{"id":13730,"date":"2026-01-07T10:10:43","date_gmt":"2026-01-07T04:40:43","guid":{"rendered":"https:\/\/www.youstable.com\/blog\/?p=13730"},"modified":"2026-01-07T10:11:00","modified_gmt":"2026-01-07T04:41:00","slug":"how-to-optimize-kubernetes-on-linux-server","status":"publish","type":"post","link":"https:\/\/www.youstable.com\/blog\/how-to-optimize-kubernetes-on-linux-server","title":{"rendered":"How to Optimize Kubernetes on Linux Server &#8211; Easy Guide"},"content":{"rendered":"\n<p><strong>To optimize Kubernetes on a Linux server,<\/strong> tune the OS (sysctl, cgroups, swap), use a modern container runtime (containerd\/CRI-O), configure kubelet (reservations, eviction, CPU\/Topology Managers), pick a fast CNI (Cilium\/Calico) and storage, right-size requests\/limits, optimize etcd, and measure with SLO-driven monitoring. Steps and examples below.<\/p>\n\n\n\n<p>Running Kubernetes is easy; running it fast and reliably on a Linux server requires deliberate tuning. In this guide, I\u2019ll show you how to optimize Kubernetes on Linux servers with practical, production-tested steps you can apply today\u2014covering kernel tuning, kubelet configuration, networking, storage, scheduling, and autoscaling.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"search-intent-and-what-youll-learn\"><strong>Search Intent and What You\u2019ll Learn<\/strong><\/h2>\n\n\n\n<p>This tutorial is for platform engineers, DevOps, and sysadmins seeking hands-on Kubernetes performance tuning on Linux. You\u2019ll get a prioritized checklist, rationale behind each change, and copy-paste configurations. We\u2019ll keep language beginner-friendly, but the techniques reflect real-world production experience.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"prerequisites-and-baseline-checks\"><strong>Prerequisites and Baseline Checks<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Linux kernel 5.4+ <\/strong>(newer kernels offer better cgroups, BPF, and networking performance).<\/li>\n\n\n\n<li>cgroups v1 or v2 supported by your K8s version and runtime (v2 is fully supported in modern Kubernetes\/containerd).<\/li>\n\n\n\n<li>SSD\/NVMe for etcd and container storage; XFS or ext4 formatted correctly for overlayfs.<\/li>\n\n\n\n<li>Swap disabled (unless you explicitly configure NodeSwap and understand the trade-offs).<\/li>\n\n\n\n<li>Time synced via chrony\/systemd-timesyncd and entropy available (rngd) for TLS-heavy clusters.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"optimize-the-linux-os-for-kubernetes\"><strong>Optimize the Linux OS for Kubernetes<\/strong><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"recommended-sysctl-tuning\"><strong>Recommended sysctl tuning<\/strong><\/h3>\n\n\n\n<p>These sysctl settings improve connection tracking, networking throughput, and resource limits. Adjust to your workload scale; test before global rollout.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># \/etc\/sysctl.d\/99-kubernetes-tuning.conf\n# Required for most CNIs using bridges\nnet.bridge.bridge-nf-call-iptables=1\nnet.bridge.bridge-nf-call-ip6tables=1\n\n# Increase conntrack table size for high connection churn\nnet.netfilter.nf_conntrack_max=262144\nnet.netfilter.nf_conntrack_buckets=65536\n\n# Socket buffers and backlog\nnet.core.rmem_max=134217728\nnet.core.wmem_max=134217728\nnet.core.somaxconn=4096\nnet.ipv4.tcp_max_syn_backlog=4096\n\n# Ephemeral port range for bursty traffic\nnet.ipv4.ip_local_port_range=1024 65000\n\n# ARP\/Neighbor cache thresholds (large node counts)\nnet.ipv4.neigh.default.gc_thresh1=4096\nnet.ipv4.neigh.default.gc_thresh2=8192\nnet.ipv4.neigh.default.gc_thresh3=16384\n\n# File watchers (fixes issues with dev tools\/controllers)\nfs.inotify.max_user_watches=1048576\nfs.inotify.max_user_instances=1024\n<\/code><\/pre>\n\n\n\n<pre class=\"wp-block-code\"><code># Apply immediately\nsudo modprobe br_netfilter\nsudo sysctl --system\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"disable-swap-and-align-cgroups-systemd\"><strong>Disable swap and align cgroups\/systemd<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Disable <a href=\"https:\/\/www.youstable.com\/blog\/swap-memory-in-linux\/\">swap to avoid unpredictable memory<\/a> reclaim: sudo swapoff -a &amp;&amp; sed -i &#8216;\/ swap \/ s\/^\/#\/&#8217; \/etc\/fstab.<\/li>\n\n\n\n<li>Use systemd as the cgroup driver for kubelet and container runtime to prevent resource accounting drift.<\/li>\n<\/ul>\n\n\n\n<pre class=\"wp-block-code\"><code># Verify cgroup driver alignment\n# containerd: SystemdCgroup = true (see next section)\n# kubelet: KubeletConfiguration cgroupDriver: \"systemd\"\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"filesystem-and-container-storage\"><strong>Filesystem and container storage<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Use XFS with <code>ftype=1<\/code> or ext4 with d_type support for overlayfs.<\/li>\n\n\n\n<li>Prefer NVMe\/SSD for container and etcd storage; mount with <code>noatime<\/code>.<\/li>\n\n\n\n<li>Enable image garbage collection thresholds in kubelet to prevent disk pressure.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"choose-and-tune-the-container-runtime\"><strong>Choose and Tune the Container Runtime<\/strong><\/h2>\n\n\n\n<p>containerd and CRI-O are the fastest options for Kubernetes. Docker works via dockershim-replacements but adds an extra layer. For most clusters, containerd balances performance, features, and ecosystem support.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"containerd-optimal-settings\"><strong>containerd optimal settings<\/strong><\/h3>\n\n\n\n<pre class=\"wp-block-code\"><code># \/etc\/containerd\/config.toml (key excerpts)\n&#91;plugins.\"io.containerd.grpc.v1.cri\".containerd.runtimes.runc.options]\n  SystemdCgroup = true\n\n&#91;plugins.\"io.containerd.grpc.v1.cri\"]\n  sandbox_image = \"registry.k8s.io\/pause:3.9\"\n\n&#91;plugins.\"io.containerd.grpc.v1.cri\".registry]\n  # Optional: private mirror\/cache to speed image pulls\n  &#91;plugins.\"io.containerd.grpc.v1.cri\".registry.mirrors.\"your-mirror.local\"]\n    endpoint = &#91;\"https:\/\/your-mirror.local\"]\n<\/code><\/pre>\n\n\n\n<p>Restart containerd after changes and pre-pull base images for latency-sensitive deployments.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"kubelet-and-node-level-configuration\"><strong>Kubelet and Node-Level Configuration<\/strong><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"kubeletconfiguration-best-practices\"><strong>KubeletConfiguration best practices<\/strong><\/h3>\n\n\n\n<pre class=\"wp-block-code\"><code># \/var\/lib\/kubelet\/config.yaml (key excerpts)\napiVersion: kubelet.config.k8s.io\/v1beta1\nkind: KubeletConfiguration\ncgroupDriver: systemd\nevictionHard:\n  \"memory.available\": \"200Mi\"\n  \"nodefs.available\": \"10%\"\n  \"imagefs.available\": \"10%\"\nkubeReserved:\n  cpu: \"500m\"\n  memory: \"1Gi\"\n  ephemeral-storage: \"2Gi\"\nsystemReserved:\n  cpu: \"250m\"\n  memory: \"512Mi\"\n  ephemeral-storage: \"1Gi\"\nimageGCHighThresholdPercent: 80\nimageGCLowThresholdPercent: 60\nmaxPods: 110\ncpuManagerPolicy: \"static\"           # For CPU pinning of Guaranteed pods\ntopologyManagerPolicy: \"restricted\"  # Align CPU\/memory\/PCIe on NUMA nodes\n<\/code><\/pre>\n\n\n\n<p>Use <strong>Guaranteed<\/strong> QoS for latency-critical apps: set CPU and memory <em>requests = limits<\/em>. For general workloads, set realistic requests and avoid very low CPU limits to reduce throttling.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"networking-performance-cni-kube-proxy-and-mtu\"><strong>Networking Performance: CNI, kube-proxy, and MTU<\/strong><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"cni-selection-and-tuning\"><strong>CNI selection and tuning<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Cilium (eBPF):<\/strong> Excellent performance, kube-proxy replacement, advanced observability.<\/li>\n\n\n\n<li><strong>Calico:<\/strong> Mature, policy-rich, good performance with IPVS; supports eBPF dataplane.<\/li>\n\n\n\n<li><strong>Flannel:<\/strong> Simple overlay; fine for small clusters, not the fastest.<\/li>\n<\/ul>\n\n\n\n<p>Match MTU to your network. For VXLAN overlays, MTU often needs lowering (e.g., 1450) to avoid fragmentation. Enable kube-proxy <strong>IPVS<\/strong> mode or use Cilium\u2019s kube-proxy replacement for better service <a href=\"https:\/\/www.youstable.com\/blog\/install-load-balancer-on-linux\/\">load balancing<\/a>.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># kube-proxy in IPVS mode (excerpt for kubeadm-managed clusters)\napiVersion: kubeproxy.config.k8s.io\/v1alpha1\nkind: KubeProxyConfiguration\nmode: \"ipvs\"\nipvs:\n  scheduler: \"rr\"\n<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"storage-and-volume-optimization\"><strong>Storage and Volume Optimization<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Use CSI drivers<\/strong> optimized for your platform (EBS, Ceph, Longhorn, OpenEBS, local PVs).<\/li>\n\n\n\n<li><strong>Prefer NVMe<\/strong> for etcd and high-IO workloads; avoid network-attached storage for etcd.<\/li>\n\n\n\n<li><strong>Tune filesystem<\/strong> (XFS with correct reflink\/ftype, ext4 with journaling mode ordered, noatime).<\/li>\n\n\n\n<li><strong>Right-size PVCs<\/strong> and use <strong>ReadWriteOnce<\/strong> where possible for consistency and performance.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"workload-scheduling-and-resource-management\"><strong>Workload Scheduling and Resource Management<\/strong><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"requests-limits-and-qos-classes\"><strong>Requests, limits, and QoS classes<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Requests<\/strong> drive scheduling and capacity planning; set them to realistic averages.<\/li>\n\n\n\n<li><strong>Limits<\/strong> protect nodes, but strict CPU limits can cause CFS throttling. For throughput services, consider no CPU limit or a higher one.<\/li>\n\n\n\n<li><strong>Guaranteed QoS<\/strong> for latency-sensitive services (set requests = limits).<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"topology-and-numa-awareness\"><strong>Topology and NUMA awareness<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Enable <strong>CPU Manager<\/strong> (static) and <strong>Topology Manager<\/strong> (restricted\/single-numa-node) for consistent latency on multi-socket servers.<\/li>\n\n\n\n<li>Use <strong>nodeAffinity<\/strong>, <strong>podAntiAffinity<\/strong>, and <strong>topologySpreadConstraints<\/strong> to reduce contention and hotspots.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"autoscaling-that-actually-works\"><strong>Autoscaling That Actually Works<\/strong><\/h2>\n\n\n\n<p>Autoscaling is performance insurance. Use it to match capacity to demand and prevent overloaded nodes.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># Horizontal Pod Autoscaler example (CPU-based)\napiVersion: autoscaling\/v2\nkind: HorizontalPodAutoscaler\nmetadata:\n  name: web\nspec:\n  scaleTargetRef:\n    apiVersion: apps\/v1\n    kind: Deployment\n    name: web\n  minReplicas: 3\n  maxReplicas: 30\n  metrics:\n  - type: Resource\n    resource:\n      name: cpu\n      target:\n        type: Utilization\n        averageUtilization: 60\n<\/code><\/pre>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>HPA<\/strong> for replicas based on CPU\/memory\/custom metrics.<\/li>\n\n\n\n<li><strong>VPA<\/strong> for rightsizing requests (run in recommendation mode for safety on critical apps).<\/li>\n\n\n\n<li><strong>Cluster Autoscaler<\/strong> to add\/remove nodes (or provider-native tools). Ensure your cloud provider\/node group integrates properly.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"control-plane-and-etcd-tuning\"><strong>Control Plane and etcd Tuning<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Place <strong>etcd on dedicated, local NVMe<\/strong> with low latency; avoid remote\/networked disks.<\/li>\n\n\n\n<li>Run 3\u20135 etcd members; more is not always better due to quorum latency.<\/li>\n\n\n\n<li>Set appropriate etcd resource limits; monitor WAL fsync latency and apply periodic <strong>defrag<\/strong>.<\/li>\n\n\n\n<li>Co-locate control plane components on adequately sized nodes; pin CPU\/memory if noisy neighbors exist.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"observability-and-slo-driven-optimization\"><strong>Observability and SLO-Driven Optimization<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Metrics:<\/strong> Prometheus + kube-state-metrics; watch scheduler latency, API server requests, etcd commit latency, container CPU throttling, throttled seconds, and node pressure signals.<\/li>\n\n\n\n<li><strong>Logs:<\/strong> Use fluent-bit (lightweight) and enable log rotation for containerd JSON logs.<\/li>\n\n\n\n<li><strong>Tracing:<\/strong> OpenTelemetry for request path visibility; invaluable for pinpointing network vs CPU bottlenecks.<\/li>\n\n\n\n<li><strong>Dashboards:<\/strong> Define SLOs per service (p95 latency, error budget) and optimize only what impacts them.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"quick-wins-and-common-bottlenecks\"><strong>Quick Wins and Common Bottlenecks<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Switch kube-proxy to <strong>IPVS<\/strong> or use <strong>Cilium eBPF<\/strong> dataplane.<\/li>\n\n\n\n<li>Align <strong>cgroupDriver=systemd<\/strong> for both kubelet and containerd.<\/li>\n\n\n\n<li>Right-size <strong>requests<\/strong> and remove overly strict CPU <strong>limits<\/strong> if throttling is observed.<\/li>\n\n\n\n<li>Increase <strong>nf_conntrack_max<\/strong> for connection-heavy microservices.<\/li>\n\n\n\n<li>Lower <strong>MTU<\/strong> on overlays to prevent fragmentation.<\/li>\n\n\n\n<li>Enable <strong>CPU\/Topology Manager<\/strong> for latency-sensitive workloads.<\/li>\n\n\n\n<li>Use <strong>NVMe<\/strong> for etcd and container storage; set image GC thresholds.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"security-settings-that-also-improve-performance\"><strong>Security Settings That Also Improve Performance<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Use <strong>seccomp<\/strong> and <strong>AppArmor<\/strong> to reduce kernel attack surface and syscall overhead variability.<\/li>\n\n\n\n<li>Drop unnecessary Linux capabilities (e.g., remove <code>NET_RAW<\/code>) to limit risk and reduce packet handling overhead in some cases.<\/li>\n\n\n\n<li>Run minimal, distroless images to shrink attack surface and startup times.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"example-putting-it-all-together\"><strong>Example: Putting It All Together<\/strong><\/h2>\n\n\n\n<p>For a new node pool handling user-facing APIs with high connection churn:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Kernel\/sysctl: apply the config above, ensure <code>nf_conntrack_max=262144<\/code>, load <code>br_netfilter<\/code>.<\/li>\n\n\n\n<li>Runtime: containerd with <code>SystemdCgroup=true<\/code>, registry mirror enabled.<\/li>\n\n\n\n<li>Kubelet: CPU Manager static, Topology Manager restricted, eviction and image GC thresholds set, reservations applied.<\/li>\n\n\n\n<li>CNI: Cilium with eBPF kube-proxy replacement, MTU tuned to 1450.<\/li>\n\n\n\n<li>Workloads: Guaranteed QoS for gateway pods, HPA target 60% CPU, no CPU limit for high-throughput services, only requests.<\/li>\n\n\n\n<li>Observability: Prometheus alerts on API latency, conntrack usage, CPU throttling, and disk pressure.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"faqs-optimizing-kubernetes-on-linux\"><strong>FAQ&#8217;s: Optimizing Kubernetes on Linux<\/strong><\/h2>\n\n\n<div id=\"rank-math-faq\" class=\"rank-math-block\">\n<div class=\"rank-math-list \">\n<div id=\"faq-question-1765869891436\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \" class=\"rank-math-question \" id=\"1-what-sysctl-settings-are-best-for-kubernetes-performance\">1. <strong>What sysctl settings are best for Kubernetes performance?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Increase conntrack capacity (<code>nf_conntrack_max<\/code>), enable bridge netfilter for CNIs, raise socket buffers (<code>rmem_max<\/code>\/<code>wmem_max<\/code>), widen ephemeral ports, and increase neighbor cache thresholds. See the sysctl snippet above for a production-ready baseline.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1765869947669\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \" class=\"rank-math-question \" id=\"2-is-containerd-faster-than-docker-for-kubernetes\">2. <strong>Is containerd faster than Docker for Kubernetes?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Yes, containerd or CRI-O typically offer lower overhead and tighter CRI integration than Docker\u2019s shim-based setups. containerd is a strong default for performance, stability, and ecosystem support. Ensure <code>SystemdCgroup=true<\/code> for best results.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1765869956653\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \" class=\"rank-math-question \" id=\"3-should-i-disable-swap-on-kubernetes-nodes\">3. <strong>Should I disable swap on Kubernetes nodes?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>In most cases, yes. Disabling swap avoids unpredictable reclaim latency and aligns with kubelet\u2019s memory management. Swap support exists in newer Kubernetes versions but is advanced and not recommended for typical production clusters.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1765869967669\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \" class=\"rank-math-question \" id=\"4-which-cni-is-best-for-high-performance\">4. <strong>Which CNI is best for high performance?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Cilium (eBPF) leads for performance and advanced features, including kube-proxy replacement and deep observability. Calico is mature and fast, especially with IPVS or its eBPF dataplane. Flannel is simple but not the fastest at scale.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1765869979519\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \" class=\"rank-math-question \" id=\"5-how-do-cpu-limits-affect-performance-in-kubernetes\">5. <strong>How do CPU limits affect performance in Kubernetes?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Strict CPU limits enforce CFS quotas, which can cause throttling and latency spikes under load. For throughput-critical services, consider setting only requests (no limits) or higher limits, and use Guaranteed QoS for predictable CPU allocation.<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"final-checklist\"><strong>Final Checklist<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Linux tuned: sysctl applied, swap off, cgroup\/systemd aligned.<\/li>\n\n\n\n<li>containerd\/CRI-O configured; registry mirror and log rotation enabled.<\/li>\n\n\n\n<li>kubelet reservations, eviction, image GC, CPU\/Topology managers set.<\/li>\n\n\n\n<li>Fast CNI (Cilium\/Calico), MTU correct; kube-proxy in IPVS or eBPF replacement.<\/li>\n\n\n\n<li>NVMe-backed etcd and container storage; CSI driver optimized.<\/li>\n\n\n\n<li>Requests\/limits set for QoS; HPA\/VPA and Cluster Autoscaler in place.<\/li>\n\n\n\n<li>Observability with Prometheus and alerts on key latency and pressure metrics.<\/li>\n<\/ul>\n\n\n\n<p>Follow this roadmap and you\u2019ll run a Kubernetes cluster on Linux that is faster, more predictable, and easier to scale. If you prefer expert help, YouStable\u2019s engineers can design, benchmark, and <a href=\"https:\/\/www.youstable.com\/blog\/benefits-of-fully-managed-dedicated-server\/\">manage a fully<\/a> optimized Kubernetes stack tailored to your workloads.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>To optimize Kubernetes on a Linux server, tune the OS (sysctl, cgroups, swap), use a modern container runtime (containerd\/CRI-O), configure [&hellip;]<\/p>\n","protected":false},"author":13,"featured_media":17189,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"iawp_total_views":3,"footnotes":""},"categories":[350],"tags":[],"class_list":["post-13730","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-knowledgebase"],"acf":[],"featured_image_src":"https:\/\/www.youstable.com\/blog\/wp-content\/uploads\/2025\/12\/How-to-Optimize-Kubernetes-on-Linux-Server.jpg","author_info":{"display_name":"Prahlad Prajapati","author_link":"https:\/\/www.youstable.com\/blog\/author\/prahladblog"},"_links":{"self":[{"href":"https:\/\/www.youstable.com\/blog\/wp-json\/wp\/v2\/posts\/13730","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.youstable.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.youstable.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.youstable.com\/blog\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/www.youstable.com\/blog\/wp-json\/wp\/v2\/comments?post=13730"}],"version-history":[{"count":3,"href":"https:\/\/www.youstable.com\/blog\/wp-json\/wp\/v2\/posts\/13730\/revisions"}],"predecessor-version":[{"id":17191,"href":"https:\/\/www.youstable.com\/blog\/wp-json\/wp\/v2\/posts\/13730\/revisions\/17191"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.youstable.com\/blog\/wp-json\/wp\/v2\/media\/17189"}],"wp:attachment":[{"href":"https:\/\/www.youstable.com\/blog\/wp-json\/wp\/v2\/media?parent=13730"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.youstable.com\/blog\/wp-json\/wp\/v2\/categories?post=13730"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.youstable.com\/blog\/wp-json\/wp\/v2\/tags?post=13730"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}