Every time we went to UEFI Plugfest, one of the frequently asked questions is how to setup a PXE/HTTPBoot server. Besides, we also have to setup and test the server before the event. Although we already have the document(*), it may be easier to deploy with a container image. My goal is to learn how to package a container image in SLE/openSUSE and create a flexible image for the fast deployment of PXE/HTTPBoot server.

The current geekos install at http://geekos.prv.suse.net/search is not reachable for employees outside of engineering. We want to move it to the SUSE IT maintained EKS cluster to make it available for all.

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SUSE dissolved an old warehouse, containing lots and lots of boxes with old SUSE / SuSE / S.u.S.E software. All of those boxes were originally going to be dumped in March 2021, which could be prevented. They are now stored in the SUSE Event Area in Nuremberg.

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A few months ago, the YaST team released cockpit-wicked. Compared to YaST, this module contains a pretty simple data model, but there is still some duplication with YaST logic.

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The idea for project starts on LEO workshop. The main goal is to provide UI for local configuration that allows easy transition to 1:N management. So here is vision:

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• Complete the pull request from rust2rpm that will help bundling crates in RPM

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Join an instructor-led bootcamp to explore the Rust programming language in two-hour sessions each day throughout Hackweek.

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I run openSUSE TW and FF with i7-5600U Intel CPU. Calls with ~4 (video) participants work but my CPU load is approaching number of cores. In slightly bigger calls (>=6 participants) the CPU load was insufficient and audio packets were being dropped. I'd like learn more about webrtc video streams in order to reduce the client's CPU work or make it more adaptive when running with limited resources.

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A local RMT mirror will run out of space at some point because rpm files, which are not referenced by repomd.xml anymore, are left behind.

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The aim of the project is to run a sample microservice app in Kubernetes. A simple app will be written in Python and work as an online store comprising of frontend, orders, and products services. (could be more!!)

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This project aims to speed-up and simplify setup for analysis of application core files provided by our customers.

motivation

Test automation can be fun and openQA is good at it but it has limitations. This project is meant to find out where the limits are for applications with lots of things moving on the screen, e.g. a game. Completely unrelated, web based tools become the norm for many users, e.g. when working from a chromebook or similar environments. The idea here is to try to use only web based tools and not force users to use a terminal which can be frightening :) As a third requirement: Some people are not feeling comfortable using openQA "because tests are written in Perl". This is not necessarily true because tests are rather written using a simplistic test API and only a small subset of Perl knowledge is necessary, however, we still want to support other entry points so there is Python support added in https://github.com/os-autoinst/os-autoinst/pull/1558 . To find out what this new way is capable of this project should use only that Python support and find out any restrictions.

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I've had a fairly modern AMD GPU for some time, but I haven't had time to check the current status of neural network based video editing. I know many are proprietary CUDA specific, sadly, even if projects themselves would be open source, but I'd like to check which ones would support OpenCL as well or any other means to use an AMD GPU with fully open source stack (including drivers).

Relax-and-Recover (ReaR) is used to recreate a destroyed system on compatible replacement hardware, see https://en.opensuse.org/SDB:Disaster_Recovery Currently ReaR requires basically 100% compatible replacement hardware.

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There are multiple network benchmark tools already, most popular probably being netperf and iperf. Each of them has its pros and cons but the biggest drawback probably is that netperf runs only one connection (flow) and while iperf can use multiple connections, it still runs in a single thread. For benchmarking of contemporary fast networks like 40Gb/s or 100Gb/s ethernet, this can be a severe limitation as the performance is often CPU bound. Even on 10Gb/s ethernet, we are often unable to saturate the medium if tunneling or complex packet processing is involved.

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I'd like to have NeoMutt show an index of emails at the same time as the body of the selected email, horizontally next to each other.

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Create a JS library to get the output openQA logs (autoinst-log) and

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Study Google Motion Photo file format, which records a short video clip in addition to actual photo in the same jpeg file.

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PyYAML is a YAML processor in python, and it was one of the first libraries written for YAML.