0
Automatically back up, verify, and monitor all your self-hosted services, databases, and containers from a single dashboard.
Added Mar 6, 2026
42 signals
Self-hosters and homelab operators cobble together fragile backup systems from multiple tools — bash scripts, cron jobs, rsync, separate monitoring services, and manual database dumps. These setups break silently, lack restore testing, and require constant maintenance. Most users admit their strategy amounts to hoping nothing breaks, with no unified way to manage backups across Docker containers, VMs, databases, and config files.
Detailed solution approach available for premium members.
Market timing analysis available for premium members.
Hi all, today I am pleased to open source the fractalbits api\_server, supporting both **actix & axum** framework. FractalBits is an S3-compatible object storage system designed for high performance and low latency. Using our custom-built metadata engine, it delivers up to 1 million 4K read IOPS for single bucket with p99 latency \~5ms, at significantly lower cost than AWS S3 Express One Zone. Unlike standard S3, FractalBits provides native atomic rename support for both objects and directories. Our storage engine is implemented with Zig, for its simpler io\_uring programming model and easier customized memory allocators. We are not open sourcing those parts yet, since the language is still moving to new async IO APIs. However, you can check how we make the two languages get along with each other well by checking our high performance rpc framework if interested. Other than that, We are basically **using rust to manage almost everything for our project**: build, dev env setup, testing setup and running, and also cloud deployments, without using a single line of shell script! Our repo link is below, and welcome to have a try and leave any feedback. I will also be pleased to answer any related questions: [https://github.com/fractalbits-labs/fractalbits-main](https://github.com/fractalbits-labs/fractalbits-main)
Hey r/selfhosted I'm thrilled to announce the latest major update to **Kriti Images**, my open-source, URL-based image transformation service built in Go. [**Website**](https://kritiimages.com) **|** [**Demo**](https://kritiimages.com/docs/transformations) **|** [**GitHub**](https://github.com/kritihq/kriti-images) If you're looking for a performant, self-hosted alternative to services like Cloudflare Images or ImageKit, Kriti Images is for you. **What's New: Scalable Storage with S3** This is a game-changer for self-hosters who need reliability and scalability without running into local storage limits. Setup is super simple with a config file: images: source: awss3 # Change from 'local' aws.s3.bucket: my-kriti-bucket **Quick Transformation Example** It lets you apply complex transformations (resize, crop, blur, format change, color adjustments, etc.) simply by modifying the image URL. GET /cgi/images/tr:width=500,blur=5,format=webp/image1.jpg Give Kriti Images a spin and let me know what you think! All feedback and contributions are welcome. *Up next I am working on a Canva like image editor with basic functionalities.*
HS5 is a high-performance scale-up self-hosted S3 compatible object storage server. It is ideal for use cases where single-node scaling, performance, and data-loss risk are acceptable. So for some self-hosting use cases it might be great. I actually see recent (the last one 20h ago) posts here where it might be a fit for the use case. HS5 features a web interface for managing buckets and users. I was previously using MinIO for my single node object storage needs, but it did not scale well with many objects since it creates multiple files for each object. Now it does not aim to solve the single-node use case anymore anyway and is unmaintained as well. Feedback welcome! Website: [https://hs5.eu](https://hs5.eu) Github: [https://github.com/uroni/hs5](https://github.com/uroni/hs5)
The provided text explores object storage as a specialized system for housing large, static files known as blobs, such as videos and high-resolution images. Unlike relational databases, which struggle with the performance overhead and backup delays caused by massive files, object storage uses a flat namespace and immutable writes to ensure efficiency. Key industry standards include using a traditional database for metadata while storing the actual content on cheap, redundant storage nodes to achieve high durability. [Object Storage](https://youtu.be/wJWlWzwaBuU) Advanced techniques like pre-signed URLs allow clients to bypass application servers for direct uploads, while multi-part uploads enable the handling of massive files by breaking them into smaller chunks. Ultimately, the source highlights tools like Amazon S3 as essential components for maintaining speed and scalability in modern system design.
[Benchmark screenshot showing GET performance](https://preview.redd.it/n06lrqr6bf3g1.png?width=2023&format=png&auto=webp&s=1ff2f3bf8bb7240f4728a8d3a2ebdd894ad1dbaa) See details in [https://github.com/fractalbits-labs/fractalbits-main/tree/main](https://github.com/fractalbits-labs/fractalbits-main/tree/main) and welcome feedback!
+81 more signals