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Kubernetes in IT administration and serverless computing: An empirical study and research challenges

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Abstract

Today’s industry has gradually realized the importance of lifting efficiency and saving costs during the life-cycle of an application. In particular, we see that most of the cloud-based applications and services often consist of hundreds of micro-services; however, the traditional monolithic pattern is no longer suitable for today’s development life-cycle. This is due to the difficulties of maintenance, scale, load balance, and many other factors associated with it. Consequently, people switch their focus on containerization—a lightweight virtualization technology. The saving grace is that it can use machine resources more efficiently than the virtual machine (VM). In VM, a guest OS is required to simulate on the host machine, whereas containerization enables applications to share a common OS. Furthermore, containerization facilitates users to create, delete, or deploy containers effortlessly. In order to manipulate and manage the multiple containers, the leading Cloud providers introduced the container orchestration platforms, such as Kubernetes, Docker Swarm, Nomad, and many others. In this paper, a rigorous study on Kubernetes from an administrator’s perspective is conducted. In a later stage, serverless computing paradigm was redefined and integrated with Kubernetes to accelerate the development of software applications. Theoretical knowledge and experimental evaluation show that this novel approach can be accommodated by the developers to design software architecture and development more efficiently and effectively by minimizing the cost charged by public cloud providers (such as AWS, GCP, Azure). However, serverless functions are attached with several issues, such as security threats, cold start problem, inadequacy of function debugging, and many other. Consequently, the challenge is to find ways to address these issues. However, there are difficulties and hardships in addressing all the issues altogether. Respectively, in this paper, we simply narrow down our analysis toward the security aspects of serverless. In particular, we quantitatively measure the success probability of attack in serverless (using Attack Tree and Attack–Defense Tree) with the possible attack scenarios and the related countermeasures. Thereafter, we show how the quantification can reflect toward the end-to-end security enhancement. In fine, this study concludes with research challenges such as the burdensome and error-prone steps of setting the platform, and investigating the existing security vulnerabilities of serverless computing, and possible future directions.

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Notes

  1. ADTool https://satoss.uni.lu/members/piotr/adtool/

  2. Namespace encapsulates the Kernel’s global resources, so that each namespace can have an independent and isolated resource sets. It helps ensure different processes to use the same resource in their namespaces without interfering with each other.

  3. Docker Hub is a registry service on the cloud that allows developers to download Docker images that are built by other communities.

  4. Pods is a collection of containers whose functions are highly related.

  5. Volume is a store technique, which maps local file to container’s directory. It enables developers to modify local code and dynamic update the container.

  6. Ubuntu https://ubuntu.com/

  7. Kubernetes The Hard Way https://github.com/kelseyhightower/kubernetes-the-hard-way

  8. Vagrant is automatic tool for creating and managing multiple VMs at the same time.

  9. CoreDNS is a DNS server. It is written in Go. It can be used in a multitude of environments because of its flexibility.

  10. Kubeadm Way https://kubernetes.io/docs/setup/production-environment/tools/kubeadm/install-kubeadm/

  11. High availability: HA means that developers usually create more than one node for some services to prevent the emergency. If one node breaks down, then other nodes can back up and work.

  12. Grafana Dashboard https://grafana.com/grafana/dashboards

  13. hey https://github.com/rakyll/hey

  14. ADTool https://satoss.uni.lu/members/piotr/adtool/

Abbreviations

AWS :

Amazon Web Service

ASAP :

Autonomous System Adaptation Platform

CAS :

Content-Addressable Storage

CI :

Continuous Integration

CD :

Continuous Deployment

CLI :

Command Line Interface

CNI :

Container Network Interface

CA :

Certificate Authority

DRIP :

Dynamic Real-time Infrastructure Planner

FaaS :

Function as a Service

GCP :

Google Cloud Platform

HA :

High Availability

IoT :

Internet Of Thing

IFC :

Information Flow Control

IaaS :

Infrastructure as a Service

K8S :

Kubernetes

HPA :

Horizontal Pod Autoscaler

MPSC :

Multi-Provider Serverless Computing

P2P :

Peer-to-Peer

SaaS :

Software as a Service

SWITCH :

Software Workbench for Interactive, Time Critical and Highly self-adaptive Cloud applications

SLO :

Service-Level Objective

SIDE :

SWITCH Interactive Development Environment

VM :

Virtual Machine

ATree :

Attack Tree

ADTree :

Attack–Defense Tree

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Author notes

  1. Subrota Kumar Mondal and Rui Pan have contributed equally.

Authors and Affiliations

  1. Faculty of Information Technology, Macau University of Science and Technology, Macao, China

    Subrota Kumar Mondal

  2. Faculty of Science, Vrije Universiteit Amsterdam, North Holland, Netherlands

    Rui Pan

  3. Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Geelong, Australia

    H M Dipu Kabir

  4. Faculty of Information Technology, Macau University of Science and Technology, Macao, China

    Tan Tian

  5. The Department of Computing Decision Sciences, Lingnan University, Hong Kong, China

    Hong-Ning Dai

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Mondal, S.K., Pan, R., Kabir, H.M.D. et al. Kubernetes in IT administration and serverless computing: An empirical study and research challenges. J Supercomput 78, 2937–2987 (2022). https://doi.org/10.1007/s11227-021-03982-3

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