Minio

Mochi is a self-hosted algorithmic trading backtest platform. It takes a stock ticker and date range, downloads historical market data, runs trading strategy simulations across multiple parameter combinations, aggregates the results with Trino, generates statistical graphs with R, and presents everything through a React dashboard. The entire pipeline runs on a homelab Kubernetes cluster orchestrated by Argo Workflows. Architecture Overview ┌──────────────────────────────────────────────────────────────────────────┐ │ dashboard.minoko.life │ │ React + Vite + TypeScript │ │ S3 client (MinIO) ─── Backtest API client │ └──────────────┬───────────────────────────────┬───────────────────────────┘ │ │ ▼ ▼ ┌──────────────────────┐ ┌──────────────────────────┐ │ MinIO (S3 API) │ │ Backtest API (FastAPI) │ │ s3.minoko.life │ │ backtest-api.minoko.life│ │ 13 buckets │ │ POST /backtest │ └──────────┬───────────┘ └────────────┬─────────────┘ │ │ │ ┌───────────────────▼──────────────────┐ │ │ Argo Workflows │ │ │ workflows.minoko.life │ │ │ │ │ │ Phase 1: backtest-pipeline │ │ │ ┌────────┐ ┌──────────┐ ┌────────┐ │ │ │ │Polygon │→│Enhancer │→│Metadata│ │ │ │ │Python │ │Kotlin │ │Python │ │ │ │ └────────┘ └──────────┘ └───┬────┘ │ │ │ │ │ │ │ Phase 2: per scenario (x N) │ │ │ │ ┌──────────────────────────┐│ │ │ │ │mochi-trades (Java) ││ │ │ │ │ │ ││ │ │ │ │sync-partitions (Trino) ││ │ │ │ │ │ ││ │ │ │ │mochi-aggregate (Java) ││ │ │ │ │ │ ││ │ │ │ │ ┌──┴──┬──────┐ ││ │ │◀─────────────│──│ │years│stops │best- ││ │ │ results │ │ │ .r │ .r │traders.r││ │ │ │ │ └─────┴──────┴────┬────┘│ │ │ │ │ trade-extract (Kt) │ ││ │ │ │ │ py-trade-lens (Py) │ ││ │ │ │ │ trade-summary (Py) │ ││ │ │ │ └──────────────────────────┘│ │ │ └──────────────────────────────┘ │ │ │ │ ┌──────────────────────────────┐ │ └────────▶│ Trino (Coordinator + Worker) │◀──────────┘ │ Hive Metastore + Postgres │ │ 100GB worker for aggregation │ └──────────────────────────────┘ Components Component Language Purpose Image mochi-dashboard TypeScript/React UI, S3 browsing, backtest submission harbor.minoko.life/mochi/mochi-dashboard backtest-api Python/FastAPI Accepts backtest requests, creates Argo Workflows harbor.minoko.life/mochi/backtest-api polygon Python Downloads historical data from Polygon.io API harbor.minoko.life/mochi/polygon trade-data-enhancer Kotlin Calculates ATR and technical indicators harbor.minoko.life/mochi/trade-data-enhancer data-metadata Python Generates scenario parameter combinations for Phase 2 harbor.minoko.life/mochi/data-metadata mochi-java Java 21 Core trading simulation engine and Trino aggregation harbor.minoko.life/mochi/mochi-java r-graphs R Statistical visualizations (years, stops, best traders) harbor.minoko.life/mochi/r-graphs trade-extract Kotlin Extracts individual trades from aggregated results harbor.minoko.life/mochi/trade-extract py-trade-lens Python Trade analysis and insights harbor.minoko.life/mochi/py-trade-lens trade-summary Python Final result summarization harbor.minoko.life/mochi/trade-summary Five languages across ten containerized services. ...

etcd is the heart of a Kubernetes cluster - it stores all cluster state including deployments, secrets, configmaps, and PVC definitions. Losing etcd means losing your entire cluster configuration. Yet many homelab setups neglect etcd backups until it’s too late. This post walks through setting up automated etcd backups using a Kubernetes CronJob that uploads snapshots to MinIO. The Challenge etcd runs as a static pod on the control plane node, which makes backing it up trickier than a regular application: ...

How I set up automated cloud backups for my homelab Kubernetes cluster using MinIO and Scaleway, while avoiding US and German cloud providers. The Problem I run a Kubernetes homelab with PostgreSQL and ImmuDB databases. Daily backups run via CronJobs and store compressed dumps in MinIO (self-hosted S3-compatible storage). But what happens if my server dies? All my backups would be gone. I needed offsite cloud backup, but wanted to avoid: ...