001046529 001__ 1046529
001046529 005__ 20250924202050.0
001046529 037__ $$aFZJ-2025-03852
001046529 041__ $$aEnglish
001046529 1001_ $$0P:(DE-Juel1)128666$$aBruns, Benjamin$$b0$$ufzj
001046529 1112_ $$a5th conference for Research Software Engineering in Germany (deRSE25)$$cKarlsruhe$$d2025-02-25 - 2025-03-01$$gdeRSE25$$wGermany
001046529 245__ $$aModernizing Legacy Infrastructure Monitoring: Enhancing Performance with Prometheus and GitLab CI/CD
001046529 260__ $$c2025
001046529 3367_ $$033$$2EndNote$$aConference Paper
001046529 3367_ $$2BibTeX$$aINPROCEEDINGS
001046529 3367_ $$2DRIVER$$aconferenceObject
001046529 3367_ $$2ORCID$$aCONFERENCE_POSTER
001046529 3367_ $$2DataCite$$aOutput Types/Conference Poster
001046529 3367_ $$0PUB:(DE-HGF)24$$2PUB:(DE-HGF)$$aPoster$$bposter$$mposter$$s1758693878_23085$$xOther
001046529 500__ $$ahttps://zenodo.org/records/14982650
001046529 520__ $$aEffective monitoring of (computing) infrastructure, especially in complex systems with various dependencies, is crucial for ensuring high availability and early detection of performance issues. This poster demonstrates the integration of Prometheus and GitLab CI/CD to modernize our existing infrastructure monitoring methods. As infrastructure checks increase, our legacy monitoring system faces growing challenges such as performance bottlenecks, limited scalability, and maintenance difficulties. Prometheus, with its real-time monitoring and alerting capabilities, offers a scalable and flexible solution. It supports both horizontal and vertical scaling, efficient data storage, and a modular architecture that facilitates the seamless integration of various existing monitoring tools, such as specialized exporters.Using Prometheus as our backend involves setting up a containerized system, creating data sources and targets, and configuring (custom) metrics and alerts. The use of GitLab’s CI/CD pipeline further automates the building, deployment and testing processes. Additionally, Grafana, when used alongside Prometheus, provides a robust visualization tool to display statistics and reports, such as CPU and GPU usage or file quotas. This approach not only enhances efficiency and ensures timely alerts for potential issues but also keeps the monitoring system up-to-date and resilient. It also provides users with valuable statistics through a modern and flexible backend. Furthermore, containerizing the new monitoring system offers significant advantages, including portability, scalability, and modularization.The poster presents selected infrastructure systems, directly comparing the usability and performance of our legacy script-based monitoring system and the new Prometheus-based monitoring system.
001046529 536__ $$0G:(DE-HGF)POF4-5112$$a5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001046529 8564_ $$uhttps://events.hifis.net/event/1741/contributions/14046/
001046529 909CO $$ooai:juser.fz-juelich.de:1046529$$pVDB
001046529 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)128666$$aForschungszentrum Jülich$$b0$$kFZJ
001046529 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5112$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
001046529 9141_ $$y2025
001046529 920__ $$lyes
001046529 9201_ $$0I:(DE-Juel1)IAS-8-20210421$$kIAS-8$$lDatenanalyse und Maschinenlernen$$x0
001046529 980__ $$aposter
001046529 980__ $$aVDB
001046529 980__ $$aI:(DE-Juel1)IAS-8-20210421
001046529 980__ $$aUNRESTRICTED