Building an Open-Source Platform-as-a-Service with Intelligent Management of Multiple Cloud Resources

Author(s):  
Calin Sandru ◽  
Dana Petcu ◽  
Victor Ion Munteanu
2019 ◽  
Vol 214 ◽  
pp. 08031 ◽  
Author(s):  
Alberto Aimar ◽  
Asier Aguado Corman ◽  
Pedro Andrade ◽  
Javier Delgado Fernandez ◽  
Borja Garrido Bear ◽  
...  

The new unified monitoring architecture (MONIT) for the CERN Data Centres and for the WLCG Infrastructure is based on established open source technologies to collect, stream, store and access monitoring data. The previous solutions, based on in-house development and commercial software, have been replaced with widely- recognized technologies such as Collectd, Kafka, Spark, Elasticsearch, InfluxDB, Grafana and others. The monitoring infrastructure, fully based on CERN cloud resources, covers the whole workflow of the monitoring data: from collecting and validating metrics and logs to making them available for dashboards, reports and alarms. The deployment in production of this new DC and WLCG monitoring is well under way and this contribution provides a summary of the progress, hurdles met and lessons learned in using these open source technologies. It also focuses on the choices made to achieve the required levels of stability, scalability and performance of the MONIT monitoring service.


2013 ◽  
Vol 27 (9) ◽  
pp. 2443-2469 ◽  
Author(s):  
Dana Petcu ◽  
Silviu Panica ◽  
Ciprian Crăciun ◽  
Marian Neagul ◽  
Calin Şandru

Author(s):  
Liang Zhang ◽  
Johann Li ◽  
Ping Li ◽  
Xiaoyuan Lu ◽  
Maoguo Gong ◽  
...  

2018 ◽  
Vol 10 (8) ◽  
pp. 1274 ◽  
Author(s):  
Kiwon Lee ◽  
Kwangseob Kim

Recently, web application services based on cloud computing technologies are being offered. In the web-based application field of geo-spatial data management or processing, data processing services are produced or operated using various information communication technologies. Platform-as-a-Service (PaaS) is a type of cloud computing service model that provides a platform that allows service providers to implement, execute, and manage applications without the complexity of establishing and maintaining the lower-level infrastructure components, typically related to application development and launching. There are advantages, in terms of cost-effectiveness and service development expansion, of applying non-proprietary PaaS cloud computing. Nevertheless, there have not been many studies on the use of PaaS technologies to build geo-spatial application services. This study was based on open source PaaS technologies used in a geo-spatial image processing service, and it aimed to evaluate the performance of that service in relation to the Web Processing Service (WPS) 2.0 specification, based on the Open Geospatial Consortium (OGC) after a test application deployment using the configured service supported by a cloud environment. Using these components, the performance of an edge extraction algorithm on the test system in three cases, of 300, 500, and 700 threads, was assessed through a comparison test with another test system, in the same three cases, using Infrastructure-as-a-Service (IaaS) without Load Balancer-as-a-Service (LBaaS). According to the experiment results, in all the test cases of WPS execution considered in this study, the PaaS-based geo-spatial service had a greater performance and lower error rates than the IaaS-based cloud without LBaaS.


Author(s):  
Fadi P. Deek ◽  
James A. M. McHugh
Keyword(s):  

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