permissions.

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    Hacker News·44w

    psviderski/unregistry: Push docker images directly to remote servers without an external registry

    Unregistry is a lightweight container registry that enables direct Docker image transfers to remote servers over SSH without requiring external registries. The tool includes a 'docker pussh' command that transfers only missing image layers, making deployments faster and more efficient. It eliminates the need for Docker Hub subscriptions, self-hosted registries, or inefficient save/load operations by establishing SSH tunnels and using temporary registry containers for direct image transfers.

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    ITNEXT·44w

    How We Load Test Argo CD at Scale: 1,000 vClusters with GitOps on Kubernetes

    A comprehensive load testing experiment demonstrates how Argo CD performs at scale with up to 1,000 virtual clusters using vCluster technology. The test reveals practical scaling limits: Argo CD handles around 500 applications and 50-60 clusters before requiring significant tuning. Key findings include memory pressure on Application Controllers around 100 vClusters, the need for resource limit adjustments, and architectural considerations for multi-tenant GitOps platforms. The experiment used over €20,000 worth of infrastructure on STACKIT and provides detailed insights into component-specific bottlenecks, optimization strategies, and alternative approaches like Kargo for enterprise-scale deployments.

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    Awesome Go·45w

    Learning Go Interface Encapsulation from K8s

    Explores Go interface encapsulation techniques learned from Kubernetes codebase, covering how to hide implementation details, enable easier mock testing, support multiple implementations, and encapsulate common patterns like exception handling and WaitGroup usage. Demonstrates practical examples including the SyncHandler interface pattern, mock testing strategies with gomonkey, and utility wrappers for goroutine management.

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    ByteByteGo·45w

    How Lyft Uses ML to Make 100 Million Predictions A Day

    Lyft processes 100 million ML predictions daily through their LyftLearn Serving platform, which addresses both data plane performance and control plane complexity. The system uses isolated microservices where each team owns their repository, deployment pipeline, and runtime environment. Key components include an HTTP serving layer with Flask/Gunicorn, a core serving library handling model lifecycle, custom ML code injection points, and integration with Kubernetes/Envoy infrastructure. The platform features automated config generation, built-in model self-testing, and supports any Python-compatible ML framework while maintaining strict isolation between teams.

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    Article

    Devtron·43w

    Multi-Environment CI/CD Across Clusters Made Easy

    Multi-environment CI/CD across clusters is essential for reliable software delivery but introduces complexity around environment drift, manual promotions, and visibility gaps. Devtron simplifies this with GitOps-first workflows, visual pipelines, and environment-specific access controls. The platform supports deployment strategies like blue-green and canary deployments, includes built-in security scanning and approval gates, and provides centralized observability across Dev, Staging, Production, and DR environments. A real-world case study shows how one company managed 2500+ services across 15+ clusters, reducing deployment time by 60% while eliminating scripting overhead.

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    Community Picks·43w

    10+ Most Powerful GitHub Repos I Discovered in 2025 (You’ll Wish You Knew Sooner)

    A curated list of 11 powerful GitHub repositories discovered in 2025, featuring tools for AI-powered development, infrastructure management, and developer productivity. Highlights include Forge for AI-assisted terminal coding, Terraform for infrastructure as code, Kubernetes for container orchestration, monitoring tools like Prometheus, and modern development platforms like Turborepo and Hoppscotch. Each tool is presented with practical use cases and enterprise adoption examples.

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