The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
A Survey of Autoscaling in Kubernetes
Abstract
Autoscaling is the vital feature of cloud infrastructure to acquire or allocate computing resources ondemand, which allows users to automatically scale the resources provisioned to the applications without human action under a fluctuating workload to optimize the resource cost while satisfying the Quality of Service (QoS) requirements. Kubernetes (K8s), the most prevalent container orchestration, provides built-in autoscalers to deal with the scaling problem in terms of vertical and horizontal at container level but still has some limitations. In this paper, we survey the state of the art of existing approaches to solve the problem of container autoscaling in Kubernetes, their main characteristics as well as their current issues. Based on the analysis, new future directions that can be explored are proposed.
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“Similarly, the pod autoscaler in Kubernetes automatically scales the number of replicas based on their resource consumption, resulting in the addition or deletion of pods in the system [49].”
From Toward Context-Aware Anomaly Detection for AIOps in Microservices Using Dynamic Knowledge Graphs (2026) · cites this paper as [49]
Citations
Cites
Rzaḑca, K., Findeisen, P., Swiderski, J., Zych, P., Broniek, P., Kusmierek, J., Nowak, P. K., Strack, B., Witusowski, P., Hand, S., et al. (2020) · European Conference on Computer Systems · doi:10.1145/3342195.3387524 · Cited by 306
Horizontal Pod Autoscaling in Kubernetes for Elastic Container Orchestration
Nguyen, T.-T., Yeom, Y.-J., Kim, T., et al. (2020) · Sensors · doi:10.3390/s20164621 · Cited by 189
Machine Learning-Based Scaling Management for Kubernetes Edge Clusters
Toka, L., Dobreff, G., Fodor, B., et al. (2021) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2021.3052837 · Cited by 173
Autonomic Vertical Elasticity of Docker Containers with ELASTICDOCKER
Al-Dhuraibi, Y., Paraïso, F., Djarallah, N. B., et al. (2017) · IEEE ... International Conference on Cloud Computing · doi:10.1109/cloud.2017.67 · Cited by 154
Machine learning-based auto-scaling for containerized applications
Imdoukh, M., Ahmad, I., & Alfailakawi, M. G. (2019) · Neural Computing and Applications · doi:10.1007/s00521-019-04507-z · Cited by 152
Adaptive scaling of Kubernetes pods
Balla, D., Simon, C., & Maliosz, M. (2020) · IEEE/IFIP Network Operations and Management Symposium (NOMS) · doi:10.1109/noms47738.2020.9110428 · Cited by 105
Intelligent Autoscaling of Microservices in the Cloud for Real-Time Applications
Khaleq, A. A., & Ra, I. (2021) · IEEE Access · doi:10.1109/access.2021.3061890 · Cited by 101
Yu, G., Chen, P., & Zheng, Z. (2020) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2020.2985352 · Cited by 87
Exploring Potential for Non-Disruptive Vertical Auto Scaling and Resource Estimation in Kubernetes
Rattihalli, G., Govindaraju, M., Lu, H., et al. (2019) · IEEE ... International Conference on Cloud Computing · doi:10.1109/cloud.2019.00018 · Cited by 79
Traffic-Aware Horizontal Pod Autoscaler in Kubernetes-Based Edge Computing Infrastructure
Phuc, L. H., Phan, L.-A., & Kim, T. (2022) · IEEE Access · doi:10.1109/access.2022.3150867 · Cited by 68
Cited by
Toward Context-Aware Anomaly Detection for AIOps in Microservices Using Dynamic Knowledge Graphs
Moens, P., Steenwinckel, B., Ongenae, F., Volckaert, B., & Hoecke, S. V. (2026) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2026.3652304 · Cited by 6
“Similarly, the pod autoscaler in Kubernetes automatically scales the number of replicas based on their resource consumption, resulting in the addition or deletion of pods in the system [49].”
Metadata
- Authors
- Tran, M.-N., Vu, D.-D., & Kim, Y.
- Affiliations
- Soongsil University (KR)
- Venue
- 2022 Thirteenth International Conference on Ubiquitous and Future Networks (ICUFN)
- Publisher
- IEEE
- Published
- 2022-07-05
- Pages
- 263-265
- OpenAlex
- W4286247410
- Cited by
- 51
- References
- 20
- Citations by year
- 2026: 12 · 2025: 16 · 2024: 14 · 2023: 8 · 2022: 1
- FWCI
- 8.72
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Ubiquitous and Future Networks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
- Physical Sciences › Computer Science › Computer Networks and Communications › Software System Performance and Reliability
- Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
- Keywords
- Kubernetes, auto-scaling, container orchestration, horizontal scaling, vertical scaling, cloud resource provisioning, quality of service, resource cost optimization, workload fluctuation
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
