A common challenge for OpenStack and K8S deployments is debugging the network when things go awry. The aim of DPHAT is to provide operators of cloud infrastructure with tooling that can analyze the environment and supply the following:
- Feedback that the environment is in a healthy operational state
- Identification of and guidance about where something in the network fabric is broken
- Guidance on remediation steps
- A pluggable interface to enable support for various cloud platforms, their respective networking backends, and any hardware devices (ie switches/routers) present in the deployment
- RESTful API, CLI, and UI
This involves:
- Gathering information from any relevant SDN controller, representing the network topology for the cloud, and developing an algorithm for analyzing the topology
- Probing of VM's and containers via ARP, ICMP (ping), port scan, ofproto trace, etc. to asses forwarding and security policy instantiation
- Reading pod / compute node state and identifying missing namespaces, tap devices, iptables chains, etc.
- Building a database of remediation actions that can be correlated with issues flagged by DPHAT
If you want to help alleviate the headache of debugging networking issues in the cloud, let's work together!
Looking for hackers with the skills:
This project is part of:
Hack Week 18
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SUSE AI Meets the Game Board by moio
Use tabletopgames.ai’s open source TAG and PyTAG frameworks to apply Statistical Forward Planning and Deep Reinforcement Learning to two board games of our own design. On an all-green, all-open source, all-AWS stack!
Results: Infrastructure Achievements
We successfully built and automated a containerized stack to support our AI experiments. This included:
- a Fully-Automated, One-Command, GPU-accelerated Kubernetes setup: we created an OpenTofu based script, tofu-tag, to deploy SUSE's RKE2 Kubernetes running on CUDA-enabled nodes in AWS, powered by openSUSE with GPU drivers and gpu-operator
- Containerization of the TAG and PyTAG frameworks: TAG (Tabletop AI Games) and PyTAG were patched for seamless deployment in containerized environments. We automated the container image creation process with GitHub Actions. Our forks (PRs upstream upcoming):
./deploy.sh
and voilà - Kubernetes running PyTAG (k9s
, above) with GPU acceleration (nvtop
, below)
Results: Game Design Insights
Our project focused on modeling and analyzing two card games of our own design within the TAG framework:
- Game Modeling: We implemented models for Dario's "Bamboo" and Silvio's "Totoro" and "R3" games, enabling AI agents to play thousands of games ...in minutes!
- AI-driven optimization: By analyzing statistical data on moves, strategies, and outcomes, we iteratively tweaked the game mechanics and rules to achieve better balance and player engagement.
- Advanced analytics: Leveraging AI agents with Monte Carlo Tree Search (MCTS) and random action selection, we compared performance metrics to identify optimal strategies and uncover opportunities for game refinement .
- more about Bamboo on Dario's site
- more about R3 on Silvio's site (italian, translation coming)
- more about Totoro on Silvio's site
A family picture of our card games in progress. From the top: Bamboo, Totoro, R3
Results: Learning, Collaboration, and Innovation
Beyond technical accomplishments, the project showcased innovative approaches to coding, learning, and teamwork:
- "Trio programming" with AI assistance: Our "trio programming" approach—two developers and GitHub Copilot—was a standout success, especially in handling slightly-repetitive but not-quite-exactly-copypaste tasks. Java as a language tends to be verbose and we found it to be fitting particularly well.
- AI tools for reporting and documentation: We extensively used AI chatbots to streamline writing and reporting. (Including writing this report! ...but this note was added manually during edit!)
- GPU compute expertise: Overcoming challenges with CUDA drivers and cloud infrastructure deepened our understanding of GPU-accelerated workloads in the open-source ecosystem.
- Game design as a learning platform: By blending AI techniques with creative game design, we learned not only about AI strategies but also about making games fun, engaging, and balanced.
Last but not least we had a lot of fun! ...and this was definitely not a chatbot generated line!
The Context: AI + Board Games
Integrate Backstage with Rancher Manager by nwmacd
Description
Backstage (backstage.io) is an open-source, CNCF project that allows you to create your own developer portal. There are many plugins for Backstage.
This could be a great compliment to Rancher Manager.
Goals
Learn and experiment with Backstage and look at how this could be integrated with Rancher Manager. Goal is to have some kind of integration completed in this Hack week.
Progress
Screen shot of home page at the end of Hackweek:
Day One
- Got Backstage running locally, understanding configuration with HTTPs.
- Got Backstage embedded in an IFRAME inside of Rancher
- Added content into the software catalog (see: https://backstage.io/docs/features/techdocs/getting-started/)
- Understood more about the entity model
Day Two
- Connected Backstage to the Rancher local cluster and configured the Kubernetes plugin.
- Created Rancher theme to make the light theme more consistent with Rancher
Days Three and Day Four
Created two backend plugins for Backstage:
- Catalog Entity Provider - this imports users from Rancher into Backstage
- Auth Provider - uses the proxied sign-in pattern to check the Rancher session cookie, to user that to authenticate the user with Rancher and then log them into Backstage by connecting this to the imported User entity from the catalog entity provider plugin.
With this in place, you can single-sign-on between Rancher and Backstage when it is deployed within Rancher. Note this is only when running locally for development at present
Day Five
- Start to build out a production deployment for all of the above
- Made some progress, but hit issues with the authentication and proxying when running proxied within Rancher, which needs further investigation
Extending KubeVirtBMC's capability by adding Redfish support by zchang
Description
In Hack Week 23, we delivered a project called KubeBMC (renamed to KubeVirtBMC now), which brings the good old-fashioned IPMI ways to manage virtual machines running on KubeVirt-powered clusters. This opens the possibility of integrating existing bare-metal provisioning solutions like Tinkerbell with virtualized environments. We even received an inquiry about transferring the project to the KubeVirt organization. So, a proposal was filed, which was accepted by the KubeVirt community, and the project was renamed after that. We have many tasks on our to-do list. Some of them are administrative tasks; some are feature-related. One of the most requested features is Redfish support.
Goals
Extend the capability of KubeVirtBMC by adding Redfish support. Currently, the virtbmc component only exposes IPMI endpoints. We need to implement another simulator to expose Redfish endpoints, as we did with the IPMI module. We aim at a basic set of functionalities:
- Power management
- Boot device selection
- Virtual media mount (this one is not so basic )
Resources
Introducing "Bottles": A Proof of Concept for Multi-Version CRD Management in Kubernetes by aruiz
Description
As we delve deeper into the complexities of managing multiple CRD versions within a single Kubernetes cluster, I want to introduce "Bottles" - a proof of concept that aims to address these challenges.
Bottles propose a novel approach to isolating and deploying different CRD versions in a self-contained environment. This would allow for greater flexibility and efficiency in managing diverse workloads.
Goals
- Evaluate Feasibility: determine if this approach is technically viable, as well as identifying possible obstacles and limitations.
- Reuse existing technology: leverage existing products whenever possible, e.g. build on top of Kubewarden as admission controller.
- Focus on Rancher's use case: the ultimate goal is to be able to use this approach to solve Rancher users' needs.
Resources
Core concepts:
- ConfigMaps: Bottles could be defined and configured using ConfigMaps.
- Admission Controller: An admission controller will detect "bootled" CRDs being installed and replace the resource name used to store them.
- Aggregated API Server: By analyzing the author of a request, the aggregated API server will determine the correct bottle and route the request accordingly, making it transparent for the user.
A CLI for Harvester by mohamed.belgaied
[comment]: # Harvester does not officially come with a CLI tool, the user is supposed to interact with Harvester mostly through the UI [comment]: # Though it is theoretically possible to use kubectl to interact with Harvester, the manipulation of Kubevirt YAML objects is absolutely not user friendly. [comment]: # Inspired by tools like multipass from Canonical to easily and rapidly create one of multiple VMs, I began the development of Harvester CLI. Currently, it works but Harvester CLI needs some love to be up-to-date with Harvester v1.0.2 and needs some bug fixes and improvements as well.
Project Description
Harvester CLI is a command line interface tool written in Go, designed to simplify interfacing with a Harvester cluster as a user. It is especially useful for testing purposes as you can easily and rapidly create VMs in Harvester by providing a simple command such as:
harvester vm create my-vm --count 5
to create 5 VMs named my-vm-01
to my-vm-05
.
Harvester CLI is functional but needs a number of improvements: up-to-date functionality with Harvester v1.0.2 (some minor issues right now), modifying the default behaviour to create an opensuse VM instead of an ubuntu VM, solve some bugs, etc.
Github Repo for Harvester CLI: https://github.com/belgaied2/harvester-cli
Done in previous Hackweeks
- Create a Github actions pipeline to automatically integrate Harvester CLI to Homebrew repositories: DONE
- Automatically package Harvester CLI for OpenSUSE / Redhat RPMs or DEBs: DONE
Goal for this Hackweek
The goal for this Hackweek is to bring Harvester CLI up-to-speed with latest Harvester versions (v1.3.X and v1.4.X), and improve the code quality as well as implement some simple features and bug fixes.
Some nice additions might be: * Improve handling of namespaced objects * Add features, such as network management or Load Balancer creation ? * Add more unit tests and, why not, e2e tests * Improve CI * Improve the overall code quality * Test the program and create issues for it
Issue list is here: https://github.com/belgaied2/harvester-cli/issues
Resources
The project is written in Go, and using client-go
the Kubernetes Go Client libraries to communicate with the Harvester API (which is Kubernetes in fact).
Welcome contributions are:
- Testing it and creating issues
- Documentation
- Go code improvement
What you might learn
Harvester CLI might be interesting to you if you want to learn more about:
- GitHub Actions
- Harvester as a SUSE Product
- Go programming language
- Kubernetes API
Remote control for Adam Audio active monitor speakers by dmach
Description
I own a pair of Adam Audio A7V active studio monitor speakers. They have ethernet connectors that allow changing their settings remotely using the A Control software. From Windows :-( I couldn't find any open source alternative for Linux besides AES70.js library.
Goals
- Create a command-line tool for controlling the speakers.
- Python is the language of choice.
- Implement only a simple tool with the desired functionality rather than a full coverage of AES70 standard.
TODO
- ✅ discover the device
- ❌ get device manufacturer and model
- ✅ get serial number
- ✅ get description
- ✅ set description
- ✅ set mute
- ✅ set sleep
- ✅ set input (XRL (balanced), RCA (unbalanced))
- ✅ set room adaptation
- bass (1, 0, -1, -2)
- desk (0, -1, -2)
- presence (1, 0, -1)
- treble (1, 0, -1)
- ✅ set voicing (Pure, UNR, Ext)
- ❌ the Ext voicing enables the following extended functionality:
- gain
- equalizer bands
- on/off
- type
- freq
- q
- gain
- ❌ udev rules to sleep/wakeup the speakers together with the sound card
Resources
- https://www.adam-audio.com/en/a-series/a7v/
- https://www.adam-audio.com/en/technology/a-control-remote-software/
- https://github.com/DeutscheSoft/AES70.js
- https://www.aes.org/publications/standards/search.cfm?docID=101 - paid
- https://www.aes.org/standards/webinars/AESStandardsWebinarSC0212L20220531.pdf
- https://ocaalliance.github.io/downloads/AES143%20Network%20track%20NA10%20-%20AES70%20Controller.pdf
Result
- The code is available on GitHub: https://github.com/dmach/pacontrol