Resilient Auto-Scaling of Microservice Architectures with Efficient Resource Management
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866912417206763520 |
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| author | Ahmad, Hussain Treude, Christoph Wagner, Markus Szabo, Claudia |
| author_facet | Ahmad, Hussain Treude, Christoph Wagner, Markus Szabo, Claudia |
| contents | Horizontal Pod Auto-scalers (HPAs) are crucial for managing resource allocation in microservice architectures to handle fluctuating workloads. However, traditional HPAs fail to address resource disruptions caused by faults, cyberattacks, maintenance, and other operational challenges. These disruptions result in resource wastage, service unavailability, and HPA performance degradation. To address these challenges, we extend our prior work on Smart HPA and propose SecureSmart HPA, which offers resilient and resource-efficient auto-scaling for microservice architectures. SecureSmart HPA monitors microservice resource demands, detects disruptions, evaluates resource wastage, and dynamically adjusts scaling decisions to enhance the resilience of auto-scaling operations. Furthermore, SecureSmart HPA enables resource sharing among microservices, optimizing scaling efficiency in resource-constrained environments. Experimental evaluation at varying disruption severities, with 25%, 50%, and 75% resource wastage, demonstrates that SecureSmart HPA performs effectively across different levels of disruptions. It achieves up to a 57.2% reduction in CPU overutilization and a 51.1% increase in resource allocation compared to Smart HPA, highlighting its ability to deliver resilient and efficient auto-scaling operations in volatile and resource-constrained environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_05693 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Resilient Auto-Scaling of Microservice Architectures with Efficient Resource Management Ahmad, Hussain Treude, Christoph Wagner, Markus Szabo, Claudia Distributed, Parallel, and Cluster Computing Horizontal Pod Auto-scalers (HPAs) are crucial for managing resource allocation in microservice architectures to handle fluctuating workloads. However, traditional HPAs fail to address resource disruptions caused by faults, cyberattacks, maintenance, and other operational challenges. These disruptions result in resource wastage, service unavailability, and HPA performance degradation. To address these challenges, we extend our prior work on Smart HPA and propose SecureSmart HPA, which offers resilient and resource-efficient auto-scaling for microservice architectures. SecureSmart HPA monitors microservice resource demands, detects disruptions, evaluates resource wastage, and dynamically adjusts scaling decisions to enhance the resilience of auto-scaling operations. Furthermore, SecureSmart HPA enables resource sharing among microservices, optimizing scaling efficiency in resource-constrained environments. Experimental evaluation at varying disruption severities, with 25%, 50%, and 75% resource wastage, demonstrates that SecureSmart HPA performs effectively across different levels of disruptions. It achieves up to a 57.2% reduction in CPU overutilization and a 51.1% increase in resource allocation compared to Smart HPA, highlighting its ability to deliver resilient and efficient auto-scaling operations in volatile and resource-constrained environments. |
| title | Resilient Auto-Scaling of Microservice Architectures with Efficient Resource Management |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2506.05693 |