Future Approach to tier-0 extension

Jones, Ben; McCance, Gavin; Cordeiro, Cristovao; Giordano, D.; Traylen, S.; García, Daysi

doi:10.1088/1742-6596/898/8/082040

Cited by 2 publications

(1 citation statement)

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“…In the context of the IT department, the infrastructure functionality has grown during these years, from container orchestration engines with OpenStack Magnum [4,5] to ()api for baremetal provisioning with OpenStack Ironic [6,7]. Finally, the Batch Service has faced not only the challenge of scaling-up the pool but to integrate opportunistic resources [8] and to also explore the exploitation of external clouds to expand capacity [9,10]. In a rapidly changing environment, some constants remain: the compute demand keeps growing, and the IT budget is still tight.…”

Section: Introductionmentioning

confidence: 99%

Managing the CERN Batch System with Kubernetes

et al. 2020

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The CERN Batch Service faces many challenges in order to get ready for the computing demands of future LHC runs. These challenges require that we look at all potential resources, assessing how efficiently we use them and that we explore different alternatives to exploit opportunistic resources in our infrastructure as well as outside of the CERN computing centre. Several projects, like BEER, Helix Nebula Science Cloud and the new OCRE project, have proven our ability to run batch workloads on a wide range of non-traditional resources. However, the challenge is not only to obtain the raw compute resources needed but how to define an operational model that is cost and time efficient, scalable and flexible enough to adapt to a heterogeneous infrastructure. In order to tackle both the provisioning and operational challenges it was decided to use Kubernetes. By using Kubernetes we benefit from a de-facto standard in containerised environments, available in nearly all cloud providers and surrounded by a vibrant ecosystem of open-source projects. Leveraging Kubernetes’ built-in functionality, and other open-source tools such as Helm, Terraform and GitLab CI, we have deployed a first cluster prototype which we discuss in detail. The effort has simplified many of the existing operational procedures we currently have, but has also made us rethink established procedures and assumptions that were only valid in a VM-based cloud environment. This contribution presents how we have adopted Kubernetes into the CERN Batch Service, the impact its adoption has in daily operations, a comparison on resource usage efficiency and the experience so far evolving our infrastructure towards this model.

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Section: Introductionmentioning

confidence: 99%

Managing the CERN Batch System with Kubernetes

et al. 2020

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Orchestration Architecture for Automatic Deployment of 5G Services from Bare Metal in Mobile Edge Computing Infrastructure

Chirivella‐Perez¹,

Calero²,

Wang³

et al. 2018

Wireless Communications and Mobile Computing

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The progress in realizing the Fifth Generation (5G) mobile networks has been accelerated recently towards deploying 5G prototypes with increasing scale. One of the Key Performance Indicators (KPIs) in 5G deployments is the service deployment time, which should be substantially reduced from the current 90 hours to the target 90 minutes on average as defined by the 5G Public-Private Partnership (5G-PPP). To achieve this challenging KPI, highly automated and coordinated operations are required for the 5G network management. This paper addresses this challenge by designing and prototyping a novel 5G service deployment orchestration architecture that is capable of automating and coordinating a series of complicated operations across physical infrastructure, virtual infrastructure, and service layers over a distributed mobile edge computing paradigm, in an integrated manner. Empirical results demonstrate the superior performance achieved, which meets the 5G-PPP KPI even in the most challenging scenario where 5G services are installed from bare metal.

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Future Approach to tier-0 extension

Cited by 2 publications

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Managing the CERN Batch System with Kubernetes

Managing the CERN Batch System with Kubernetes

Orchestration Architecture for Automatic Deployment of 5G Services from Bare Metal in Mobile Edge Computing Infrastructure

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