Abstract
In modern data centres an effective and efficient monitoring system is a critical asset, yet a continuous concern for administrators. Since its birth, INFN Tier-1 data centre, hosted at CNAF, has used various monitoring tools all replaced, a few years ago, by a system common to all CNAF departments (based on Sensu, Influxdb, Grafana). Given the complexity of the inter-dependencies of the several services running at the data centre and the foreseen large increase of resources in the near future, a more powerful and versatile monitoring system is needed. This new monitoring system should be able to automatically correlate log files and metrics coming from heterogeneous sources and devices (including services, hardware and infrastructure) thus providing us with a suitable framework to implement a solution for the predictive analysis of the status of the whole environment. In particular, the possibility to correlate IT infrastructure monitoring information with the logs of running applications is of great relevance in order to be able to quickly find application failure root cause. At the same time, a modern, flexible and user-friendly analytics solution is needed in order to enable users, IT engineers and IT managers to extract valuable information from the different sources of collected data in a timely fashion. In this paper, a prototype of such a system, installed at the INFN Tier-1, is described with an assessment of the state and an evaluation of the resources needed for a fully production system. Technologies adopted, amount of foreseen data, target KPIs and production design are illustrated.
Highlights
Maintenance is the process of preserving or restoring the good operating conditions of a system
INFN-CNAF’s Tier-1 site is the major Italian data centre in the Worldwide LHC Computing Grid1 (WLCG). This data centre features 40,000 CPU cores, 40 PB of disk storage, 90 PB of tape storage, and it is connected to the Italian (GARR) 2 and European (GEANT) 3 research network infrastructure with more than 200 Gbps. In such a scenario, adopting a predictive maintenance approach would allow INFN saving costs deriving from downtime or unnecessary hardware replacement
Log files may refer to system processes and services as well as log files produced by the HEP experiments running on the nodes
Summary
Maintenance is the process of preserving or restoring the good operating conditions of a system. It is an expensive approach, since many hardware components could have a longer life and are instead replaced due to a scheduled intervention This motivates the approach known as conditionbased maintenance: the continuous monitoring of a set of measurements can highlight abnormal behaviors, allowing the administrator to perform a maintenance intervention before a fault occurs [1]. This data centre features 40,000 CPU cores, 40 PB of disk storage, 90 PB of tape storage, and it is connected to the Italian (GARR) 2 and European (GEANT) 3 research network infrastructure with more than 200 Gbps In such a scenario, adopting a predictive maintenance approach would allow INFN saving costs deriving from downtime ( providing a better service) or unnecessary hardware replacement.
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