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📜 HomeLab Chronicles: Episode 6 - Source of Truth

Hey all 👋 Last episode a power cut exposed an uncomfortable fact: my cluster's entire memory lived in one SQLite-flavored database, on one laptop, bound to one Wi-Fi address, guarded by one aging battery. Four single points of failure in a trench coat. The fix isn't making that database unkillable. The fix is making it unimportant . If every manifest lives in git and something reconciles the cluster against git continuously, then "the datastore died" stops being a tragedy and becomes a reboot with extra steps. So: Flux . Here's the setup, and the four ways I face-planted installing it. 🗂️ The Shape of the Repo clusters/homelab/ flux-system/ <- Flux writes this at bootstrap; hands off infrastructure.yaml <- points at infrastructure/ apps.yaml <- points at apps/ infrastructure/ controllers/ <- Longhorn + Envoy Gateway HelmReleases configs/ <- GatewayClass, Gateway, StorageClasses apps/homelab/ airflow/ <- the actual point of all this Three Flux Kustomizations, chained: infra-controllers → infra-configs → apps , via dependsOn . That chaining is not decoration. My GatewayClass can't exist until Envoy Gateway's CRDs exist, and the CRDs arrive with the controller's Helm chart. Without dependsOn , Flux sprints ahead, tries to create a GatewayClass into a cluster that's never heard of GatewayClasses, and fails with the enthusiasm of a golden retriever running into a glass door. dependsOn plus wait: true turns that into: install controllers, wait until healthy , then configs, then apps. Boring. Sequential. Correct. The three great virtues. 🔑 Sidequest 1: The Token Bureaucracy flux bootstrap github needs a GitHub token, and the docs-diving summary is: Classic PAT: repo scope. Needed if Flux should create the repo. Fine-grained PAT (pre-created repo): Contents read/write, Metadata read, and — the one everyone misses — Administration read/write , because Flux installs an SSH deploy key on the repo, and deploy keys are an admin operation. Here's the nice part: the deploy key is

2026-08-30 原文 →
AI 资讯

Smart Home Garden Irrigation Project

Garden Irrigation System Summary MY project to make a bespoke irrigation system for my home garden, which comes in at under £10 per zone including the actual water delivery method, and is made with relatively easily sourced components. I am a mechanical engineer by training, but not an electrician so interested in hearing pointers on how to make it better. Some of the component and tool links below are AliExpress affiliate links. If you buy through them I earn a small commission at no extra cost to you. Everything listed is what I actually bought and used, or the closest equivalent I could find. This helps me fund some more ambitious but hopefully useful builds in the future. Intro So I have a vegetable patch and some flowers in the garden; it became a bit of a job during the hot days of summer to water the plants in the evening. I didn’t especially mind it but given my love of AI and tech, alongside recent experiments with Home Assistant, I thought there must be a 2026 version of this job. I tried a Wi-Fi-controlled tap, but quickly realised the flow rate was low - due to a small aperture size, and also scaling up with this type of solution to 6 + zones would quickly get expensive and leave me dependent on battery-powered solutions - also not a big win. So as I had begun experimenting with creating my own devices with dev boards etc, I figured, “how hard can it be” and in honesty it wasn’t, just took a bit of trial and error. This guide will be focused on how i would build it today, not all the steps that got me to here. My philosophy Standardised equipment/ components as much as possible Speed of delivery = speed of experimentation Modular where possible Anything can be achieved at any cost, but some of the fun is building something from very little Components Note all water pipes for this project are ½ inch and so connector etc are for that, this corresponds to a ¾ in threaded connector for attaching to pipes Standard UK Hose (½ inch) ¾ inch Threaded Tap Push Fit

2026-08-29 原文 →
AI 资讯

ESP32 Energy Metering with HLW8032, BL0942, and ESPHome

ESP32 Energy Metering with HLW8032, BL0942, and ESPHome ESP32 energy metering with HLW8032, BL0942, and ESPHome is not just about reading voltage, current, power, and energy. This article explains how to design the UART boundary, reporting cadence, calibration, entity model, and diagnostics as one stable data path. Many ESP32 energy metering projects start well. You connect an HLW8032 or BL0942 module, enable the matching ESPHome component, and Home Assistant quickly shows voltage, current, power, and energy. But reading values is not the same as building an energy metering node that can run reliably over time. The core conclusion is this: the hard part of ESP32 energy metering is not whether HLW8032 or BL0942 can be read. The hard part is designing the metering chip, UART, Wi-Fi behavior, ESPHome entities, calibration, and diagnostics as one stable data path. If the project focuses only on sensor YAML, it can later fail on transient loads, serial conflicts, unstable sampling, Wi-Fi reconnects, Home Assistant database growth, and calibration drift. In this article, an ESP32 energy metering node means an edge device where ESP32 reads voltage, current, power, and energy from a metering chip such as HLW8032 or BL0942, then exposes those values through ESPHome to Home Assistant or another upper-layer platform. It is suitable for device energy monitoring, trend observation, and low-risk operational diagnostics. It should not be treated as a billing-grade meter or an electrical protection device. If the goal is to monitor the energy behavior of one appliance, one small circuit, or one commercial device inside Home Assistant, ESP32 + ESPHome + HLW8032/BL0942 is a fast and low-cost path. If the goal is billing, electrical protection, high-accuracy compliance measurement, or safety interlocking, use certified meters, protection devices, or industrial acquisition hardware instead of stretching an ESPHome node beyond its boundary. 1. Why energy metering is more fragile than or

2026-08-27 原文 →
AI 资讯

Domux: a compact open model for smart-home command understanding at the edge

Voice and chat assistants for the home share a deceptively hard job: turning messy natural language into precise, structured commands. “Make it cozy in here” has to become a concrete intent plus the right slots — which device, which room, which value. Domux is an open model from iFlytek that focuses on exactly this problem: command understanding for smart-home assistants, framed as intent parsing and slot filling. What it is Task: smart-home command understanding — intent parsing + slot filling Base model: fine-tuned on google/gemma-4-E2B-it Modality: multimodal (image + text input) Target: edge / on-device deployment rather than large cloud models License: Gemma Why the compact base matters Building on the small Gemma-4-E2B base keeps Domux in a size class meant to run close to the device. For home assistants, that direction is attractive: keeping command understanding on-device can reduce round-trips and keep more interaction local, instead of routing every utterance to a large hosted model. Try it The model card is on Hugging Face (access is gated — you may need to log in and request access): 👉 https://huggingface.co/iFlytekOpenSource/Domux We're sharing open work like this because on-device, task-focused models are a practical piece of the foundation-model and serving story — not everything needs to be a giant cloud model.

2026-08-23 原文 →