--- title: "Building an Uptime Kuma Cluster with Vibe Coding: From Standalone to High-Availability Monitoring Platform" description: "Using the Vibe Coding approach, a step-by-step guide to upgrading Uptime Kuma from standalone to a cluster-capable high-availability monitoring system — covering Docker Compose, load balancing, shared databases, and full Failover." canonical_url: "https://blog.markkulab.net/en/post/implement-uptime-kuma-cluster-vibe-coding" author: "Mark Ku" author_url: "https://blog.markkulab.net/en/author/mark-ku" site: "Mark Ku's Tech Notes" date_published: "2025-08-18T18:30:00.000Z" date_modified: "2026-06-21T16:51:19.000Z" category: "DevOps" tags: ["uptime kuma", "cluster", "vibe coding", "docker", "mariadb", "load balancer", "monitoring", "high availability", "openresty"] language: "en" license: "CC BY 4.0" license_url: "https://creativecommons.org/licenses/by/4.0/" attribution: "when reusing or quoting, credit the author and link back to the original" --- # Building an Uptime Kuma Cluster with Vibe Coding: From Standalone to High-Availability Monitoring Platform > **TL;DR** — Upgrade Uptime Kuma to a cluster using Vibe Coding, Docker Compose, and MariaDB for high availability. ## Preface Uptime Kuma is an open-source monitoring tool — already great out of the box. But if you need to monitor more than 1,000 APIs on a single instance, things start getting sluggish. In this article I'll use **Vibe Coding** to walk through upgrading Uptime Kuma into a version that supports **sharding** and **clustering**, plus add APIs for easier automation. ## Why bother with a Cluster? First, the requirements. Uptime Kuma is open-source monitoring software. [I previously shared how to switch its backend to MariaDB](https://blog.markkulab.net/uptime-kuma-mariadb-restful-api/). We replaced the default SQLite with MariaDB, deployed independently as `kuma-mariadb`, to support higher concurrent reads/writes. However, once monitoring scales past 1,000 APIs, performance noticeably drops — real testing confirmed sluggishness as the count grows. Uptime Kuma is a Node.js app, and Node.js's single-threaded architecture inherently has a performance ceiling under heavy concurrency. That led me to also research [practical solutions for Node.js single-thread performance limits](https://blog.markkulab.net/post/nodejs-worker-threads-bun-performance). Plus, our department's systems need to monitor nearly 4,000 APIs — a single Uptime Kuma instance just won't cut it. For services with SLA-based billing, monitoring downtime can mean direct contractual penalties — the monitoring platform itself must be highly available. Also, open-source Uptime Kuma doesn't support a RESTful API, which is very inconvenient for "API automatically goes live and becomes monitored" workflows. To avoid extra container deployment cost, we extended a RESTful API directly into Uptime Kuma. Based on these needs and limitations, **Cluster architecture** is the natural answer, ensuring: * **Fault tolerance / failover**: nodes can fail without service interruption * **Load distribution**: multiple instances share the load — more stable performance * **High availability**: avoid single points of failure, transparent and reliable data * **Automation**: API-driven monitoring creation — easier for DevOps ## Break down requirements, organize ideas, plan and implement with Vibe Coding In the spirit of Vibe Coding: break the requirements into small pieces, then build piece by piece. For larger and more complex projects, ask AI to draft a plan or guideline first, iteratively refine the AI-written plan, and finally have AI execute it. ### 1. Sharding support Different monitors need to be distributed to different nodes: * Add / modify / delete nodes * Clearly indicate which node each monitor runs on * On container start, auto-register the node into the database ### 2. Health Check Use **Nginx / OpenResty + Lua (`health_check.lua`)** for node health checks: #### Nginx Job mechanism OpenResty provides a powerful scheduled-task mechanism — easily implement periodic health checks via **`ngx.timer.at()`**: * **`init_worker_by_lua_block`**: runs when each worker process starts; initializes the health-check timer * **`ngx.timer.at(delay, callback)`**: creates a one-shot timer that runs the callback after the specified delay * **Recursive timers**: in the `health_check_worker` callback, after running the health check, call `ngx.timer.at()` again — forming a periodic loop * **Avoid duplicate execution**: use `ngx.shared.DICT` or marker variables to ensure each worker only starts one health-check task This design keeps health checks running entirely inside Nginx workers — no extra external process or cron job needed. Efficient and reliable. #### Health-check flow * OpenResty's worker periodically calls `health_check_worker`, running `run_health_check` at fixed intervals * For each node, call `/api/v1/health` for an HTTP health check * On consecutive failures → mark the node's status in the DB `node` table as `offline` * On consecutive successes → update `node.status` back to `online` and trigger the "monitor restoration" flow ### 3. Failover When a node dies, monitoring tasks must auto-migrate. This is handled by `health_check.lua` plus the database: * Add a dedicated `node` table and node-related fields in the DB to record each node's `status`, `last_seen` * The `monitor` table records each monitor's current `node_id` (and `assigned_node` when needed) * When a node fails health check several times consecutively: * health_check marks the node as `offline` * Calls `redistribute_monitors_from_node(node_id)` to evenly distribute the monitors that node was responsible for to other `online` nodes * When the node recovers (consecutive successful checks): * health_check marks the node as `online` * Calls `revert_monitors_to_node(node_id)` to move auto-migrated monitors back to the original node, preventing long-term imbalance ### 4. Node Recovery Recovered nodes need to come back automatically: * Auto-register on restart, status set to `online` * The system moves migrated monitors back * Ensure no duplicate execution, prevent data conflicts * Also provide **manual recovery** — let admins decide whether to migrate back ### 5. RESTful API extension Automation extension (RESTful API Extension): since native Uptime Kuma lacks an external API, to achieve "service goes live → automatically monitored" automation, we extended a RESTful API that automatically sets up monitoring when APIs are onboarded. Uptime Kuma actually has plenty of built-in logic — it just doesn't expose APIs (everything goes through WebSocket). Knowing that, we can ask AI to expose the Service as APIs, making automation much easier. ### 6. OpenResty unified entry and load balancing To present a single external entry point while internally distributing traffic among multiple Kuma nodes, we use OpenResty as the unified proxy and routing layer. This entry dynamically selects target nodes based on health and load, while handling real-time communication, APIs, and static content proxying. When a node fails, it auto-bypasses; when recovered, it re-flows — ensuring scalability and fault tolerance. ### 7. Manual node switching On top of automatic load balancing and Failover, provide a "manual node switching" capability: admins can switch single or multiple monitoring tasks to a specific node, drain a node before maintenance, or temporarily lock/pin total traffic to a specific node (including pinning via Cookie). These manual operations cooperate with existing health-check and auto-migration mechanisms — they don't conflict. ## System architecture ``` System Architecture ┌────────────────────────────┐ │ OpenResty (Nginx + Lua) │ │ ─ Load balancer (monitor_router) │ │ ─ Health check (health_check) │ └─────────┬──────────────────┘ │ ┌──────────────────┼────────────────────┐ │ │ │ ┌───────────▼─────────┐ ┌─────▼────────────┐ ┌─────▼────────────┐ │ Uptime Kuma │ │ Uptime Kuma │ │ Uptime Kuma │ │ Node 1 │ │ Node 2 │ │ Node 3 │ │ (Port 3001) │ │ (Port 3001) │ │ (Port 3001) │ │ (Host: 9091) │ │ (Host: 9092) │ │ (Host: 9093) │ └─────────┬───────────┘ └─────┬────────────┘ └──────┬───────────┘ │ │ │ └───────────────────┼─────────────────────┘ │ ┌─────────▼─────────┐ │ MariaDB │ │ (Port 3306) │ │ (Host: 9090) │ └───────────────────┘ ``` Key components: - **OpenResty / Nginx**: only defines a virtual `upstream uptime_kuma_cluster` in `nginx.conf`; the actual node selection is delegated to Lua. - **`monitor_router.lua`**: invoked in `balancer_by_lua_block`, providing `pick_node_for_request()` — dynamically picks the least-busy node based on each node's current "running monitor count," and routes via `ngx.balancer.set_current_peer()` to the corresponding `uptime-kuma-nodeX` container. - **`health_check.lua`**: periodically scans node health, updates the DB `node` table, and triggers automatic monitoring task migration and restoration on node failure/recovery. ## Flow diagrams ### 1. Load balancing and routing flow (monitor_router.lua) ``` Request flow Client Request │ ▼ Nginx / OpenResty (location /, /api/, /socket.io/ → proxy_pass to uptime_kuma_cluster) │ ▼ balancer_by_lua_block calls monitor_router.pick_node_for_request() │ ▼ Query DB: SELECT n.node_id, COUNT(m.id) AS monitor_count FROM node n LEFT JOIN monitor m ON m.node_id = n.node_id AND m.active = 1 WHERE n.status = 'online' GROUP BY n.node_id ORDER BY monitor_count ASC, node_id ASC │ ▼ Pick the online node with the fewest monitors (e.g., node2) │ ▼ Compose upstream: uptime-kuma-node2:3001 │ ▼ ngx.balancer.set_current_peer("uptime-kuma-node2", 3001) │ ▼ Request actually forwarded to the corresponding Uptime Kuma node ``` ### 2. Health check and Failover / Recovery flow (health_check.lua) ``` Health check and auto-migration flow Health check worker periodically runs run_health_check() │ ▼ Query DB to get all nodes (node table) │ ▼ For each node, call /api/v1/health │ ├── Healthy: update node.status = 'online', reset failure count; │ on consecutive successes trigger revert_monitors_to_node(node_id) │ └── Failed: accumulate failure count; once threshold is reached, set node.status = 'offline' and trigger redistribute_monitors_from_node(node_id), evenly distributing monitors to other online nodes │ ▼ Health status and stats written to DB + ngx.shared.health_checker │ ▼ Expose overall status externally via /health, /api/health-status, /lb/health, /lb/capacity APIs ``` ## Results ![Uptime Kuma dashboard showing service up and down status](https://blog.markkulab.net/content/markku/posts/implement-uptime-kuma-cluster-vibe-coding/images/螢幕截圖1.jpg) ![Uptime Kuma nodes settings displaying three online cluster nodes](https://blog.markkulab.net/content/markku/posts/implement-uptime-kuma-cluster-vibe-coding/images/螢幕截圖2.jpg) ![Uptime Kuma API documentation in Swagger UI showing health endpoints](https://blog.markkulab.net/content/markku/posts/implement-uptime-kuma-cluster-vibe-coding/images/螢幕截圖3.jpg) After discussing with my supervisor, since we take from the community we give back to the community — the related code is open-sourced: [Uptime Kuma Cluster GitHub repo](https://github.com/markku636/uptime-kuma-cluster) ## Reflections The AI era may have multiplied productivity by 5–10×, freeing us from typing every line by hand. But during later maintenance, we discover insufficient familiarity with the code. This drives home a deep lesson: no matter how tools evolve, someone ultimately needs to truly understand and maintain the code. Technical depth and comprehension remain irreplaceable. ## Further reading * [Practical solutions for Node.js single-thread performance bottlenecks](https://blog.markkulab.net/post/nodejs-worker-threads-bun-performance) * [Uptime Kuma official docs](https://github.com/louislam/uptime-kuma) * [Docker Compose official docs](https://docs.docker.com/compose/) * [OpenResty official docs](https://openresty.org/) * [MariaDB official docs](https://mariadb.org/) * [Lua programming language](https://www.lua.org/) --- ## About this article and its author Originally published on [Mark Ku's Tech Notes](https://blog.markkulab.net/en/post/implement-uptime-kuma-cluster-vibe-coding) License: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — when reusing or quoting, credit the author and link back to the original ### About the author **[Mark Ku](https://blog.markkulab.net/en/author/mark-ku)** — Software engineer - 10+ years as a software engineer - Built North-American e-commerce and AI SaaS subscription billing ### Free tools built by the author All of these are free to use: - [Free PDF Sign Tool](https://blog.markkulab.net/en/tools/pdf-sign): Online PDF sign tool — draw, type, or upload a signature, then drag, resize, and download. 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Free and open source (MIT). - [AI Podcast Cut](https://blog.markkulab.net/en/tools/ai-podcast-cut): Drop in a recording and it removes fillers and stutters, levels loudness segment by segment, and sends a second agent to review every cut. Cut points snap to word boundaries and zero crossings, every splice gets a fade, and sentence-end breaths are preserved. Desktop app for Windows, macOS and Linux. MIT licensed; the Windows installer bundles ffmpeg. - [AI Video Cut](https://blog.markkulab.net/en/tools/ai-video-cut): Pick something in your video: type it (face, license plate, phone screen, logo), click points or drag a box, or let Claude Code / Codex pick it. AI Video Cut tracks it frame by frame, then mosaics or blurs it, recolors it, pins stickers and text to it, swaps a screen or poster for your own image or video, or removes it using background that other frames actually captured. Plus sequence editing, local captions and an AI assistant. Free, open-source (MIT) Windows desktop app (macOS / Linux experimental) that runs locally, nothing uploaded. - [open-pos restaurant POS](https://blog.markkulab.net/en/tools/open-pos): One computer and one receipt printer is enough to open the shop. Your data lives on your own disk, no subscription, no lock-in, MIT licensed. Money is integer New Taiwan dollars with tax split by the statutory formula, so sales + tax always equals the total. Printing goes straight over ESC/POS on TCP 9100, with no vendor driver. Tauri + Rust + SQLite desktop app, v1.0 in development. - [.NET e-commerce API template](https://blog.markkulab.net/en/tools/dotnet-ecommerce-api): An e-commerce backend API template built on .NET 10: Controller → Service → Repository layering, Autofac convention-based registration, SqlSugar for MySQL / MariaDB and SQL Server, Redis cache and message queue, Hangfire jobs, JWT auth, and an extensible payment provider module (ECPay, Newebpay). 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