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INFN-CNAF is one of the Worldwide LHC Computing Grid (WLCG) Tier-1 data centres, providing computing, networking and storage resources to a wide variety of scientific collaborations, not limited to the four LHC (Large Hadron Collider) experiments. The INFN-CNAF data centre will move to a new location next year. At the same time, the requirements from our experiments and users are becoming increasingly challenging and new scientific communities have started or will soon start exploiting our resources. Currently, we are reengineering several services, in particular our monitoring infrastructure, in order to improve the day-by-day operations and to cope with the increasing complexity of the use cases and with the future expansion of the centre. This scenario led us to implement a data streaming infrastructure designed to enable log analysis, anomaly detection, threat hunting, integrity monitoring and incident response. Such data streaming platform has been organised to manage different kinds of data coming from heterogeneous sources, to support multi-tenancy and to be scalable. Moreover, we will be able to provide an on demand end-to-end data streaming application to those users/communities requesting such kind of facility. The infrastructure is based on the Apache Kafka platform, which provides streaming of events at large scale, with authorization and authentication configured at the topic level for ensuring data isolation and protection. Data can be consumed by different applications, such as those devoted to log analysis, which provide the capability to index large amounts of data and implement appropriate access policies to inspect and visualise information. In this contribution we will present and motivate our technological choices for the definition of the infrastructure, we will describe its components and we will depict use cases which can be addressed with this platform.

The Italian WLCG Tier-1 located in Bologna and managed by INFN-CNAF has a long tradition in supporting several research communities in the fields of High-Energy Physics, Astroparticle Physics, Gravitational Waves, Nuclear Physics and others, to which provides computing resources in the form of batch computing, both HPC, HTC and Cloud, and storage. Although the LHC experiments at CERN represent the main users of the Tier-1 resources, an increasing number of communities and experiments are also being supported in all of their computing activities. Due to this demanding user base, an efficient support system is needed in order to assure a smooth and appropriate exploitation of the computing infrastructure. In this framework, such a role is played by the Tier-1 User Support group, which acts as the entry point for services, support requests, and problem reports. The group makes use of multiple systems to meet the different needs and specificities of the supported experiments. Moreover, the group continuously maintains detailed knowledge base in the form of an on-line user guide and develops tools to advertise specific information about the services available to the communities in a form that is easy to access and use. The communication channels are represented by ticketing systems and also by mailing lists used for a more direct communication, allowing to promptly notify maintenance interventions, downtimes and more in general all the new features and services provided by the center. In this paper, the ticketing systems, tools, platforms and services that User Support offers, and the internal organization of the department will be described. Future workflow plans in view of the DATACLOUD project, which will require an increasing effort, will also be presented.

INFN has been running a distributed infrastructure (the Tier-1 at Bologna-CNAF and 9 Tier-2 centres) for more than 20 years which currently offers about 150000 CPU cores and 120 PB of space both in tape and disk storage, serving more than 40 international scientific collaborations. This Grid-based infrastructure was augmented in 2019 with the INFN Cloud: a production quality multi-site federated Cloud infrastructure, composed by a core backbone, and which is able to integrate other INFN sites and public or private Clouds as well. The INFN Cloud provides a customizable and extensible portfolio offering computing and storage services spanning the IaaS, PaaS and SaaS layers, with dedicated solutions to serve special purposes, such as ISO-certified regions for the handling of sensitive data. INFN is now revising and expanding its infrastructure to tackle the challenges expected in the next 10 years of scientific computing adopting a “cloud-first” approach, through which all the INFN data centres will be federated via the INFN Cloud middleware and integrated with key HPC centres, such as the pre-exascale Leonardo machine at CINECA. In such a process, which involves both the infrastructures and the higher level services, initiatives and projects such as the "Italian National Centre on HPC, Big Data and Quantum Computing" (funded in the context of the Italian "National Recovery and Resilience Plan") and the Bologna Technopole are precious opportunities that will be exploited to offer advanced resources and services to universities, research institutions and industry. In this paper we describe how INFN is evolving its computing infrastructure, with the ambition to create and operate a national vendorneutral, open, scalable, and flexible "datalake" able to serve much more than just INFN users and experiments.

INFN-CNAF is one of the Worldwide Large Hadron Collider Computing Grid (WLCG) Tier-1 data centers, providing support in terms of computing, networking, storage resources and services also to a wide variety of scientific collaborations, ranging from physics to bioinformatics and industrial engineering [1]. Recently, several collaborations working with our data center have developed computing and data management workflows that require access to S3 storage services and/or the integration with POSIX capabilities. Nevertheless, the access to the data must be regulated by federated authentication and authorization mechanisms, such as OpenID Connect (OIDC), which is largely adopted by communities like WLCG [2] and within the European Open Science Cloud (EOSC) [3]. In the present work, the possibility to regulate POSIX access by integrating JSON Web Token (JWT) [4] authentication, provided by INDIGO-IAM as Identity Provider [5], with solutions based on S3 (for object storage) and WebDAV (for hierarchical storage) protocols has been evaluated an related results have been reported. In such respect, a comparison between the performance yielded by S3 and WebDAV protocols has been carried out within the same distributed environment with the aim to better identify the solution most suitable for the different use cases.

In the latest years, CNAF (the national center of the Italian Institute for Nuclear Physics INFN dedicated to Research and Development on Information and Communication Technologies) has been working on the Long Term Data Preservation (LTDP) project for the CDF experiment, active at Fermilab from 1990 to 2011. The main aims of the project are to protect the most relevant part of the CDF RUN-2 data collected between 2001 and 2011 and already stored on tape at CNAF (4 PB), as well as to ensure the availability and the access to the analysis facility to those data over time. Lately, the CDF database, hosting information about CDF datasets such as their structure, file locations and metadata, has been imported from Fermilab to CNAF. Also, the Sequential Access via Metadata (SAM) station data handling tool for CDF data management, that allows to manage data transfers and to retrieve information from the CDF database, has been properly installed and configured at CNAF. This was a fundamental step in the perspective of a complete decommissioning of CDF services on Fermilab side. An access system has been designed and tested to submit CDF analysis jobs, using CDF software distributed via CERN Virtual Machine File System (CVMFS) and requesting delivery of CDF files stored on CNAF tapes, as well as data present only on Fermilab storage archive. Moreover, the availability and the correctness of all CDF data stored on CNAF tapes has been verified. This paper describes all these recent evolutions in detail, presenting the future plans for the LTDP project at CNAF.

Background: Heart diseases due to iron overload are still the main cause of mortality in patients affected by beta-thalassemia. Detection of cardiac iron overload in pre-clinical stage allows tailoring of chelation therapy and follow-up strategies. Echocardiographic longitudinal strain analysis may be a useful tool for early detection of cardiac functional impairment iron-related., Methods: We examined 58 patients with beta-thalassemia on regular blood transfusion and iron chelation, without overt cardiac disease who had recent Biosusceptometry SQUID to quantify liver iron concentration and cardiac assessment by CMR T2*., Results: Average global longitudinal strain (GLS) was able to identify abnormal (<20 ms) cardiac T2* values with 96% specificity and negative predictive value of 92% (AUC 0.84, P=0.01). Apical 4-ch GLS may help identify early longitudinal impairment associated with severe liver iron overload with 96% specificity and negative predictive value of 92% (AUC 0.84, P=0.02). Patients with severe liver iron overload had lower average Global Longitudinal Strain values compared to other patients ( P -value =0.005)., Conclusion: GLS was a sensitive marker to detect both myocardial and liver iron overload in a population that is still free from cardiac symptoms. Thus, strain echocardiography may be a useful tool for early detection of iron overload in Beta-thalassemia., Competing Interests: None., (AJCD Copyright © 2021.)