Introduction

TensorFlow™ is an open-source software library for Machine Intelligence written on Python. It was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well. (https://www.tensorflow.org/)

Using values recorded by SUSE Manager it should be possible to predict the outcome of certain operations if machine learning is applied. We are especially interested in the time it takes to apply patches to systems. With anecdotal values a neural network should be trained to predict this for future operations. We need do find out which values can and should be provided, which classifier(s) to use, aso.

Goals:

  • Monday:

    • Learn about Tensorflow: Definitions, how to create a model, different frameworks, etc
    • Define set of features that can be gathered from the SUSE Manager DB to create our dataset.
    • Explore the values of the dataset: Know about min-max values, boundaries, type of data (categorical, continuous).
    • Define crossed relation between data (crossed columns).
    • Is our dataset good enough?
  • Tuesday:

    • Create and test different tensorflow models: DNNCombinedLinearClassifier, DNNClassifier, etc
    • Are those models' estimations good enough?
    • Is tensorflow suitable for achiving the project goal? are estimation good enough for us?
    • Upload working example.

Outcomes:

  • Initial dataset was not really good. We modified the SQL query to collect also package ids.
  • In the past we restricted the dataset to only contain actions for erratas which only contains one package, but the resulting dataset was not big enough.
  • We implemented a DNNRegressor.
  • Dataset: COLUMNS = ["server_id","errata_id","nrcpu","mhz","ram","package_id","size","time"] (we only currently use server_id, errata_id, package_id)
  • Currently the dataset is based patch installation actions which contains only a one single errata but this errata can have multiple packages associated.
  • We don't know the installation time for a package, because the "time" data we have is for the complete action, so we do a very draft estimation just dividing the total time by the number of packages the errata contains.
  • Estimations seems to be good enough, of course, the database still needs to be improved as well as the model itself where the feature columns definition can be adjusted to get better results.
  • Current estimations are good enough to, at least, give an estimation saying if the action you're planning is going to take less than ~10 seconds, ~30 seconds, ~1 minute, ~5 minutes, etc.

Some samples of estimations:

expected -> estimated

0.233874837557475 -> 0.230502188205719
0.233874837557475 -> 0.25423765182495117
0.233874837557475 -> 0.1823016107082367
0.979458148662861 -> 0.8299890756607056
0.979458148662861 -> 0.8462812900543213
0.211660345395406 -> 0.22346541285514832
1.70577935377757 -> 1.9606330394744873
2.60000002384186 -> 2.39455509185791
0.976182460784912 -> 0.1866598129272461
0.976182460784912 -> 0.614652693271637
2.80241966247559 -> 1.0975050926208496
0.6621074676513671 -> 0.6865990161895752
0.0968895809991019 -> 0.041620612144470215
0.0968895809991019 -> 0.1236574649810791
0.0968895809991019 -> 0.05707252025604248
1.3669094741344499 -> 2.2393956184387207
1.3669094741344499 -> 2.2393956184387207

"Actual" vs "Predicted" screenshots:

Screenshot1

Full graph: view full graph here

Next steps:

  • Refinement of model and dataset
  • Add actions with multiple errata to the dataset
  • Implement also a DNNClassifier to directly classifing instead of getting a float number (possible classes: seconds, minutes, hours).
  • POC of integration with the SUSE Manager UI
  • Refeed the neural network with the actual results of the new actions on SUSE Manager.
  • Replace package_id with something consistent across customers (eg: package name)
  • Try to find a way to avoid averaging the time per package on erratas that point to multiple packages
  • Estimate the actual action (not per package)

Code repository: Internal GitLab

Looking for hackers with the skills:

tensorflow python machinelearning susemanager

This project is part of:

Hack Week 16

Activity

  • over 6 years ago: bfilho liked this project.
  • about 7 years ago: j_renner liked this project.
  • about 7 years ago: PSuarezHernandez added keyword "tensorflow" to this project.
  • about 7 years ago: PSuarezHernandez added keyword "python" to this project.
  • about 7 years ago: PSuarezHernandez added keyword "machinelearning" to this project.
  • about 7 years ago: PSuarezHernandez added keyword "susemanager" to this project.
  • about 7 years ago: mdinca liked this project.
  • about 7 years ago: dmaiocchi liked this project.
  • about 7 years ago: dmaiocchi disliked this project.
  • about 7 years ago: dmaiocchi liked this project.
  • about 7 years ago: mdinca joined this project.
  • about 7 years ago: PSuarezHernandez liked this project.
  • about 7 years ago: jochenbreuer joined this project.
  • about 7 years ago: PSuarezHernandez started this project.
  • about 7 years ago: PSuarezHernandez originated this project.

  • Comments

    • PSuarezHernandez
      about 7 years ago by PSuarezHernandez | Reply

      The outcomes from this HW project has been published!! The project page has been updated to include the results!

    Similar Projects

    Make more sense of openQA test results using AI by livdywan

    Description

    AI has the potential to help with something many of us spend a lot of time doing which is making sense of openQA logs when a job fails.

    User Story

    Allison Average has a puzzled look on their face while staring at log files that seem to make little sense. Is this a known issue, something completely new or maybe related to infrastructure changes?

    Goals

    • Leverage a chat interface to help Allison
    • Create a model from scratch based on data from openQA
    • Proof of concept for automated analysis of openQA test results

    Bonus

    • Use AI to suggest solutions to merge conflicts
      • This would need a merge conflict editor that can suggest solving the conflict
    • Use image recognition for needles

    Resources

    Timeline

    Day 1

    • Conversing with open-webui to teach me how to create a model based on openQA test results

    Day 2

    Highlights

    • I briefly tested compared models to see if they would make me more productive. Between llama, gemma and mistral there was no amazing difference in the results for my case.
    • Convincing the chat interface to produce code specific to my use case required very explicit instructions.
    • Asking for advice on how to use open-webui itself better was frustratingly unfruitful both in trivial and more advanced regards.
    • Documentation on source materials used by LLM's and tools for this purpose seems virtually non-existent - specifically if a logo can be generated based on particular licenses

    Outcomes

    • Chat interface-supported development is providing good starting points and open-webui being open source is more flexible than Gemini. Although currently some fancy features such as grounding and generated podcasts are missing.
    • Allison still has to be very experienced with openQA to use a chat interface for test review. Publicly available system prompts would make that easier, though.


    ClusterOps - Easily install and manage your personal kubernetes cluster by andreabenini

    Description

    ClusterOps is a Kubernetes installer and operator designed to streamline the initial configuration and ongoing maintenance of kubernetes clusters. The focus of this project is primarily on personal or local installations. However, the goal is to expand its use to encompass all installations of Kubernetes for local development purposes.
    It simplifies cluster management by automating tasks and providing just one user-friendly YAML-based configuration config.yml.

    Overview

    • Simplified Configuration: Define your desired cluster state in a simple YAML file, and ClusterOps will handle the rest.
    • Automated Setup: Automates initial cluster configuration, including network settings, storage provisioning, special requirements (for example GPUs) and essential components installation.
    • Ongoing Maintenance: Performs routine maintenance tasks such as upgrades, security updates, and resource monitoring.
    • Extensibility: Easily extend functionality with custom plugins and configurations.
    • Self-Healing: Detects and recovers from common cluster issues, ensuring stability, idempotence and reliability. Same operation can be performed multiple times without changing the result.
    • Discreet: It works only on what it knows, if you are manually configuring parts of your kubernetes and this configuration does not interfere with it you can happily continue to work on several parts and use this tool only for what is needed.

    Features

    • distribution and engine independence. Install your favorite kubernetes engine with your package manager, execute one script and you'll have a complete working environment at your disposal.
    • Basic config approach. One single config.yml file with configuration requirements (add/remove features): human readable, plain and simple. All fancy configs managed automatically (ingress, balancers, services, proxy, ...).
    • Local Builtin ContainerHub. The default installation provides a fully configured ContainerHub available locally along with the kubernetes installation. This configuration allows the user to build, upload and deploy custom container images as they were provided from external sources. Internet public sources are still available but local development can be kept in this localhost server. Builtin ClusterOps operator will be fetched from this ContainerHub registry too.
    • Kubernetes official dashboard installed as a plugin, others planned too (k9s for example).
    • Kubevirt plugin installed and properly configured. Unleash the power of classic virtualization (KVM+QEMU) on top of Kubernetes and manage your entire system from there, libvirtd and virsh libs are required.
    • One operator to rule them all. The installation script configures your machine automatically during installation and adds one kubernetes operator to manage your local cluster. From there the operator takes care of the cluster on your behalf.
    • Clean installation and removal. Just test it, when you are done just use the same program to uninstall everything without leaving configs (or pods) behind.

    Planned features (Wishlist / TODOs)

    • Containerized Data Importer (CDI). Persistent storage management add-on for Kubernetes to provide a declarative way of building and importing Virtual Machine Disks on PVCs for


    Make more sense of openQA test results using AI by livdywan

    Description

    AI has the potential to help with something many of us spend a lot of time doing which is making sense of openQA logs when a job fails.

    User Story

    Allison Average has a puzzled look on their face while staring at log files that seem to make little sense. Is this a known issue, something completely new or maybe related to infrastructure changes?

    Goals

    • Leverage a chat interface to help Allison
    • Create a model from scratch based on data from openQA
    • Proof of concept for automated analysis of openQA test results

    Bonus

    • Use AI to suggest solutions to merge conflicts
      • This would need a merge conflict editor that can suggest solving the conflict
    • Use image recognition for needles

    Resources

    Timeline

    Day 1

    • Conversing with open-webui to teach me how to create a model based on openQA test results

    Day 2

    Highlights

    • I briefly tested compared models to see if they would make me more productive. Between llama, gemma and mistral there was no amazing difference in the results for my case.
    • Convincing the chat interface to produce code specific to my use case required very explicit instructions.
    • Asking for advice on how to use open-webui itself better was frustratingly unfruitful both in trivial and more advanced regards.
    • Documentation on source materials used by LLM's and tools for this purpose seems virtually non-existent - specifically if a logo can be generated based on particular licenses

    Outcomes

    • Chat interface-supported development is providing good starting points and open-webui being open source is more flexible than Gemini. Although currently some fancy features such as grounding and generated podcasts are missing.
    • Allison still has to be very experienced with openQA to use a chat interface for test review. Publicly available system prompts would make that easier, though.


    Team Hedgehogs' Data Observability Dashboard by gsamardzhiev

    Description

    This project aims to develop a comprehensive Data Observability Dashboard that provides r insights into key aspects of data quality and reliability. The dashboard will track:

    Data Freshness: Monitor when data was last updated and flag potential delays.

    Data Volume: Track table row counts to detect unexpected surges or drops in data.

    Data Distribution: Analyze data for null values, outliers, and anomalies to ensure accuracy.

    Data Schema: Track schema changes over time to prevent breaking changes.

    The dashboard's aim is to support historical tracking to support proactive data management and enhance data trust across the data function.

    Goals

    Although the final goal is to create a power bi dashboard that we are able to monitor, our goals is to 1. Create the necessary tables that track the relevant metadata about our current data 2. Automate the process so it runs in a timely manner

    Resources

    AWS Redshift; AWS Glue, Airflow, Python, SQL

    Why Hedgehogs?

    Because we like them.


    Saline (state deployment control and monitoring tool for SUSE Manager/Uyuni) by vizhestkov

    Project Description

    Saline is an addition for salt used in SUSE Manager/Uyuni aimed to provide better control and visibility for states deploymend in the large scale environments.

    In current state the published version can be used only as a Prometheus exporter and missing some of the key features implemented in PoC (not published). Now it can provide metrics related to salt events and state apply process on the minions. But there is no control on this process implemented yet.

    Continue with implementation of the missing features and improve the existing implementation:

    • authentication (need to decide how it should be/or not related to salt auth)

    • web service providing the control of states deployment

    Goal for this Hackweek

    • Implement missing key features

    • Implement the tool for state deployment control with CLI

    Resources

    https://github.com/openSUSE/saline


    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 and Salt-ssh clients, but NOT traditional clients, which are deprecated.

    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):

    1. Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)
    2. 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)
    3. Package management (install, remove, update...)
    4. Patching
    5. Applying any basic salt state (including a formula)
    6. Salt remote commands
    7. Bonus point: Java part for product identification, and monitoring enablement
    8. Bonus point: sumaform enablement (https://github.com/uyuni-project/sumaform)
    9. Bonus point: Documentation (https://github.com/uyuni-project/uyuni-docs)
    10. 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 :-)

    Pending

    FUSS

    FUSS is a complete GNU/Linux solution (server, client and desktop/standalone) based on Debian for managing an educational network.

    https://fuss.bz.it/

    Seems to be a Debian 12 derivative, so adding it could be quite easy.

    • [W] Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)
    • [W] Onboarding (salt minion from UI, salt minion from bootstrap script, and salt-ssh minion) (this will probably require adding OS to the bootstrap repository creator) --> Working for all 3 options (salt minion UI, salt minion bootstrap script and salt-ssh minion from the UI).
    • [W] Package management (install, remove, update...) --> Installing a new package works, needs to test the rest.
    • [I] Patching (if patch information is available, could require writing some code to parse it, but IIRC we have support for Ubuntu already). No patches detected. Do we support patches for Debian at all?
    • [W] Applying any basic salt state (including a formula)
    • [W] Salt remote commands
    • [ ] Bonus point: Java part for product identification, and monitoring enablement


    FamilyTrip Planner: A Personalized Travel Planning Platform for Families by pherranz

    Description

    FamilyTrip Planner is an innovative travel planning application designed to optimize travel experiences for families with children. By integrating APIs for flights, accommodations, and local activities, the app generates complete itineraries tailored to each family’s unique interests and needs. Recommendations are based on customizable parameters such as destination, trip duration, children’s ages, and personal preferences. FamilyTrip Planner not only simplifies the travel planning process but also offers a comprehensive, personalized experience for families.

    Goals

    This project aims to: - Create a user-friendly platform that assists families in planning complete trips, from flight and accommodation options to recommended family-friendly activities. - Provide intelligent, personalized travel itineraries using artificial intelligence to enhance travel enjoyment and minimize time and cost. - Serve as an educational project for exploring Go programming and artificial intelligence, with the goal of building proficiency in both.

    Resources

    To develop FamilyTrip Planner, the project will leverage: - APIs such as Skyscanner, Google Places, and TripAdvisor to source real-time information on flights, accommodations, and activities. - Go programming language to manage data integration, API connections, and backend development. - Basic machine learning libraries to implement AI-driven itinerary suggestions tailored to family needs and preferences.


    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 and Salt-ssh clients, but NOT traditional clients, which are deprecated.

    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):

    1. Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)
    2. 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)
    3. Package management (install, remove, update...)
    4. Patching
    5. Applying any basic salt state (including a formula)
    6. Salt remote commands
    7. Bonus point: Java part for product identification, and monitoring enablement
    8. Bonus point: sumaform enablement (https://github.com/uyuni-project/sumaform)
    9. Bonus point: Documentation (https://github.com/uyuni-project/uyuni-docs)
    10. 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 :-)

    Pending

    FUSS

    FUSS is a complete GNU/Linux solution (server, client and desktop/standalone) based on Debian for managing an educational network.

    https://fuss.bz.it/

    Seems to be a Debian 12 derivative, so adding it could be quite easy.

    • [W] Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)
    • [W] Onboarding (salt minion from UI, salt minion from bootstrap script, and salt-ssh minion) (this will probably require adding OS to the bootstrap repository creator) --> Working for all 3 options (salt minion UI, salt minion bootstrap script and salt-ssh minion from the UI).
    • [W] Package management (install, remove, update...) --> Installing a new package works, needs to test the rest.
    • [I] Patching (if patch information is available, could require writing some code to parse it, but IIRC we have support for Ubuntu already). No patches detected. Do we support patches for Debian at all?
    • [W] Applying any basic salt state (including a formula)
    • [W] Salt remote commands
    • [ ] Bonus point: Java part for product identification, and monitoring enablement


    Improve Development Environment on Uyuni by mbussolotto

    Description

    Currently create a dev environment on Uyuni might be complicated. The steps are:

    • add the correct repo
    • download packages
    • configure your IDE (checkstyle, format rules, sonarlint....)
    • setup debug environment
    • ...

    The current doc can be improved: some information are hard to be find out, some others are completely missing.

    Dev Container might solve this situation.

    Goals

    Uyuni development in no time:

    • using VSCode:
      • setting.json should contains all settings (for all languages in Uyuni, with all checkstyle rules etc...)
      • dev container should contains all dependencies
      • setup debug environment
    • implement a GitHub Workspace solution
    • re-write documentation

    Lots of pieces are already implemented: we need to connect them in a consistent solution.

    Resources

    • https://github.com/uyuni-project/uyuni/wiki


    Create SUSE Manager users from ldap/ad groups by mbrookhuis

    Description

    This tool is used to create users in SUSE Manager Server based on LDAP/AD groups. For each LDAP/AD group a role within SUSE Manager Server is defined. Also, the tool will check if existing users still have the role they should have, and, if not, it will be corrected. The same for if a user is disabled, it will be enabled again. If a users is not present in the LDAP/AD groups anymore, it will be disabled or deleted, depending on the configuration.

    The code is written for Python 3.6 (the default with SLES15.x), but will also work with newer versions. And works against SUSE Manger 4.3 and 5.x

    Goals

    Create a python and/or golang utility that will manage users in SUSE Manager based on LDAP/AD group-membership. In a configuration file is defined which roles the members of a group will get.

    Table of contents

    Installation

    To install this project, perform the following steps:

    • Be sure that python 3.6 is installed and also the module python3-PyYAML. Also the ldap3 module is needed:

    bash zypper in python3 python3-PyYAML pip install yaml

    • On the server or PC, where it should run, create a directory. On linux, e.g. /opt/sm-ldap-users

    • Copy all the file to this directory.

    • Edit the configsm.yaml. All parameters should be entered. Tip: for the ldap information, the best would be to use the same as for SSSD.

    • Be sure that the file sm-ldap-users.py is executable. It would be good to change the owner to root:root and only root can read and execute:

    bash chmod 600 * chmod 700 sm-ldap-users.py chown root:root *

    Usage

    This is very simple. Once the configsm.yaml contains the correct information, executing the following will do the magic:

    bash /sm-ldap-users.py

    repository link

    https://github.com/mbrookhuis/sm-ldap-users


    Saline (state deployment control and monitoring tool for SUSE Manager/Uyuni) by vizhestkov

    Project Description

    Saline is an addition for salt used in SUSE Manager/Uyuni aimed to provide better control and visibility for states deploymend in the large scale environments.

    In current state the published version can be used only as a Prometheus exporter and missing some of the key features implemented in PoC (not published). Now it can provide metrics related to salt events and state apply process on the minions. But there is no control on this process implemented yet.

    Continue with implementation of the missing features and improve the existing implementation:

    • authentication (need to decide how it should be/or not related to salt auth)

    • web service providing the control of states deployment

    Goal for this Hackweek

    • Implement missing key features

    • Implement the tool for state deployment control with CLI

    Resources

    https://github.com/openSUSE/saline