{"id":1561,"date":"2026-11-02T22:38:48","date_gmt":"2026-11-02T22:38:48","guid":{"rendered":"https:\/\/bestdedicatedwebhostingserver.com\/blog\/?p=1561"},"modified":"2026-11-02T22:38:48","modified_gmt":"2026-11-02T22:38:48","slug":"gaming-server-bare-metal-kubernetes-k3s-node-basics","status":"publish","type":"post","link":"https:\/\/bestdedicatedwebhostingserver.com\/blog\/gaming-server-bare-metal-kubernetes-k3s-node-basics\/","title":{"rendered":"Kubernetes on Bare-Metal Game Nodes: k3s Basics That Actually Matter"},"content":{"rendered":"
\n

Bare-metal Kubernetes trades a managed control plane, cloud load balancers, and node autoscaling for predictable performance, no egress bill, and full control of the network layer. For a single-node or small-cluster setup — a CI runner pool, internal services, or a game-adjacent backend — that trade is usually a good one. This guide covers what changes, how much Kubernetes you need, and the gaps you must fill yourself. For a hardware-level companion, see the bare-metal reference on this site<\/a>.<\/p>\n

What the absence of a cloud provider removes<\/h2>\n

A cloud Kubernetes cluster relies on a control loop that watches for a Service of type LoadBalancer and asks the provider’s API to create one. On bare metal that API does not exist, so the Service stays pending forever unless you install something that implements the contract.<\/p>\n

The same applies to node lifecycle. There is no autoscaler group to grow, and no cloud controller to remove a node that stops responding. You own the lifecycle: provisioning, joining, draining, and replacing nodes are all manual or scripted operations you write.<\/p>\n

Persistent volumes are another gap. Cloud clusters conjure a block device from an API; on bare metal you either use a CSI driver bound to local disks, or provision a distributed storage layer.<\/p>\n\n\n\n\n\n\n\n\n\n
Concern<\/th>\nCloud default<\/th>\nBare-metal replacement<\/th>\n<\/tr>\n<\/thead>\n
LoadBalancer Services<\/td>\nProvisioned automatically<\/td>\nMetalLB or NodePort<\/td>\n<\/tr>\n
Persistent storage<\/td>\nProvider CSI<\/td>\nLocal-path, Rook-Ceph, or Longhorn<\/td>\n<\/tr>\n
Node scaling<\/td>\nAutoscaler<\/td>\nManual or scripted<\/td>\n<\/tr>\n
Node identity<\/td>\nProvider metadata<\/td>\nExplicit --node-ip<\/code> and hostname<\/td>\n<\/tr>\n
Ingress IP<\/td>\nManaged<\/td>\nOwn address, BGP or virtual IP<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

How much Kubernetes do you actually need<\/h2>\n

For a single dedicated server, k3s is usually the right answer. It packages the control plane into one process, replaces etcd with a lighter embedded store by default, and ships with a Traefik ingress and a service load balancer. It runs comfortably in 1–2 GB of RAM, leaving the rest for workloads.<\/p>\n

Full upstream Kubernetes on a single node is possible and useful if you need version parity with a production cluster, but the control plane components alone will consume several gigabytes. On a 32 GB server that is acceptable; on a 16 GB server it is a poor allocation.<\/p>\n

For three or more servers, k3s with an embedded etcd topology gives you a highly available control plane without a separate management node. RKE2 is the alternative when you need a stricter security baseline and explicit CIS hardening.<\/p>\n

Addressing and ingress on hardware you own<\/h2>\n

You will have a small static public address block. Two things need to be decided before installation: which address the ingress listens on, and how a node that moves between machines keeps the same identity.<\/p>\n

The simplest arrangement on a single node is to bind a dedicated IP to the host network and have the ingress controller claim it through a hostNetwork DaemonSet. On a multi-node cluster, MetalLB in L2 mode advertises the service IP from one node at a time, with failover when that node goes down. If you have AS number and BGP access, MetalLB in BGP mode gives cleaner failover and proper ECMP.<\/p>\n

kubectl create namespace metallb-system\nkubectl apply -f https:\/\/raw.githubusercontent.com\/metallb\/metallb\/main\/config\/manifests\/metallb-native.yaml\n# then an IPAddressPool and L2Advertisement for your block<\/code><\/pre>\n
Note that advertising an address block into a provider network sometimes requires coordination with them. Confirm before you configure BGP that the upstream router will accept your announcements.<\/p>\n
Storage decisions that cannot be deferred<\/h2>\n
Ephemeral pods on local NVMe are trivially fast, and for stateless services you need nothing beyond the built-in local-path provisioner. The moment you need a PersistentVolume that survives a node replacement, the calculus changes.<\/p>\n
For a single node, local-path is the correct answer, paired with a backup strategy, because any failure of the machine loses the data. For three nodes, Longhorn gives replicated block storage with a reasonably simple operational model, at the cost of write latency and cross-node network traffic. Ceph via Rook is more capable and considerably more complex; it makes sense at five nodes and above.<\/p>\n
Be honest about the trade: distributed storage on three nodes with 1 Gbit networking is slower on random writes than a local NVMe, sometimes by a factor of three. Running a database on it because “it is replicated” is a common mistake that trades availability for latency most workloads do not need.<\/p>\n
Network plugin and the MTU trap<\/h2>\n
Flannel with VXLAN is the default in most small-cluster setups and is easy to operate. Calico without an overlay, running in pure BGP mode, avoids encapsulation and the associated MTU overhead, at the cost of requiring address management upstream.<\/p>\n
If you choose an overlay, the pod MTU must be reduced by the encapsulation header — typically 50 bytes for VXLAN. Leaving the pod MTU at 1500 while the underlay is also 1500 produces the classic symptom of small requests succeeding and large responses hanging, because the encapsulated packets exceed the path MTU and are silently dropped.<\/p>\n
ip link show flannel.1 | grep mtu\nkubectl exec -it <pod> -- ip route get 1.1.1.1<\/code><\/pre>\n
Operations you now own<\/h2>\n
Back up the etcd snapshot on a schedule, not just the workloads. For k3s, this is a single command, and it should run from a systemd timer with retention:<\/p>\n
k3s etcd-snapshot save --name=$(date +%F)\nls \/var\/lib\/rancher\/k3s\/server\/db\/snapshots\/<\/code><\/pre>\n
Certificate rotation is automatic on k3s, but the kubelet serving certificate needs to be recognised as rotated when the node’s address changes. If you rebuild a node with a new address, drain and delete the old node object rather than renaming in place.<\/p>\n
Finally, monitor the node as a node: kubelet resource pressure evicts pods based on node conditions, and a disk that reaches the eviction threshold will start killing pods that were perfectly healthy. Alert on filesystem usage at 80% and reserve dedicated disk for the container runtime through --kubelet-arg=eviction-hard<\/code>.<\/p>\n
When bare-metal Kubernetes is worth it<\/h2>\n
If you are running a handful of containers, Docker Compose on a single machine is simpler and cheaper in operational time. Kubernetes earns its complexity when you need declarative rollouts across several nodes, self-healing, and a uniform deployment model across environments. On dedicated hardware, that case arrives most often for internal platforms, CI runners that need real CPU and disk, and game backends that benefit from persistent local storage.<\/p>\n
Start with k3s on one node, add MetalLB only when you need a stable service address, and defer distributed storage until a second failure domain genuinely exists. The cluster that survives its first year is the one whose operator understood every component well enough to debug it without a managed control plane to lean on. For further bare-metal platform guides, browse the dedicated server operations archive on bestdedicatedwebhostingserver.com<\/a>.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"
Bare-metal Kubernetes trades a managed control plane, cloud load balancers, and node autoscaling for predictable performance, no egress bill, and full control of the network layer. 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