Adaptive Management of Microservices in Dynamic Computing Environments: A Taxonomy and Future Directions
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866911628005474304 |
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| author | Chen, Ming Islam, Muhammed Tawfiqul Read, Maria Rodriguez Buyya, Rajkumar |
| author_facet | Chen, Ming Islam, Muhammed Tawfiqul Read, Maria Rodriguez Buyya, Rajkumar |
| contents | Microservice-based cloud applications face changing workloads, evolving request paths, variable network conditions, interference, and failures. These dynamics couple autoscaling, placement, routing, isolation, and remediation. The survey examines dynamics-aware adaptive management for microservices. Its taxonomy covers control locus, modeled dynamics, adaptation strategy, and evaluation evidence; objectives and telemetry are cross-cutting. A synthesis of 84 system entries and 13 evaluation artifacts shows that production dynamics are often partially modeled. Reported gains also depend on evaluation fidelity. Key future directions include cross-layer coordination, telemetry-to-control abstractions, safe learning-based control, and reproducible dynamic evaluation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_25222 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Adaptive Management of Microservices in Dynamic Computing Environments: A Taxonomy and Future Directions Chen, Ming Islam, Muhammed Tawfiqul Read, Maria Rodriguez Buyya, Rajkumar Distributed, Parallel, and Cluster Computing Microservice-based cloud applications face changing workloads, evolving request paths, variable network conditions, interference, and failures. These dynamics couple autoscaling, placement, routing, isolation, and remediation. The survey examines dynamics-aware adaptive management for microservices. Its taxonomy covers control locus, modeled dynamics, adaptation strategy, and evaluation evidence; objectives and telemetry are cross-cutting. A synthesis of 84 system entries and 13 evaluation artifacts shows that production dynamics are often partially modeled. Reported gains also depend on evaluation fidelity. Key future directions include cross-layer coordination, telemetry-to-control abstractions, safe learning-based control, and reproducible dynamic evaluation. |
| title | Adaptive Management of Microservices in Dynamic Computing Environments: A Taxonomy and Future Directions |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2604.25222 |