Using Kubernetes in Academic Environment : Problems and Approaches
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F22%3A00126703" target="_blank" >RIV/00216224:14610/22:00126703 - isvavai.cz</a>
Result on the web
<a href="https://jsspp.org/papers22/6.pdf" target="_blank" >https://jsspp.org/papers22/6.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-22698-4_12" target="_blank" >10.1007/978-3-031-22698-4_12</a>
Alternative languages
Result language
angličtina
Original language name
Using Kubernetes in Academic Environment : Problems and Approaches
Original language description
In this work, we discuss our experience when utilizing the Kubernetes orchestrator (K8s) to efficiently allocate resources in a heterogeneous and dynamic academic environment. In the commercial world, the "pay per use" model is a strong regulating factor for efficient resource usage. In the academic environment, resources are usually provided "for free" to the end-users, thus they often lack a clear motivation to plan their use efficiently. In this paper, we show three major sources of inefficiencies. One is the users' requirement to have interactive computing environments, where the users need resources for their application as soon as possible. Users do not appreciate waiting for interactive environments, but constantly keeping some resources available for interactive tasks is inefficient. The second phenomenon is observable in both interactive and batch workloads; users tend to overestimate necessary limits for their computations, thus wasting resources. Finally, Kubernetes does not support fair-sharing functionality (dynamic user priorities) which hampers the efforts when developing a fair scheme for Pod/job scheduling and/or eviction. We discuss various approaches to deal with these problems such as scavenger jobs, placeholder jobs, Kubernetes-specific resource allocation policies, separate clusters, priority classes, and novel hybrid cloud approach. We also show that all these proposals open interesting scheduling-related questions that are hard to answer with existing Kubernetes tools and policies. Last but not least, we provide a real workload trace from our installation to the scheduling community which captures these phenomena.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
<a href="/en/project/LM2018140" target="_blank" >LM2018140: e-Infrastructure CZ</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Job Scheduling Strategies for Parallel Processing
ISBN
9783031226977
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
19
Pages from-to
235-253
Publisher name
Springer
Place of publication
Cham (Switzerland)
Event location
Virtual Event
Event date
Jan 1, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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