Best of Kubernetes — October 2025

  1. 1
    Video
    Avatar of codeheadCodeHead·28w

    Should YOU Become A Devops Engineer

    DevOps engineering combines development and operations to automate software delivery through CI/CD pipelines, containerization, and infrastructure management. The role requires skills in Linux, scripting, cloud platforms, and tools like Docker, Kubernetes, and Terraform. DevOps engineers earn competitive salaries (up to $190,000+) due to specialized expertise, but the work focuses on infrastructure, automation, and system stability rather than product development. Success requires enjoying problem-solving, automation, and behind-the-scenes technical work.

  2. 2
    Article
    Avatar of infoworldInfoWorld·25w

    What’s the Go language really good for?

    Go has evolved from a curiosity to a battle-tested language powering major cloud-native projects like Docker and Kubernetes. Known for its simplicity, fast compilation, and built-in concurrency features (goroutines and channels), Go excels at building distributed network services, cloud applications, and standalone tools. While it offers automatic memory management and cross-platform portability, it deliberately omits features like macros and produces larger binaries. The language recently added generics in version 1.18 after years of deliberation. Go's future remains strong in cloud infrastructure and network services, with emerging interest in AI workloads, though it faces competition from Python in ML/AI and Rust in systems programming.

  3. 3
    Article
    Avatar of bytebytegoByteByteGo·29w

    How Airbnb Runs Distributed Databases on Kubernetes at Scale

    Airbnb deployed distributed SQL databases across multiple Kubernetes clusters, each mapped to a different AWS Availability Zone, to achieve high availability and fault tolerance. They built custom Kubernetes operators to safely manage stateful workloads, coordinate node replacements, and maintain quorum during failures. Using AWS EBS for persistent storage, PVCs for volume management, and techniques like replica reads and stale reads, they mitigated latency issues while maintaining consistency. Their largest production cluster handles 3 million queries per second across 150 nodes with 300TB of data, achieving 99.95% availability through careful sequencing of upgrades, canary deployments, and overprovisioning for resilience.

  4. 4
    Article
    Avatar of bytebytegoByteByteGo·28w

    How OpenAI Uses Kubernetes And Apache Kafka for GenAI

    OpenAI built a stream processing platform using Apache Flink (PyFlink) on Kubernetes to handle real-time data for AI model training and experimentation. The architecture addresses three key challenges: providing Python-first APIs for ML practitioners, handling cloud capacity constraints, and managing multi-primary Kafka clusters. The system features a control plane for multi-cluster failover, per-namespace isolation in Kubernetes, watchdog services for Kafka topology monitoring, and decoupled state management using RocksDB with highly available blob storage. Custom Kafka connectors enable reading from multiple primary clusters simultaneously while maintaining resilience during outages.

  5. 5
    Article
    Avatar of growwenggGroww Engineering·27w

    A Framework for Cloud Cost Optimization: How We Saved 40% of our Cloud cost

    Groww Engineering reduced their cloud costs by 40% over three months through a systematic framework combining visibility, ownership, and architectural changes. They built an internal FinOps dashboard for granular cost tracking, standardized resource labeling across teams, shifted from fixed to elastic infrastructure, deprecated legacy services, migrated analytics to an in-house query engine, and established continuous optimization practices with team-level budgets and regular audits.

  6. 6
    Article
    Avatar of buildkiteBuildkite·25w

    Kubernetes with Buildkite: faster, simpler, and ready for scale

    Buildkite has updated its Kubernetes Agent Stack with simplified installation requiring only a single agent token instead of multiple configuration parameters, improved scaling to handle tens of thousands of concurrent jobs with 80% smaller Kubernetes objects, better error surfacing with full YAML specs and stack-level failure signals, out-of-the-box Prometheus integration for instant observability dashboards, and expanded Helm configuration options. Future improvements include custom scheduling policies, more granular job states, and fine-grained job configuration controls.

  7. 7
    Article
    Avatar of hnHacker News·28w

    Why Self-host?

    Explores the motivations for self-hosting personal services, focusing on privacy and digital sovereignty. Discusses how calendar, contact, and location data reveal sensitive information about users, and argues against relying on big tech companies. Provides practical recommendations for self-hosting calendar/contact servers (Baïkal), email (Stalwart, Mailcow), smart home automation (Home Assistant), RSS aggregators (FreshRSS), and location tracking (dawarich). Shares a personal journey from single server to a 3-node Kubernetes cluster setup.

  8. 8
    Article
    Avatar of metalbearMetalBear·25w

    Introducing DB Branching in mirrord: Run Against a Shared Environment With a Personal, Isolated Database

    mirrord introduces DB Branching, a feature that creates temporary, isolated database branches for testing schema changes and migrations safely. When enabled, it automatically overrides database connection strings to point to a separate branch that mirrors the main database, allowing developers to test changes without affecting shared staging environments. The feature currently supports MySQL databases and is available in mirrord for Teams, with a step-by-step guide demonstrating how to test schema changes using a Go service on Kubernetes.

  9. 9
    Article
    Avatar of hnHacker News·28w

    Leveling Up My Homelab

    A detailed account of rebuilding a personal homelab from a basic setup with limited compute and manual configuration into a production-grade Kubernetes cluster. The new infrastructure features 8 worker nodes, Talos Linux with PXE boot, GitOps via Argo CD, 10G networking, and plans for GPU workloads and multi-site clustering. The rebuild addresses previous limitations around orchestration, disaster recovery, scalability, and remote access while enabling serious experimentation with modern cloud-native technologies.

  10. 10
    Video
    Avatar of techworldwithnanaTechWorld with Nana·25w

    From QA to DevOps - How I Learned DevOps to future-proof my career

    A senior test automation engineer shares his transition into DevOps to future-proof his career. He explains how traditional QA roles are evolving to require infrastructure skills like CI/CD, Docker, and Kubernetes. Through structured learning and hands-on projects, he successfully combined test automation expertise with DevOps knowledge, leading to freelance opportunities at higher rates. The discussion covers practical learning strategies, the importance of understanding tool integration over isolated skills, and why QA professionals need to adapt as AI automates basic testing tasks.

  11. 11
    Article
    Avatar of medium_jsMedium·25w

    Building a Kubernetes Platform — Think Big, Think in Planes

    Introduces a mental model for building Internal Developer Platforms by thinking in horizontal 'planes' rather than vertical layers. Explains five key planes (Developer, Integration/Delivery, Monitoring/Logging, Security, and Resource) and provides deep dives into Control, Observability, and Service planes. Uses OpenChoreo as a case study to demonstrate how this architecture enables scalable, secure-by-default platforms that centralize control while distributing scale across multiple Kubernetes clusters.

  12. 12
    Article
    Avatar of devtronDevtron·27w

    Simplifying the Kubernetes CI/CD Pipeline

    Devtron simplifies Kubernetes CI/CD pipeline setup by providing an intuitive UI that abstracts complex YAML configurations. The platform offers Kubernetes-native builds running in pods, GitOps integration, multiple deployment strategies (rolling, blue-green, canary), and unified observability. It includes pre-built templates, multi-cluster support, security scanning, and cost management features. The guide walks through installing Devtron and creating a complete CI/CD workflow from repository connection to deployment, demonstrating how platform teams can manage builds, deployments, and operations from a single dashboard without extensive Kubernetes expertise.

  13. 13
    Article
    Avatar of rhdevRed Hat Developer·27w

    Node.js 20+ memory management in containers

    Node.js 20+ automatically adjusts heap size based on container memory limits through cgroup awareness. By default, heap size is 50% of container memory up to 4 Gi, maxing out at 2 GB. The --max-old-space-size flag can override these defaults. The article explains V8 garbage collection behavior, troubleshooting memory leaks, and deployment considerations for OpenShift/Kubernetes environments. Key insight: simply increasing heap size won't fix underlying memory leaks, as OutOfMemory exceptions will eventually occur regardless.

  14. 14
    Article
    Avatar of giantswarmGiant Swarm·25w

    The Gateway API shift: how Kubernetes networking actually works at scale

    Gateway API is replacing Kubernetes Ingress as the standard for traffic management at scale. Unlike Ingress, which relies on controller-specific annotations and lacks proper role separation, Gateway API provides a structured model with GatewayClass, Gateway, and Route resources that enable platform teams to manage infrastructure while application teams control routing rules. It supports advanced features like GRPC routing, service mesh integration through GAMMA, and safe cross-namespace delegation via ReferenceGrant. The API includes conformance testing for portability across controllers and vendors, making it suitable for multi-cluster, multi-team enterprise environments where consistent, scalable networking is critical.

  15. 15
    Article
    Avatar of faunFaun·26w

    My Kubestronaut journey

    A developer shares their experience completing all five CNCF Kubernetes certifications (KCNA, CKA, KCSA, CKAD, and CKS) over three months to become a Kubestronaut. The post details exam scores, preparation strategies, study resources used, and technical challenges encountered during the certification process, particularly with the PSI Secure Browser on Mac. Includes a GitHub repository with study notes, course recommendations, and practical tips for each certification exam.

  16. 16
    Article
    Avatar of arangoArangoDB·27w

    ArangoDB: Multi-Model Database for Your Modern Apps

    ArangoDB is a multi-model database that combines graph, document, key-value, and search capabilities in a single system with a unified query language (AQL). It offers flexible deployment options including fully-managed cloud service (ArangoGraph), on-premises, and Kubernetes support across major cloud platforms. The database provides native client libraries for multiple programming languages and emphasizes database consolidation by replacing multiple specialized databases with one unified solution.

  17. 17
    Article
    Avatar of do_communityDigitalOcean Community·27w

    Manage Multi-Cluster Deployments with ArgoCD

    ArgoCD ApplicationSets automate Kubernetes deployments across multiple clusters using a declarative GitOps approach. The guide demonstrates how to set up ArgoCD, configure ApplicationSets with generators for multi-cluster management, and reduce deployment times by 83% while ensuring consistency. It covers installation, cluster registration, ApplicationSet configuration with parameter substitution, troubleshooting common issues, and explains how generators create parameter sets that render into individual ArgoCD Applications for each target cluster.

  18. 18
    Article
    Avatar of istioIstio·27w

    Announcing Istio 1.26.5

    Istio 1.26.5 is a patch release that includes several bug fixes and improvements. Key changes include enhanced TLS secret access controls for Kubernetes Gateway API gateways, configurable pod-to-proxy association behavior, fixes for waypoint configuration and ServiceEntry resolution in ztunnel, and removal of the installation dependency between pilot and CNI components.

  19. 19
    Article
    Avatar of freecodecampfreeCodeCamp·25w

    Serverless and Microservices with C# & Azure

    A comprehensive 2-hour video course covering serverless architecture and microservices development using C# and Azure. The course progresses from fundamental concepts to production-ready implementations, including Azure Functions, Docker containers, Kubernetes orchestration, and .NET Aspire. Topics include serverless architecture patterns, microservices design patterns, onion architecture, Azure triggers, background functions, IoT functions, and practical route planning microservices.

  20. 20
    Article
    Avatar of bytebytegoByteByteGo·26w

    EP185: Docker vs Kubernetes

    Docker packages applications with dependencies into containers that run on a single machine, while Kubernetes orchestrates containers across multiple machines for scalability and resilience. Docker uses a simple workflow from Dockerfile to container runtime, whereas Kubernetes adds master nodes, worker nodes, and Pods for distributed, self-healing deployments. Additional topics covered include batch versus stream processing, modular monoliths as an architectural pattern combining monolith simplicity with microservices flexibility, process versus thread differences, and how AI agents chain reasoning, tools, and memory.

See all Kubernetes archives