Building better base images
This project addresses the inefficiencies of traditional Dockerfile-based container builds where each customization layer creates storage bloat through duplicate dependencies from repeated apt-get install commands, network inefficiency from redundant package downloads across different images, and slow iteration cycles requiring full rebuilds of all previous steps. Our solution enables building minimal base images from scratch using debootstrap that precisely include only required components in the initial build, while allowing creation of specialized variants (Java, Kafka, etc.) from these…
In plain words
This project provides tools for creating optimized container base images using debootstrap, targeting developers who build Docker containers. Rather than layering customizations in Dockerfiles that duplicate dependencies and waste storage, it generates minimal base images from scratch and creates specialized variants for specific workloads like Java or Kafka. The approach reduces image size, speeds up build times, and improves resource efficiency compared to traditional Docker layer stacking.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
This project addresses the inefficiencies of traditional Dockerfile-based container builds where each customization layer creates storage bloat through duplicate dependencies from repeated apt-get install commands, network inefficiency from redundant package downloads across different images, and slow iteration cycles requiring full rebuilds of all previous steps. Our solution enables building minimal base images from scratch using debootstrap that precisely include only required components in the initial build, while allowing creation of specialized variants (Java, Kafka, etc.) from these common foundations - resulting in significantly leaner images, faster builds, and more efficient resource utilization compared to standard Docker layer stacking approaches.
More work this month
the category →


The app store for voice native apps that lives in your notch
Work · 28d ago · voiceos.com

The New Calendly▲211Handle all of the work before, during, and after meetings
Work · 17d ago · calendly.com
Launched alongside, April 2025
the whole month →- IB
Hi everyone, I built PyXL — a hardware processor that executes a custom assembly generated from Python programs, without using a traditional interpreter or virtual machine. It compiles Python -> CPython Bytecode -> Instruction set designed for direct hardware execution. I’m sharing an early benchmark: a GPIO test where PyXL achieves a 480ns round-trip toggle — compared to 14-25 micro seconds on a MicroPython Pyboard - even though PyXL runs at a lower clock (100MHz vs. 168MHz). The design is stack-based, fully pipelined, and preserves Python's dynamic typing without static type restrictions.…
Dev tools · 2025 · runpyxl.com
- UC
Life & fun · 2025 · filiph.github.io
- IB
https://the-pocket.github.io/Tutorial-Codebase-Knowledge/
AI · 2025 · github.com


