Project Description

The goal is to have a language model, that is able to answer technical questions on Uyuni. Uyuni documentation is too large for in-context processing, so finetuning is the way to go.

Goal for this Hackweek

Finetune a model based on llama-2-7b.

Resources

github repo

No Hackers yet

Join this project Leave this project

Looking for hackers with the skills:

ai uyuni

This project is part of:

Hack Week 23

Activity

about 2 years ago: nadvornik added keyword "ai" to this project.

about 2 years ago: nadvornik added keyword "uyuni" to this project.

about 2 years ago: nadvornik originated this project.

Comments

Be the first to comment!

Similar Projects

ai

The Agentic Rancher Experiment: Do Androids Dream of Electric Cattle? by moio

Rancher is a beast of a codebase. Let's investigate if the new 2025 generation of GitHub Autonomous Coding Agents and Copilot Workspaces can actually tame it.

The Plan

Create a sandbox GitHub Organization, clone in key Rancher repositories, and let the AI loose to see if it can handle real-world enterprise OSS maintenance - or if it just hallucinates new breeds of Kubernetes resources!

Specifically, throw "Agentic Coders" some typical tasks in a complex, long-lived open-source project, such as:

❥ The Grunt Work: generate missing GoDocs, unit tests, and refactorings. Rebase PRs.

❥ The Complex Stuff: fix actual (historical) bugs and feature requests to see if they can traverse the complexity without (too much) human hand-holding.

❥ Hunting Down Gaps: find areas lacking in docs, areas of improvement in code, dependency bumps, and so on.

If time allows, also experiment with Model Context Protocol (MCP) to give agents context on our specific build pipelines and CI/CD logs.

Why?

We know AI can write "Hello World." and also moderately complex programs from a green field. But can it rebase a 3-month-old PR with conflicts in rancher/rancher? I want to find the breaking point of current AI agents to determine if and how they can help us to reduce our technical debt, work faster and better. At the same time, find out about pitfalls and shortcomings.

The CONCLUSION!!!

A State of the Union document was compiled to summarize lessons learned this week. For more gory details, just read on the diary below!

Enable more features in mcp-server-uyuni by j_renner

Description

I would like to contribute to mcp-server-uyuni, the MCP server for Uyuni / Multi-Linux Manager) exposing additional features as tools. There is lots of relevant features to be found throughout the API, for example:

At the end of the week I managed to enable basic system group operations:

List all system groups visible to the user
Create new system groups
List systems assigned to a group
Add and remove systems from groups

Goals

Set up test environment locally with the MCP server and client + a recent MLM server [DONE]
Identify features and use cases offering a benefit with limited effort required for enablement [DONE]
Create a PR to the repo [DONE]

Resources

Flaky Tests AI Finder for Uyuni and MLM Test Suites by oscar-barrios

Description

Our current Grafana dashboards provide a great overview of test suite health, including a panel for "Top failed tests." However, identifying which of these failures are due to legitimate bugs versus intermittent "flaky tests" is a manual, time-consuming process. These flaky tests erode trust in our test suites and slow down development.

This project aims to build a simple but powerful Python script that automates flaky test detection. The script will directly query our Prometheus instance for the historical data of each failed test, using the jenkins_build_test_case_failure_age metric. It will then format this data and send it to the Gemini API with a carefully crafted prompt, asking it to identify which tests show a flaky pattern.

The final output will be a clean JSON list of the most probable flaky tests, which can then be used to populate a new "Top Flaky Tests" panel in our existing Grafana test suite dashboard.

Goals

By the end of Hack Week, we aim to have a single, working Python script that:

Connects to Prometheus and executes a query to fetch detailed test failure history.
Processes the raw data into a format suitable for the Gemini API.
Successfully calls the Gemini API with the data and a clear prompt.
Parses the AI's response to extract a simple list of flaky tests.
Saves the list to a JSON file that can be displayed in Grafana.
New panel in our Dashboard listing the Flaky tests

Resources

Jenkins Prometheus Exporter: https://github.com/uyuni-project/jenkins-exporter/
Data Source: Our internal Prometheus server.
Key Metric: jenkins_build_test_case_failure_age{jobname, buildid, suite, case, status, failedsince}.
Existing Query for Reference: count by (suite) (max_over_time(jenkins_build_test_case_failure_age{status=~"FAILED|REGRESSION", jobname="$jobname"}[$__range])).
AI Model: The Google Gemini API.
Example about how to interact with Gemini API: https://github.com/srbarrios/FailTale/
Visualization: Our internal Grafana Dashboard.
Internal IaC: https://gitlab.suse.de/galaxy/infrastructure/-/tree/master/srv/salt/monitoring

Outcome

Is SUSE Trending? Popularity and Developer Sentiment Insight Using Native AI Capabilities by terezacerna

Description

This project aims to explore the popularity and developer sentiment around SUSE and its technologies compared to Red Hat and their technologies. Using publicly available data sources, I will analyze search trends, developer preferences, repository activity, and media presence. The final outcome will be an interactive Power BI dashboard that provides insights into how SUSE is perceived and discussed across the web and among developers.

Goals

Assess the popularity of SUSE products and brand compared to Red Hat using Google Trends.
Analyze developer satisfaction and usage trends from the Stack Overflow Developer Survey.
Use the GitHub API to compare SUSE and Red Hat repositories in terms of stars, forks, contributors, and issue activity.
Perform sentiment analysis on GitHub issue comments to measure community tone and engagement using built-in Copilot capabilities.
Perform sentiment analysis on Reddit comments related to SUSE technologies using built-in Copilot capabilities.
Use Gnews.io to track and compare the volume of news articles mentioning SUSE and Red Hat technologies.
Test the integration of Copilot (AI) within Power BI for enhanced data analysis and visualization.
Deliver a comprehensive Power BI report summarizing findings and insights.
Test the full potential of Power BI, including its AI features and native language Q&A.

Resources

Google Trends: Web scraping for search popularity data
Stack Overflow Developer Survey: For technology popularity and satisfaction comparison
GitHub API: For repository data (stars, forks, contributors, issues, comments).
Gnews.io API: For article volume and mentions analysis.
Reddit: SUSE related topics with comments.

Local AI assistant with optional integrations and mobile companion by livdywan

Description

Setup a local AI assistant for research, brainstorming and proof reading. Look into SurfSense, Open WebUI and possibly alternatives. Explore integration with services like openQA. There should be no cloud dependencies. Mobile phone support or an additional companion app would be a bonus. The goal is not to develop everything from scratch.

User Story

Allison Average wants a one-click local AI assistent on their openSUSE laptop.
Ash Awesome wants AI on their phone without an expensive subscription.

Goals

Evaluate a local SurfSense setup for day to day productivity
Test opencode for vibe coding and tool calling

Timeline

Day 1

Took a look at SurfSense and started setting up a local instance.
Unfortunately the container setup did not work well. Tho this was a great opportunity to learn some new podman commands and refresh my memory on how to recover a corrupted btrfs filesystem.

Day 2

Due to its sheer size and complexity SurfSense seems to have triggered btrfs fragmentation. Naturally this was not visible in any podman-related errors or in the journal. So this took up much of my second day.

Day 3

Trying out opencode with Qwen3-Coder and Qwen2.5-Coder.

Day 4

Context size is a thing, and models are not equally usable for vibe coding.
Through arduous browsing for ollama models I did find some like myaniu/qwen2.5-1m:7b with 1m but even then it is not obvious if they are meant for tool calls.

Day 5

Whilst trying to make opencode usable I discovered ramalama which worked instantly and very well.

Outcomes

surfsense

I could not easily set this up completely. Maybe in part due to my filesystem issues. Was expecting this to be less of an effort.

opencode

Installing opencode and ollama in my distrobox container along with the following configs worked for me.

When preparing a new project from scratch it is a good idea to start out with a template.

opencode.json

``` {

uyuni

Enable more features in mcp-server-uyuni by j_renner

Description

At the end of the week I managed to enable basic system group operations:

List all system groups visible to the user
Create new system groups
List systems assigned to a group
Add and remove systems from groups

Goals

Set up test environment locally with the MCP server and client + a recent MLM server [DONE]
Identify features and use cases offering a benefit with limited effort required for enablement [DONE]
Create a PR to the repo [DONE]

Resources

Ansible to Salt integration by vizhestkov

Description

We already have initial integration of Ansible in Salt with the possibility to run playbooks from the salt-master on the salt-minion used as an Ansible Control node.

In this project I want to check if it possible to make Ansible working on the transport of Salt. Basically run playbooks with Ansible through existing established Salt (ZeroMQ) transport and not using ssh at all.

It could be a good solution for the end users to reuse Ansible playbooks or run Ansible modules they got used to with no effort of complex configuration with existing Salt (or Uyuni/SUSE Multi Linux Manager) infrastructure.

Goals

[v] Prepare the testing environment with Salt and Ansible installed
[v] Discover Ansible codebase to figure out possible ways of integration
[v] Create Salt/Uyuni inventory module
[v] Make basic modules to work with no using separate ssh connection, but reusing existing Salt connection
[v] Test some most basic playbooks

Resources

GitHub page

Video of the demo

Move Uyuni Test Framework from Selenium to Playwright + AI by oscar-barrios

Description

This project aims to migrate the existing Uyuni Test Framework from Selenium to Playwright. The move will improve the stability, speed, and maintainability of our end-to-end tests by leveraging Playwright's modern features. We'll be rewriting the current Selenium code in Ruby to Playwright code in TypeScript, which includes updating the test framework runner, step definitions, and configurations. This is also necessary because we're moving from Cucumber Ruby to CucumberJS.

If you're still curious about the AI in the title, it was just a way to grab your attention. Thanks for your understanding.

Nah, let's be honest AI helped a lot to vibe code a good part of the Ruby methods of the Test framework, moving them to Typescript, along with the migration from Capybara to Playwright. I've been using "Cline" as plugin for WebStorm IDE, using Gemini API behind it.

Goals

Migrate Core tests including Onboarding of clients
Improve test reliabillity: Measure and confirm a significant reduction of flakiness.
Implement a robust framework: Establish a well-structured and reusable Playwright test framework using the CucumberJS

Resources

mgr-ansible-ssh - Intelligent, Lightweight CLI for Distributed Remote Execution by deve5h

Description

By the end of Hack Week, the target will be to deliver a minimal functional version 1 (MVP) of a custom command-line tool named mgr-ansible-ssh (a unified wrapper for BOTH ad-hoc shell & playbooks) that allows operators to:

Execute arbitrary shell commands on thousand of remote machines simultaneously using Ansible Runner with artifacts saved locally.
Pass runtime options such as inventory file, remote command string/ playbook execution, parallel forks, limits, dry-run mode, or no-std-ansible-output.
Leverage existing SSH trust relationships without additional setup.
Provide a clean, intuitive CLI interface with --help for ease of use. It should provide consistent UX & CI-friendly interface.
Establish a foundation that can later be extended with advanced features such as logging, grouping, interactive shell mode, safe-command checks, and parallel execution tuning.

The MVP should enable day-to-day operations to efficiently target thousands of machines with a single, consistent interface.

Goals

Primary Goals (MVP):

Build a functional CLI tool (mgr-ansible-ssh) capable of executing shell commands on multiple remote hosts using Ansible Runner. Test the tool across a large distributed environment (1000+ machines) to validate its performance and reliability.

Looking forward to significantly reducing the zypper deployment time across all 351 RMT VM servers in our MLM cluster by eliminating the dependency on the taskomatic service, bringing execution down to a fraction of the current duration. The tool should also support multiple runtime flags, such as:

mgr-ansible-ssh: Remote command execution wrapper using Ansible Runner

Usage: mgr-ansible-ssh [--help] [--version] [--inventory INVENTORY]
                   [--run RUN] [--playbook PLAYBOOK] [--limit LIMIT]
                   [--forks FORKS] [--dry-run] [--no-ansible-output]

Required Arguments
--inventory, -i      Path to Ansible inventory file to use

Any One of the Arguments Is Required
--run, -r            Execute the specified shell command on target hosts
--playbook, -p       Execute the specified Ansible playbook on target hosts

Optional Arguments
--help, -h           Show the help message and exit
--version, -v        Show the version and exit
--limit, -l          Limit execution to specific hosts or groups
--forks, -f          Number of parallel Ansible forks
--dry-run            Run in Ansible check mode (requires -p or --playbook)
--no-ansible-output  Suppress Ansible stdout output

Secondary/Stretched Goals (if time permits):

Add pretty output formatting (success/failure summary per host).
Implement basic logging of executed commands and results.
Introduce safety checks for risky commands (shutdown, rm -rf, etc.).
Package the tool so it can be installed with pip or stored internally.

Resources

Collaboration is welcome from anyone interested in CLI tooling, automation, or distributed systems. Skills that would be particularly valuable include:

Python especially around CLI dev (argparse, click, rich)

Testing and adding GNU/Linux distributions on Uyuni by juliogonzalezgil

Join the Gitter channel! https://gitter.im/uyuni-project/hackweek

Uyuni is a configuration and infrastructure management tool that saves you time and headaches when you have to manage and update tens, hundreds or even thousands of machines. It also manages configuration, can run audits, build image containers, monitor and much more!

Currently there are a few distributions that are completely untested on Uyuni or SUSE Manager (AFAIK) or just not tested since a long time, and could be interesting knowing how hard would be working with them and, if possible, fix whatever is broken.

For newcomers, the easiest distributions are those based on DEB or RPM packages. Distributions with other package formats are doable, but will require adapting the Python and Java code to be able to sync and analyze such packages (and if salt does not support those packages, it will need changes as well). So if you want a distribution with other packages, make sure you are comfortable handling such changes.

No developer experience? No worries! We had non-developers contributors in the past, and we are ready to help as long as you are willing to learn. If you don't want to code at all, you can also help us preparing the documentation after someone else has the initial code ready, or you could also help with testing :-)

The idea is testing Salt (including bootstrapping with bootstrap script) and Salt-ssh clients

To consider that a distribution has basic support, we should cover at least (points 3-6 are to be tested for both salt minions and salt ssh minions):

Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)
Onboarding (salt minion from UI, salt minion from bootstrap scritp, and salt-ssh minion) (this will probably require adding OS to the bootstrap repository creator)
Package management (install, remove, update...)
Patching
Applying any basic salt state (including a formula)
Salt remote commands
Bonus point: Java part for product identification, and monitoring enablement
Bonus point: sumaform enablement (https://github.com/uyuni-project/sumaform)
Bonus point: Documentation (https://github.com/uyuni-project/uyuni-docs)
Bonus point: testsuite enablement (https://github.com/uyuni-project/uyuni/tree/master/testsuite)

If something is breaking: we can try to fix it, but the main idea is research how supported it is right now. Beyond that it's up to each project member how much to hack :-)

If you don't have knowledge about some of the steps: ask the team
If you still don't know what to do: switch to another distribution and keep testing.

This card is for EVERYONE, not just developers. Seriously! We had people from other teams helping that were not developers, and added support for Debian and new SUSE Linux Enterprise and openSUSE Leap versions :-)

In progress/done for Hack Week 25

Guide

We started writin a Guide: Adding a new client GNU Linux distribution to Uyuni at https://github.com/uyuni-project/uyuni/wiki/Guide:-Adding-a-new-client-GNU-Linux-distribution-to-Uyuni, to make things easier for everyone, specially those not too familiar wht Uyuni or not technical.

openSUSE Leap 16.0

The distribution will all love!

https://en.opensuse.org/openSUSE:Roadmap#DRAFTScheduleforLeap16.0

Curent Status We started last year, it's complete now for Hack Week 25! :-D

[W] Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file) NOTE: Done, client tools for SLMicro6 are using as those for SLE16.0/openSUSE Leap 16.0 are not available yet
[W] Onboarding (salt minion from UI, salt minion from bootstrap scritp, and salt-ssh minion) (this will probably require adding OS to the bootstrap repository creator)
[W] Package management (install, remove, update...). Works, even reboot requirement detection