[{"data":1,"prerenderedAt":335},["ShallowReactive",2],{"blog-en-k3s-vs-microk8s-ha-etcd-dqlite-edge-production":3,"blog-related-en-k3s-vs-microk8s-ha-etcd-dqlite-edge-production":284,"blog-en-k3s-vs-microk8s-ha-etcd-dqlite-edge-production-alt":272},{"id":4,"title":5,"author":6,"body":7,"date":266,"description":267,"extension":268,"image":269,"locale":270,"meta":271,"navigation":272,"path":273,"seo":274,"stem":275,"tags":276,"__hash__":283},"blog\u002Fblog\u002Fen\u002Fk3s-vs-microk8s-ha-etcd-dqlite-edge-production.md","K3s vs MicroK8s: Which One Actually Wins in Production? The HA Fork Between dqlite and etcd","Kubo Team",{"type":8,"value":9,"toc":256},"minimark",[10,15,23,30,47,56,60,66,75,83,97,100,104,110,113,121,134,145,153,157,163,166,179,182,185,189,195,198,220,223,227,230,242],[11,12,14],"h2",{"id":13},"_1-why-lumping-lightweight-kubernetes-together-leads-to-the-wrong-choice","1. Why Lumping \"Lightweight Kubernetes\" Together Leads to the Wrong Choice",[16,17,18],"p",{},[19,20],"img",{"alt":21,"src":22},"section01","https:\u002F\u002Fcdn.kubo.hexabase.io\u002Fimages\u002Fblog\u002Fen\u002Fk3s-vs-microk8s-ha-etcd-dqlite-edge-production\u002Fsection01.webp",[16,24,25,29],{},[26,27,28],"strong",{},"K3s vs MicroK8s"," comparisons often end with \"they're both lightweight, so pick whichever.\" But for anyone actually running a cluster at the edge or in production, these two are built on different philosophies.",[16,31,32,33,40,41,46],{},"K3s was built by Rancher (now part of SUSE). According to ",[34,35,39],"a",{"href":36,"rel":37},"https:\u002F\u002Fwww.cncf.io\u002Fprojects\u002Fk3s\u002F",[38],"nofollow","CNCF's official page",", K3s was accepted as a CNCF Sandbox project on August 19, 2020. ",[34,42,45],{"href":43,"rel":44},"https:\u002F\u002Fthenewstack.io\u002Franchers-k3s-joins-cncf-sandbox-as-first-kubernetes-distribution\u002F",[38],"The New Stack reported"," that this made it the first Kubernetes distribution to join CNCF Sandbox. MicroK8s, on the other hand, is a snap-package-first lightweight Kubernetes provided by Canonical, the company behind Ubuntu.",[16,48,49,50,55],{},"Different origins mean different resource design, different high-availability (HA) implementations, and different upgrade philosophies. If you choose based on \"lightweight means they're all the same,\" you'll run into unexpected operational overhead once you're in production. This article compares the practical differences between the two using data from official documentation. If you'd rather not spend time on this decision at all, a managed K3s option like ",[34,51,54],{"href":52,"rel":53},"https:\u002F\u002Fkubo.hexabase.io\u002F",[38],"Kubo"," is also worth considering.",[11,57,59],{"id":58},"_2-k3s-vs-microk8s-resource-requirements-and-install-method-measured","2. K3s vs MicroK8s: Resource Requirements and Install Method, Measured",[16,61,62],{},[19,63],{"alt":64,"src":65},"section02","https:\u002F\u002Fcdn.kubo.hexabase.io\u002Fimages\u002Fblog\u002Fen\u002Fk3s-vs-microk8s-ha-etcd-dqlite-edge-production\u002Fsection02.webp",[16,67,68,69,74],{},"According to ",[34,70,73],{"href":71,"rel":72},"https:\u002F\u002Fdocs.k3s.io\u002Finstallation\u002Frequirements",[38],"K3s's official documentation",", a server node requires a minimum of 2 CPU cores and 2GB of RAM, while an agent node requires 1 CPU core and 512MB of RAM. These are baseline requirements for K3s itself and its packaged components; workload resource consumption is separate. Supported architectures are x86_64, armhf, and arm64\u002Faarch64, so it runs on small devices like the Raspberry Pi.",[16,76,77,82],{},[34,78,81],{"href":79,"rel":80},"https:\u002F\u002Francher.com\u002Fproducts\u002Fk3s",[38],"Rancher's product page"," states that K3s ships as a single binary under 40MB. This design — reducing dependencies and packing everything into one binary — is what makes it this light.",[16,84,85,90,91,96],{},[34,86,89],{"href":87,"rel":88},"https:\u002F\u002Fcanonical.com\u002Fmicrok8s",[38],"MicroK8s",", by contrast, is positioned as \"Zero-ops, pure-upstream, HA Kubernetes,\" letting you spin up a fully functional cluster with minimal setup via its snap package. It installs on Linux via snap, on macOS via Homebrew, and on Windows via a dedicated installer — a breadth of OS support that differs from K3s. ",[34,92,95],{"href":93,"rel":94},"https:\u002F\u002Fcanonical.com\u002Fblog\u002Fcanonical-launches-microk8s-deploy-kubernetes-in-seconds",[38],"Canonical's official blog"," highlights single-command deployment and automatic updates through the Snap Store as key features.",[16,98,99],{},"Even from this comparison alone, it's clear that K3s is optimized for \"running standalone with minimal resources,\" while MicroK8s prioritizes \"multi-OS support and automated operations.\"",[11,101,103],{"id":102},"_3-k3s-vs-microk8s-the-ha-fork-embedded-etcd-vs-dqlite","3. K3s vs MicroK8s: The HA Fork — embedded etcd vs dqlite",[16,105,106],{},[19,107],{"alt":108,"src":109},"section03","https:\u002F\u002Fcdn.kubo.hexabase.io\u002Fimages\u002Fblog\u002Fen\u002Fk3s-vs-microk8s-ha-etcd-dqlite-edge-production\u002Fsection03.webp",[16,111,112],{},"The point where the two philosophies diverge most clearly is the datastore used for HA (high availability) configurations.",[16,114,115,116,120],{},"Per ",[34,117,73],{"href":118,"rel":119},"https:\u002F\u002Fdocs.k3s.io\u002Fdatastore",[38],", K3s uses SQLite as its default datastore in single-node setups. This is the option used \"when no other datastore is configured and no embedded etcd database file exists on disk,\" and it cannot be used in clusters with multiple servers. For an HA setup with multiple servers, K3s switches to embedded etcd.",[16,122,123,124,129,130,133],{},"MicroK8s takes a different approach. Per ",[34,125,128],{"href":126,"rel":127},"https:\u002F\u002Fcanonical.com\u002Fmicrok8s\u002Fdocs\u002Fhigh-availability",[38],"Canonical's official documentation",", HA is automatically enabled once a cluster has three or more nodes, and ",[26,131,132],{},"dqlite"," — a distributed SQLite — manages the Kubernetes state. Nodes are automatically classified into three roles: Voter (replicates the database and participates in leader election), Standby (replicates only), and Spare (does not participate in replication). If the leader fails, a new leader is elected within 5 seconds, and promoting a Standby node to Voter can take up to 30 seconds.",[16,135,136,137,140,141,144],{},"In short, ",[26,138,139],{},"K3s treats HA as an opt-in configuration change (SQLite → embedded etcd)",", while ",[26,142,143],{},"MicroK8s automatically moves to HA once the node-count condition is met",". The former suits teams that start with a single node and move to HA when needed; the latter suits teams that assume multi-node redundancy from the start. The difference in how much quorum design you need to think about yourself shows up here.",[16,146,147,148,152],{},"If you use a managed ",[34,149,151],{"href":52,"rel":150},[38],"K3s"," service like Kubo, you no longer need to think about embedded etcd quorum management at all — worth considering if your team is wary of HA operational complexity.",[11,154,156],{"id":155},"_4-addon-operations-and-upgrade-philosophy","4. Addon Operations and Upgrade Philosophy",[16,158,159],{},[19,160],{"alt":161,"src":162},"section04","https:\u002F\u002Fcdn.kubo.hexabase.io\u002Fimages\u002Fblog\u002Fen\u002Fk3s-vs-microk8s-ha-etcd-dqlite-edge-production\u002Fsection04.webp",[16,164,165],{},"The two philosophies diverge beyond HA, too, in day-to-day operations.",[16,167,168,169,173,174,178],{},"MicroK8s lets you enable addons — DNS, Ingress, Dashboard, Prometheus, Istio, LinkerD, Knative — with a single ",[170,171,172],"code",{},"microk8s enable"," command. As ",[34,175,177],{"href":87,"rel":176},[38],"Canonical's documentation"," describes, the premise is adding functionality as modules over time. Being a snap package also means automatic updates are built in by default, and an Ubuntu Pro subscription adds a 99.9% uptime guarantee and security maintenance.",[16,180,181],{},"K3s takes the opposite approach: starting from a minimal single binary and adding the components you need yourself, typically via Helm charts. Upgrades don't come with a built-in auto-update mechanism like Snap — the operations team controls the timing.",[16,183,184],{},"This is a tradeoff between \"delegating operations to automation\" and \"controlling it yourself.\" The former gets you moving faster and reduces reliance on any one person's knowledge; the latter makes it easier to track exactly what changed and avoid unexpected behavior shifts at an inconvenient time. Teams that want to manage Helm chart versions explicitly through GitOps will often find K3s's philosophy a better fit.",[11,186,188],{"id":187},"_5-edge-or-production-which-should-you-choose-a-decision-framework","5. Edge or Production: Which Should You Choose? A Decision Framework",[16,190,191],{},[19,192],{"alt":193,"src":194},"section05","https:\u002F\u002Fcdn.kubo.hexabase.io\u002Fimages\u002Fblog\u002Fen\u002Fk3s-vs-microk8s-ha-etcd-dqlite-edge-production\u002Fsection05.webp",[16,196,197],{},"Based on everything above, the decision comes down to three axes:",[199,200,201,208,214],"ul",{},[202,203,204,207],"li",{},[26,205,206],{},"Is resource constraint your top priority?"," In environments with limited memory\u002FCPU, like edge devices or IoT hardware, K3s's minimum requirements (2 cores\u002F2GB for server, 1 core\u002F512MB for agent) are the advantage",[202,209,210,213],{},[26,211,212],{},"Do you need parity between dev and production OS?"," If you want to reproduce the same setup on macOS or Windows, MicroK8s's multi-OS support makes it the better fit",[202,215,216,219],{},[26,217,218],{},"Who owns the HA design?"," If you want to control embedded etcd quorum design yourself, choose K3s; if you'd rather let node-count-based automation handle dqlite HA, choose MicroK8s",[16,221,222],{},"Both are conformant with the CNCF Certified Kubernetes Conformance Program and compatible with standard Kubernetes APIs, so application portability isn't a major differentiator. The difference lies in how much of the cluster's operations you're willing to take on yourselves.",[11,224,226],{"id":225},"_6-conclusion","6. Conclusion",[16,228,229],{},"K3s and MicroK8s both get filed under \"lightweight Kubernetes,\" but they differ clearly on three fronts: HA implementation (embedded etcd vs. dqlite), install\u002Fupgrade philosophy (manual control vs. automation), and OS support breadth. Rather than choosing \"because it's lightweight,\" the decision that won't leave you with regrets in production is based on how much HA operational overhead your team is willing to own.",[16,231,232,233,236,237,241],{},"If you'd rather eliminate that HA operational overhead entirely, ",[34,234,54],{"href":52,"rel":235},[38]," is an option worth considering. Kubo is a managed Kubernetes service built on K3s, where Kubo handles embedded etcd quorum design and upgrade timing on your behalf. It also delivers full K8s functionality starting at ¥48,000\u002Fmonth — about 58% of AWS EKS's ¥82,700\u002Fmonth. If you'd rather spend zero time deciding between K3s and MicroK8s and instead eliminate the operational burden altogether, check out the ",[34,238,240],{"href":52,"rel":239},[38],"Kubo Cloud"," configuration.",[16,243,244,245,249,250,255],{},"If you're evaluating K3s for edge deployments, ",[34,246,248],{"href":52,"rel":247},[38],"Kubo's"," K3s-based lightweight configuration extends directly to edge environments as well. If you need to run the same kind of comparison while keeping full data sovereignty on-premises, ",[34,251,254],{"href":252,"rel":253},"https:\u002F\u002Fwww.hexabase.com\u002Fproduct\u002Fkubo\u002Fon-premise",[38],"Kubo On-Premise"," is another option.",{"title":257,"searchDepth":258,"depth":258,"links":259},"",2,[260,261,262,263,264,265],{"id":13,"depth":258,"text":14},{"id":58,"depth":258,"text":59},{"id":102,"depth":258,"text":103},{"id":155,"depth":258,"text":156},{"id":187,"depth":258,"text":188},{"id":225,"depth":258,"text":226},"2026-10-25","K3s vs MicroK8s: both are called 'lightweight Kubernetes,' but the real production divide is HA architecture. We compare K3s's embedded etcd and MicroK8s's dqlite using official documentation data.","md","https:\u002F\u002Fcdn.kubo.hexabase.io\u002Fimages\u002Fblog\u002Fen\u002Fk3s-vs-microk8s-ha-etcd-dqlite-edge-production\u002Ftitle.webp","en",{},true,"\u002Fblog\u002Fen\u002Fk3s-vs-microk8s-ha-etcd-dqlite-edge-production",{"title":5,"description":267},"blog\u002Fen\u002Fk3s-vs-microk8s-ha-etcd-dqlite-edge-production",[277,278,279,280,281,282],"k3s","microk8s","kubernetes","high-availability","edge-computing","comparison","PaNa_GFrDXSN_wBjWGDD9iUmvf2VguTtB01r_mncdYw",[285,293,301,310,318,326],{"path":286,"title":287,"description":288,"date":289,"tags":290},"\u002Fblog\u002Fen\u002Fk3s-prometheus-agent-mode-stale-marker-edge-monitoring","We Switched K3s Edge Prometheus to Agent Mode. The Moment a Target Disappeared, So Did Its Metrics","Running Prometheus Agent mode on K3s edge clusters can leave stale values in your central dashboard when a target disappears, depending on how stale markers are handled. Here's how to design K3s edge monitoring correctly.","2026-11-03",[277,279,291,281,292],"prometheus","observability",{"path":294,"title":295,"description":296,"date":297,"tags":298},"\u002Fblog\u002Fen\u002Fk3s-system-upgrade-controller-plan-stuck-node-drain","The Plan Never Disappeared. Why K3s's system-upgrade-controller Got Stuck on One Node","We set up automated upgrades with K3s's system-upgrade-controller, and the Plan stopped progressing on a single node. The culprits were PodDisruptionBudgets and taints. Here's how the mechanism works, how to recover, and how Kubo helps.","2026-10-31",[277,279,299,300,281],"system-upgrade-controller","rolling-upgrade",{"path":302,"title":303,"description":304,"date":305,"tags":306},"\u002Fblog\u002Fen\u002Fk3s-spegel-embedded-registry-mirror-airgap-node-join","K3s's Embedded Registry Mirror Was Supposed to Just Work. Then a New Edge Node Couldn't Pull Images","K3s's embedded registry mirror (Spegel) is supposed to work cluster-wide, but a newly added edge node alone failed to pull images. The cause: an undistributed registries.yaml, credential drift, and a known containerd 2.0 bug. Here's the correct distribution workflow for air-gapped operations.","2026-10-30",[277,279,307,308,309,281],"spegel","registry-mirror","airgap",{"path":311,"title":312,"description":313,"date":314,"tags":315},"\u002Fblog\u002Fen\u002Fk3s-microshift-etcd-ostree-edge-comparison","Is Pinning etcd at the Edge a Trap or a Trade-off? K3s vs MicroShift and the Real Cost of OSTree Auto-Rollback","K3s and MicroShift are both called \"lightweight Kubernetes,\" but their assumptions about datastores and OS update models are fundamentally different. We compare etcd lock-in and OSTree auto-rollback to help you choose for production edge deployments.","2026-10-29",[277,316,279,281,317],"microshift","redhat",{"path":319,"title":320,"description":321,"date":322,"tags":323},"\u002Fblog\u002Fen\u002Fk3s-kubeadm-ha-etcd-failover-rto-gap","Your RTO Said 30 Seconds. It Took 3 Minutes. Why K3s and kubeadm HA Specs Don't Match Reality","How long does failover really take with K3s embedded etcd versus kubeadm stacked\u002Fexternal etcd? We examine the gap between official RTO targets and real-world recovery times, and how failure domains and node counts differ.","2026-10-09",[277,279,324,280,325],"etcd","kubeadm",{"path":327,"title":328,"description":329,"date":330,"tags":331},"\u002Fblog\u002Fen\u002Fk3s-rke2-migration-production-downtime-cis-ha","We Migrated K3s to RKE2 and Production Went Down for Two Hours. What \"Lightweight K8s\" Buyers Overlook","K3s vs RKE2 is often reduced to a feature checklist. Using a real production migration incident, we break down CIS Hardening, HA requirements, and storage assumptions to help you choose the right distribution for production.","2026-10-05",[277,332,279,333,280,334],"rke2","cis-benchmark","production-kubernetes",1793798729209]