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Kubernetes scheduling: Taxonomy, ongoing issues and challenges
C Carrión - ACM Computing Surveys, 2022 - dl.acm.org
Continuous integration enables the development of microservices-based applications using
container virtualization technology. Container orchestration systems such as Kubernetes …
container virtualization technology. Container orchestration systems such as Kubernetes …
Serverless computing: state-of-the-art, challenges and opportunities
Serverless computing is growing in popularity by virtue of its lightweight and simplicity of
management. It achieves these merits by reducing the granularity of the computing unit to …
management. It achieves these merits by reducing the granularity of the computing unit to …
Pond: Cxl-based memory pooling systems for cloud platforms
Public cloud providers seek to meet stringent performance requirements and low hardware
cost. A key driver of performance and cost is main memory. Memory pooling promises to …
cost. A key driver of performance and cost is main memory. Memory pooling promises to …
{FIRM}: An intelligent fine-grained resource management framework for {SLO-Oriented} microservices
User-facing latency-sensitive web services include numerous distributed,
intercommunicating microservices that promise to simplify software development and …
intercommunicating microservices that promise to simplify software development and …
Learning scheduling algorithms for data processing clusters
Efficiently scheduling data processing jobs on distributed compute clusters requires complex
algorithms. Current systems use simple, generalized heuristics and ignore workload …
algorithms. Current systems use simple, generalized heuristics and ignore workload …
An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems
Cloud services have recently started undergoing a major shift from monolithic applications,
to graphs of hundreds or thousands of loosely-coupled microservices. Microservices …
to graphs of hundreds or thousands of loosely-coupled microservices. Microservices …
Borg: the next generation
This paper analyzes a newly-published trace that covers 8 different Borg [35] clusters for the
month of May 2019. The trace enables researchers to explore how scheduling works in …
month of May 2019. The trace enables researchers to explore how scheduling works in …
Autopilot: workload autoscaling at google
K Rzadca, P Findeisen, J Swiderski, P Zych… - Proceedings of the …, 2020 - dl.acm.org
In many public and private Cloud systems, users need to specify a limit for the amount of
resources (CPU cores and RAM) to provision for their workloads. A job that exceeds its limits …
resources (CPU cores and RAM) to provision for their workloads. A job that exceeds its limits …
{Heterogeneity-Aware} cluster scheduling policies for deep learning workloads
Specialized accelerators such as GPUs, TPUs, FPGAs, and custom ASICs have been
increasingly deployed to train deep learning models. These accelerators exhibit …
increasingly deployed to train deep learning models. These accelerators exhibit …
Carbon-aware computing for datacenters
A Radovanović, R Koningstein… - … on Power Systems, 2022 - ieeexplore.ieee.org
The amount of CO emitted per kilowatt-hour on an electricity grid varies by time of day and
substantially varies by location due to the types of generation. Networked collections of …
substantially varies by location due to the types of generation. Networked collections of …