Last hackweek filtra was created – a tool to extract information like lead and cycle times from Github repos for (but not limited to) projects that are doing Kanban. The collected metrics can then be visualized with Grafana.
Currently there are two problems with filtra:
- There are two branches. The master branch, that can query information from one project per instance and the multi-board branch, that can query from multiple projects. Sadly the metrics looks a bit different for both of the branches and this needs to be fixed. Also unittests are badly needed! See: Metrics are different #20 and Missing Tests #23
- Currently filtra is basically a Prometheus endpoint. But Prometheus is not a perfect fit for this use-case, since we are only collecting a few metrics per day but with a very high retention. This is usually different for data collected with Prometheus. So the conclusion was that Postgresql would be a better fit for storing that data.
Looking for hackers with the skills:
go golang github metrics graphql grafana postgresql leadtime cycletime projectmanagement
This project is part of:
Hack Week 19
Activity
Comments
-
almost 6 years ago by jochenbreuer | Reply
First update: We'll go with Sqlite instead of Postgresql.
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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
Cluster API Provider for Harvester by rcase
Project Description
The Cluster API "infrastructure provider" for Harvester, also named CAPHV, makes it possible to use Harvester with Cluster API. This enables people and organisations to create Kubernetes clusters running on VMs created by Harvester using a declarative spec.
The project has been bootstrapped in HackWeek 23, and its code is available here.
Work done in HackWeek 2023
- Have a early working version of the provider available on Rancher Sandbox : *DONE *
- Demonstrated the created cluster can be imported using Rancher Turtles: DONE
- Stretch goal - demonstrate using the new provider with CAPRKE2: DONE and the templates are available on the repo
DONE in HackWeek 24:
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- Improve Status Conditions for some phases
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- Testing with Harvester v1.3.2
- Template improvements
- Issues creation
DONE in 2025 (out of Hackweek)
- Support of ClusterClass
- Add to
clusterctlcommunity providers, you can add it directly withclusterctl - Testing on newer versions of Harvester v1.4.X and v1.5.X
- Support for
clusterctl generate cluster ... - Improve Status Conditions to reflect current state of Infrastructure
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Goals for HackWeek 2025
- FIRST and FOREMOST, any topic is important to you
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- Certify the provider for Rancher Turtles
- Add Machine pool labeling
- Add PCI-e passthrough capabilities.
- Other improvement suggestions are welcome!
Thanks to @isim and Dominic Giebert for their contributions!
Resources
Looking for help from anyone interested in Cluster API (CAPI) or who wants to learn more about Harvester.
This will be an infrastructure provider for Cluster API. Some background reading for the CAPI aspect:
Help Create A Chat Control Resistant Turnkey Chatmail/Deltachat Relay Stack - Rootless Podman Compose, OpenSUSE BCI, Hardened, & SELinux by 3nd5h1771fy
Description
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FYI: If you have never heard of "Chatmail", you can visit their site here, but simply put it can be thought of as the underlying protocol/platform decentralized messengers like DeltaChat use for their communications. Do not confuse it with the honeypot looking non-opensource paid for prodect with better seo that directs you to chatmailsecure(dot)com
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Goals
As I indicated earlier, this project aims to drastically simplify the deployment of Chatmail relay. By converting this architecture into a portable, containerized stack using Podman and OpenSUSE base container images, we can allow anyone to deploy their own censorship-resistant, privacy-preserving communications node in minutes.
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Resources
- The links included above
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- https://delta.chat/en/help
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Description
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Rewrite Distrobox in go (POC) by fabriziosestito
Description
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Main benefits:
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Goals
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Resources
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- ArchWiki: https://wiki.archlinux.org/title/Distrobox
Create a go module to wrap happy-compta.fr by cbosdonnat
Description
https://happy-compta.fr is a tool for french work councils simple book keeping. While it does the job, it has no API to work with and it is tedious to enter loads of operations.
Goals
Write a go client module to be used as an API to programmatically manipulate the tool.
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Resources
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https://matrix.to/#/#Updatecli_community:gitter.im
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Resources
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- https://www.updatecli.io/docs/core/autodiscovery/
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go-git: unlocking SHA256-based repository cloning ahead of git v3 by pgomes
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Resources
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Description
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Resources
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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!
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❥ 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 Outputs
❥ A "State of the Agentic Union" for SUSE engineers, detailing what works, what explodes, and how much coffee we can drink while the robots do the rebasing.
❥ Honest, Daily Updates With All the Gory Details
issuefs: FUSE filesystem representing issues (e.g. JIRA) for the use with AI agents code-assistants by llansky3
Description
Creating a FUSE filesystem (issuefs) that mounts issues from various ticketing systems (Github, Jira, Bugzilla, Redmine) as files to your local file system.
And why this is good idea?
- User can use favorite command line tools to view and search the tickets from various sources
- User can use AI agents capabilities from your favorite IDE or cli to ask question about the issues, project or functionality while providing relevant tickets as context without extra work.
- User can use it during development of the new features when you let the AI agent to jump start the solution. The issuefs will give the AI agent the context (AI agents just read few more files) about the bug or requested features. No need for copying and pasting issues to user prompt or by using extra MCP tools to access the issues. These you can still do but this approach is on purpose different.

Goals
- Add Github issue support
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- Add support for Bugzilla and Redmine using this approach in the process of doing it. Record a video of it.
- Clean-up and test the implementation and create some documentation
- Create a blog post about this approach
Resources
There is a prototype implementation here. This currently sort of works with JIRA only.
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
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- 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
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- GitHub API: For repository data (stars, forks, contributors, issues, comments).
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- Reddit: SUSE related topics with comments.
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
- 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
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
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- Evaluate if and how the Uyuni MCP server could be integrated as another source of information.
Resources
Uyuni read-only replica by cbosdonnat
Description
For now, there is no possible HA setup for Uyuni. The idea is to explore setting up a read-only shadow instance of an Uyuni and make it as useful as possible.
Possible things to look at:
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- Can we use a load balancer that routes read-only queries to either instance and the other to the RW one? For example, packages or PXE data can be served by both, the API GET requests too. The rest would be RW.
Goals
- Prepare a document explaining how to do it.
- PR with the needed code changes to support it