USC-C General Assembly - Trieste

Training courses

During the USC-C meeting there will be room also for certified training courses.

The list of Topics includes courses about:

• Proxmox

  • The presentation provides an overview of the Proxmox Virtual Environment in the context of the evolution of virtualization platforms. After a brief historical overview, the ecosystem composition and the current status of the project will be described, highlighting its maturity and deployment. The platform's main features will then be analyzed, including live virtual machine migration (vmotion), storage migration, SDN integration, firewalling capabilities, and user management. A section will be dedicated to supported storage architectures: local storage, shared external storage, and hyperconverged solutions. Proxmox will also be compared with VMware and other virtualization solutions, discussing architectural differences, the licensing model, and V2V migration options. Other products in the Proxmox ecosystem will be presented, including Proxmox Backup Server (PBS), Proxmox Datacenter Manager (PDM), Proxmox Offline Mirror (POM), and Proxmox Mail Gateway (PMG), along with integration with third-party solutions. Finally, the development roadmap, some typical use cases, and a practical demo to demonstrate the main features in a real-world scenario will be illustrated.

• Machine Learning (basic course)
  • This introductory lecture aims to provide astrophysicists with a foundational understanding of Machine Learning (ML) concepts, tools, and applications relevant to modern astronomical research. In the era of increasingly large and complex datasets from surveys and simulations, ML techniques are becoming indispensable for discovery and analysis.
    We are going to cover the core paradigms of Machine Learning, focusing on Supervised Learning (e.g., classification of transient events and photometric redshift estimation) and Unsupervised Learning (e.g., clustering of galaxies and anomaly detection in time series data). The session introduces some algorithms, highlighting their main characteristics and typical applications. It also explores the general workflow of a machine learning project, including data collection, model training, evaluation, and deployment.
    The goal is to equip astrophysicists with the conceptual tools needed to critically assess and effectively apply machine learning methods in their own research.
• Virtual Observatory tools and services
  • An introduction to the IVOA: overview about the VO standards, how they are connected, and how they are connected to the Working Groups. The goal is to make it easier for newcomers to understand IVOA jargon and to get into the work flow of the VO activities. A first part of the tutorial will introduce to some of the VO standards following a use case from the user's perspective.
    A second part will show selected steps of the use case from the perspective of the data provider: what is needed from the data provider to enable the user experience of the first part?
• DevOps

  • DevOps is a modern approach to software development that integrates development and operations practices with the goal of improving collaboration, accelerating software delivery, and increasing the reliability and quality of software systems. DevOps addresses the limitations of traditional development models by promoting automation, continuous feedback, and shared responsibility.

    This course provides an introductory overview of DevOps, focusing on its core principles and on how these principles are applied within a project managed with GitLab. Participants will explore what DevOps is, why it has become an essential approach in contemporary software engineering, and which are the main tools commonly used in DevOps workflows.

    Within this framework, the course illustrates how DevOps supports continuous integration, continuous delivery, automation, and quality assurance throughout the entire software lifecycle. The session concludes with a discussion of typical DevOps workflows and practical case examples from the ASTRI and CTAO collaborations.

• Quantum Computing
  • This course provides an introduction to Quantum Computing, combining fundamental theory and modern applications. It begins with the basics of quantum mechanics, essential for understanding quantum information concepts. The course then introduces Quantum Fourier Transform (QFT) as a framework for describing complex quantum systems, followed by an overview of Quantum Machine Learning (QML) and its potential for data analysis and pattern recognition. The course concludes with quantum optimisation, focusing on optimization problems and hybrid quantum–classical approaches.
• Databases
  • The common modus operandi in astrophysical research is to recycle knowledge already acquired and shared within a single team. Too little attention is given to the discovery of new technologies to better fulfill project specifications and requirements unless a technological limit is reached during any testing use-case.
    Although the Database Management System (DBMS) is the backbone on which astronomical archives are based, the choice of the best suited DB for scientists' needs often comes up against the need to put into operation a testing prototypes, so the search for an improved technology is simply bypassed in favor of a solution already known and mastered.
    In this course we will try to make a general theorical excursus on different kinds of DBMS, related tool and show possible approaches to consciously make the best technology choice for the astronomical project, or in case, adopt a new database paradigm called “Polyglot Persistence”, where different DB solutions are joined together within a common archive ecosystem. The Polyglot Persistence focus on atomic services identified by data providers and data consumer and build the service adaptively to match the data management and access requirements.
• APRE
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• XEN 
  • This session is designed to provide IT professionals with the essential skills to excel in using the XCP-ng hypervisor and the Xen Orchestra Appliance within the Vates Virtualization Management Stack (VMS). This training session is designed to provide you with the following key skills and knowledge.
    • Master the fundamentals of the XCP-ng virtualization platform:
      • Build a solid foundation of knowledge of the key features and functionality of the XCP-ng hypervisor.
    •  Gain proficiency in using the Xen Orchestra Appliance:
      • Learn to efficiently use Xen Orchestra for seamless virtualization management and monitoring.
    • Discover best practices for managing and deploying virtualized environments: Learn how to achieve optimal performance and reliability in your virtual infrastructure.
    • Develop the foundational skills for effective virtualization management:
      • Acquire the essential skills needed to effectively manage and scale virtual environments, laying the foundation for advanced data center virtualization expertise. By the end of this course, you will have acquired the tools to manage the challenges of modern virtualization environments with confidence and expertise.

 

A special talk on Networking will be held in a dedicated session, in this last case no valid for mandatory training certification will be released.

 

The schedule is almost finalized, but last minute changes in timing could happen. We will try to be conservative on the day of the week, but shift in session sequence could be necessary. Please stay tuned on the Timetable!!