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:

1. Connects to Prometheus and executes a query to fetch detailed test failure history.
2. Processes the raw data into a format suitable for the Gemini API.
3. Successfully calls the Gemini API with the data and a clear prompt.
4. Parses the AI's response to extract a simple list of flaky tests.
5. Saves the list to a JSON file that can be displayed in Grafana.
6. 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

• Jenkins Flaky Test Detector: https://github.com/srbarrios/jenkins-flaky-tests-detector and its container
• IaC on MLM Team: https://gitlab.suse.de/galaxy/infrastructure/-/tree/master/srv/salt/monitoring/jenkinsflakytestsdetector?reftype=heads, https://gitlab.suse.de/galaxy/infrastructure/-/blob/master/srv/salt/monitoring/grafana/dashboards/flaky-tests.json?ref_type=heads, and others.
• Grafana Dashboard: https://grafana.mgr.suse.de/d/flaky-tests/flaky-tests-detection @ @ text

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Uyuni Health-check Grafana AI Troubleshooter by ygutierrez

Description

This project explores the feasibility of using the open-source Grafana LLM plugin to enhance the Uyuni Health-check tool with LLM capabilities. The idea is to integrate a chat-based "AI Troubleshooter" directly into existing dashboards, allowing users to ask natural-language questions about errors, anomalies, or performance issues.

Goals

• Investigate if and how the grafana-llm-app plug-in can be used within the Uyuni Health-check tool.
• Investigate if this plug-in can be used to query LLMs for troubleshooting scenarios.
• Evaluate support for local LLMs and external APIs through the plugin.
• Evaluate if and how the Uyuni MCP server could be integrated as another source of information.

Resources

Grafana LMM plug-in

Uyuni Health-check

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Updatecli Autodiscovery supporting WASM plugins by olblak

Description

Updatecli is a Golang Update policy engine that allow to write Update policies in YAML manifest. Updatecli already has a plugin ecosystem for common update strategies such as automating Dockerfile or Kubernetes manifest from Git repositories.

This is what we call autodiscovery where Updatecli generate manifest and apply them dynamically based on some context.

Obviously, the Updatecli project doesn't accept plugins specific to an organization.

I saw project using different languages such as python, C#, or JS to generate those manifest.

It would be great to be able to share and reuse those specific plugins

During the HackWeek, I'll hang on the Updatecli matrix channel

https://matrix.to/#/#Updatecli_community:gitter.im

Goals

Implement autodiscovery plugins using WASM. I am planning to experiment with https://github.com/extism/extism

To build a simple WASM autodiscovery plugin and run it from Updatecli

Resources

• https://github.com/extism/extism
• https://github.com/updatecli/updatecli
• https://www.updatecli.io/docs/core/autodiscovery/
• https://matrix.to/#/#Updatecli_community:gitter.im

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Rewrite Distrobox in go (POC) by fabriziosestito

Description

Rewriting Distrobox in Go.

Main benefits:

• Easier to maintain and to test
• Adapter pattern for different container backends (LXC, systemd-nspawn, etc.)

Goals

• Build a minimal starting point with core commands
• Keep the CLI interface compatible: existing users shouldn't notice any difference
• Use a clean Go architecture with adapters for different container backends
• Keep dependencies minimal and binary size small
• Benchmark against the original shell script

Resources

• Upstream project: https://github.com/89luca89/distrobox/
• Distrobox site: https://distrobox.it/
• ArchWiki: https://wiki.archlinux.org/title/Distrobox

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terraform-provider-feilong by e_bischoff

Project Description

People need to test operating systems and applications on s390 platform. While this is straightforward with KVM, this is very difficult with z/VM.

IBM Cloud Infrastructure Center (ICIC) harnesses the Feilong API, but you can use Feilong without installing ICIC(see this schema).

What about writing a terraform Feilong provider, just like we have the terraform libvirt provider? That would allow to transparently call Feilong from your main.tf files to deploy and destroy resources on your z/VM system.

Goal for Hackweek 23

I would like to be able to easily deploy and provision VMs automatically on a z/VM system, in a way that people might enjoy even outside of SUSE.

My technical preference is to write a terraform provider plugin, as it is the approach that involves the least software components for our deployments, while remaining clean, and compatible with our existing development infrastructure.

Goals for Hackweek 24

Feilong provider works and is used internally by SUSE Manager team. Let's push it forward!

Let's add support for fiberchannel disks and multipath.

Goals for Hackweek 25

Modernization, maturity, and maintenance: support for SLES 16 and openTofu, new API calls, fixes...

Resources

• Feilong TSC and demo
• Call APIs with custom Framework Providers

Outcome

• provider, for terraform 1.5.5
• provider, for terraform 0.13.4
• go client library, for Feilong API 1.0

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Contribute to terraform-provider-libvirt by pinvernizzi

Description

The SUSE Manager (SUMA) teams' main tool for infrastructure automation, Sumaform, largely relies on terraform-provider-libvirt. That provider is also widely used by other teams, both inside and outside SUSE.

It would be good to help the maintainers of this project and give back to the community around it, after all the amazing work that has been already done.

If you're interested in any of infrastructure automation, Terraform, virtualization, tooling development, Go (...) it is also a good chance to learn a bit about them all by putting your hands on an interesting, real-use-case and complex project.

Goals

• Get more familiar with Terraform provider development and libvirt bindings in Go
• Solve some issues and/or implement some features
• Get in touch with the community around the project

Resources

• CONTRIBUTING readme
• Go libvirt library in use by the project
• Terraform plugin development
• "Good first issue" list

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SUSE Health Check Tools by roseswe

SUSE HC Tools Overview

A collection of tools written in Bash or Go 1.24++ to make life easier with handling of a bunch of tar.xz balls created by supportconfig.

Background: For SUSE HC we receive a bunch of supportconfig tar balls to check them for misconfiguration, areas for improvement or future changes.

Main focus on these HC are High Availability (pacemaker), SLES itself and SAP workloads, esp. around the SUSE best practices.

Goals

• Overall improvement of the tools
• Adding new collectors
• Add support for SLES16

Resources

csv2xls* example.sh go.mod listprodids.txt sumtext* trails.go README.md csv2xls.go exceltest.go go.sum m.sh* sumtext.go vercheck.py* config.ini csvfiles/ getrpm* listprodids* rpmdate.sh* sumxls* verdriver* credtest.go example.py getrpm.go listprodids.go sccfixer.sh* sumxls.go verdriver.go

docollall.sh* extracthtml.go gethostnamectl* go.sum numastat.go cpuvul* extractcluster.go firmwarebug* gethostnamectl.go m.sh* numastattest.go cpuvul.go extracthtml* firmwarebug.go go.mod numastat* xtr_cib.sh*

$ getrpm -r pacemaker >> Product ID: 2795 (SUSE Linux Enterprise Server for SAP Applications 15 SP7 x86_64), RPM Name: +--------------+----------------------------+--------+--------------+--------------------+ | Package Name | Version | Arch | Release | Repository | +--------------+----------------------------+--------+--------------+--------------------+ | pacemaker | 2.1.10+20250718.fdf796ebc8 | x86_64 | 150700.3.3.1 | sle-ha/15.7/x86_64 | | pacemaker | 2.1.9+20250410.471584e6a2 | x86_64 | 150700.1.9 | sle-ha/15.7/x86_64 | +--------------+----------------------------+--------+--------------+--------------------+ Total packages found: 2

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