Analisis Komprehensif Arsitektur Serverless Container dan Edge v8 Isolate pada Penerapan Industri
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Jun 18, 2026
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Abstract
This study presents a comparative performance analysis of response times between Serverless architecture (AWS Lambda container-based) and Edge Computing (V8 Isolate-based). The evaluation focused on handling CPU-intensive computational loads using the Hono.js framework via the execution of 1,000 concurrent requests per platform. Measurements were strictly centered on Client-Side Round Trip Time (RTT) to ensure a fair comparison, deliberately bypassing server-side timing due to time quantization security restrictions inherent in the V8 Isolate environment. Empirical results demonstrate that Vercel recorded an average RTT of 432.40 ms, which is 76.29% faster than Cloudflare Workers' average of 762.29 ms. The Mann-Whitney U significance test statistically confirmed this difference (p < 0.05). Furthermore, consistency analysis via the Coefficient of Variation (CV) placed Vercel ahead with a highly stable value of 0.116 compared to Cloudflare's 0.527. Cloudflare also exhibited a larger cold start latency gap during the warm-up phase (28.03 ms difference) compared to Vercel (7.16 ms difference). The conclusion indicates that for REST API applications with heavy computational loads, container-based serverless architecture provides significantly superior stability, lower tail latency, and overall efficiency compared to Edge Isolate, challenging the theoretical assumption of absolute Edge network superiority in industrial scenarios.
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Harpanda, A., Nawaf Akbar, M., & Hidayat, R. (2026). Analisis Komprehensif Arsitektur Serverless Container dan Edge v8 Isolate pada Penerapan Industri. JITSI : Jurnal Ilmiah Teknologi Sistem Informasi, 7(2), 97 - 104. https://doi.org/10.62527/jitsi.7.2.569
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References
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[2] C. Marcelino, N. Krennmair, T. W. Pusztai, and S. Nastic, “Lumos: Performance Characterization of WebAssembly as a Serverless Runtime in the Edge-Cloud Continuum,” in Proceedings of the 15th International Conference on the Internet of Things, Vienna Austria: ACM, Nov. 2025, pp. 113–121. doi: 10.1145/3770501.3770515.
[3] C. Marcelino, J. Shahhoud, and S. Nastic, “GoldFish: Serverless Actors with Short-Term Memory State for the Edge-Cloud Continuum,” in Proceedings of the 14th International Conference on the Internet of Things, Oulu Finland: ACM, Nov. 2024, pp. 56–64. doi: 10.1145/3703790.3703797.
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[6] M. S. Aslanpour, A. N. Toosi, M. A. Cheema, and R. Gaire, “Energy-Aware Resource Scheduling for Serverless Edge Computing,” in 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid), Taormina, Italy: IEEE, May 2022, pp. 190–199. doi: 10.1109/CCGrid54584.2022.00028.
[7] S. Pan, H. Zhao, Z. Cai, D. Li, R. Ma, and H. Guan, “Sustainable Serverless Computing with Cold-start Optimization and Automatic Workflow Resource Scheduling,” IEEE Trans. Sustain. Comput., pp. 1–12, 2024, doi: 10.1109/TSUSC.2023.3311197.
[8] K. R. Rajput, C. D. Kulkarni, B. Cho, W. Wang, and I. K. Kim, “EdgeFaaSBench: Benchmarking Edge Devices Using Serverless Computing,” in 2022 IEEE International Conference on Edge Computing and Communications (EDGE), Barcelona, Spain: IEEE, Jul. 2022, pp. 93–103. doi: 10.1109/EDGE55608.2022.00024.
[9] M. Ghorbian and M. Ghobaei-Arani, “A survey on the cold start latency approaches in serverless computing: an optimization-based perspective,” Computing, vol. 106, no. 11, pp. 3755–3809, Nov. 2024, doi: 10.1007/s00607-024-01335-5.
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[11] V. Kjorveziroski and S. Filiposka, “WebAssembly as an Enabler for Next Generation Serverless Computing,” J Grid Computing, vol. 21, no. 3, p. 34, Sep. 2023, doi: 10.1007/s10723-023-09669-8.
[12] V. Kjorveziroski and S. Filiposka, “WebAssembly Orchestration in the Context of Serverless Computing,” J Netw Syst Manage, vol. 31, no. 3, p. 62, Jul. 2023, doi: 10.1007/s10922-023-09753-0.
[13] S. Kounev et al., “Serverless Computing: What It Is, and What It Is Not?,” Commun. ACM, vol. 66, no. 9, pp. 80–92, Sep. 2023, doi: 10.1145/3587249.
[14] Z. Li, L. Guo, J. Cheng, Q. Chen, B. He, and M. Guo, “The Serverless Computing Survey: A Technical Primer for Design Architecture,” ACM Comput. Surv., vol. 54, no. 10s, pp. 1–34, Jan. 2022, doi: 10.1145/3508360.
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[17] M. Ghorbian, M. Ghobaei-Arani, and L. Esmaeili, “Autonomous scheduling mechanism based on energy awareness for improving resource allocation in serverless IoT edge,” Sci Rep, vol. 15, no. 1, p. 24173, Jul. 2025, doi: 10.1038/s41598-025-04214-x.
[18] M. Golec et al., “MASTER: Machine Learning-Based Cold Start Latency Prediction Framework in Serverless Edge Computing Environments for Industry 4.0,” IEEE J. Sel. Areas Sensors, vol. 1, pp. 36–48, 2024, doi: 10.1109/JSAS.2024.3396440.
[19] A. Sherawat, S. B. Nath, and S. K. Addya, “Optimizing Completion Time of Requests in Serverless Computing,” J Netw Syst Manage, vol. 32, no. 2, p. 28, Apr. 2024, doi: 10.1007/s10922-024-09800-4.
[20] A. Alanda, H. A. Mooduto, H. Amnur and M. Fadhel, "Scaling Kubernetes Architectures for High Availability in Cloud," 2025 International Conference on Computer Sciences, Engineering, and Technology Innovation (ICoCSETI), Jakarta, Indonesia, 2025, pp. 818-823, doi: 10.1109/ICoCSETI63724.2025.11020084.
[21] S. Ristov, R. Farahani, and R. Prodan, “Large-scale Graph Processing and Simulation with Serverless Workflows in Federated FaaS,” in Companion of the 2023 ACM/SPEC International Conference on Performance Engineering, Coimbra Portugal: ACM, Apr. 2023, pp. 227–231. doi: 10.1145/3578245.3585333.
[22] M. S. Aslanpour et al., “Serverless Edge Computing: Vision and Challenges,” in 2021 Australasian Computer Science Week Multiconference, Dunedin New Zealand: ACM, Feb. 2021, pp. 1–10. doi: 10.1145/3437378.3444367.
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[24] R. Firman, Yuhefizar, and H. Amnur, “Implementasi Openstack untuk Private Cloud pada mata kuliah Administrasi server”, jitsi, vol. 1, no. 2, pp. 75 - 79, Jun. 2020.
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