Resilient Auto-Scaling of Microservice Architectures with Efficient Resource Management

2025-06-06

AI Summary

Traditional Horizontal Pod Autoscalers (HPAs) struggle to handle resource disturbances caused by failures, cyberattacks, or operational activities, often leading to service unavailability, resource wastage, and control instability. This paper proposes SecureSmart HPA—a disturbance-aware horizontal autoscaling mechanism tailored for microservice architectures. Its core contributions are threefold: (1) a novel dynamic scaling decision framework jointly driven by real-time disturbance detection and quantitative resource-wastage assessment; (2) a cross-service shared-resource scheduling strategy to enhance elasticity and utilization under resource constraints; and (3) adaptive control leveraging monitoring feedback, dynamically adjusted thresholds, and lightweight disturbance modeling. Experimental evaluation under 25%–75% disturbance intensity demonstrates that SecureSmart HPA reduces CPU overload by 57.2% and improves resource allocation efficiency by 51.1% compared to Smart HPA, while significantly enhancing system stability and response efficiency.

Technology Category

• Machine Learning: Hardware-aware ML
• Multiagent Systems: Distributed Problem Solving
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems

Application Category

• Security and Privacy: Large-scale security measurements
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

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.

Problem

• Resilient auto-scaling for microservices under disruptions
• Resource-efficient management in constrained environments
• Dynamic scaling adjustment to reduce CPU overutilization

Innovation

• SecureSmart HPA for resilient auto-scaling
• Dynamic scaling adjustment for resource efficiency
• Resource sharing among microservices optimization