Uma Investigação Empírica sobre Observabilidade em Sistemas 5G Nativos de Nuvem
Resumo
Ao migrar sofisticados recursos de hardware para componentes de software executados em sistemas de nuvem, as redes 5G proveem grande flexibilidade. No entanto, a softwarização das redes 5G impõe grandes desafios à gerência da rede, especialmente em relação à corretude do sistema em tempo de execução. Neste contexto, se torna essencial que o comportamento do sistema seja facilmente observável. Este trabalho apresenta uma investigação empírica sobre observabilidade em um sistema 5G formado pelas redes de núcleo e de acesso. Resultados mostram que a análise combinada de métricas e logs melhora a observabilidade do sistema e facilita a antecipação de ocorrências de falhas. Nossa investigação demonstra também que, apesar de úteis, as mensagens de logs geradas pelo sistema 5G implantado são pouco estruturadas e pouco inteligíveis.
Referências
3GPP (2020a). 5G; System architecture for the 5G System (5GS) (3GPP TS 23.501 version 16.6.0 Release 16). Technical report, 3GPP.
3GPP (2020b). Study on New Radio Access Technology; Radio Access Architecture and Interfaces (Release 14). Technical report, 3GPP.
Aceto, G. et al. (2013). Cloud monitoring: A survey. Computer Networks, 57(9):2093–2115.
Agiwal, M., Roy, A., and Saxena, N. (2016). Next Generation 5G Wireless Networks: A Comprehensive Survey. IEEE Communications Surveys Tutorials, 18(3):1617–1655.
Alliance, O. S. (2020a). OpenAirInterface — 5G software alliance for democratising wireless innovation. Disponível em: https://openairinterface.org/. Acessado em 01/02/2022.
Alliance, O. S. (2020b). Openairinterface 5G Wireless Implementation. Disponível em: https://gitlab.eurecom.fr/oai/openairinterface5g/. Acessado em 01/02/2022.
Balalaie, A., Heydarnoori, A., and Jamshidi, P. (2016). Microservices Architecture Enables DevOps: Migration to a Cloud-Native Architecture. IEEE Software, 33(3):42–52.
Bhanage, D. A., Pawar, A. V., and Kotecha, K. (2021). IT Infrastructure Anomaly Detection and Failure Handling: A Systematic Literature Review Focusing on Datasets, Log Preprocessing, Machine & Deep Learning Approaches and Automated Tool. IEEE Access, 9:156392–156421.
Both, C. B. et al. (2020). Soft5G+: explorando a softwarização nas redes 5G. In Minicursos do XXXVIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, chapter 3, pages 91–139. Sociedade Brasileira de Computação.
Chen, B. and Jiang, Z. M. J. (2021). A Survey of Software Log Instrumentation. ACM Comput. Surv., 54(4).
CNCF (2022). Cloud native glossary. Disponível em: https://glossary.cncf.io/observability/. Acessado em 03/02/2022.
Contreras, L. M. et al. (2020). Computing at the Edge: But, what Edge? In NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium, pages 1–9.
Esposito, C., Castiglione, A., and Choo, K.-K. R. (2016). Challenges in Delivering Software in the Cloud as Microservices. IEEE Cloud Computing, 3(5):10–14.
Esteves, T., Neves, F., Oliveira, R., and Paulo, J. a. (2021). CAT: Content-Aware Tracing and Analysis for Distributed Systems. In Proceedings of the 22nd International Middleware Conference, page 223–235. Association for Computing Machinery.
Free5GC (2021). Open source 5G core network base on 3GPP R15. Disponível em: https://github.com/free5gc/free5gc. Acessado: 01/02/2022.
Google (2022). Google Cloud’s operations suite (formerly Stackdriver). Disponível em: https://cloud.google.com/products/operations. Acessado em 03/02/2022.
John, W. et al. (2017). Meeting the Observability Shallenges for VNFs in 5G Systems. In 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM), pages 1127–1130.
Kaltenberger, F. et al. (2020). OpenAirInterface: Democratizing innovation in the 5G Era. Computer Networks, 176:107284.
Karumuri, S. et al. (2020). Towards Observability Data Management at Scale. In SIGMOD Record, volume 49.
Larsen, L. M. P., Checko, A., and Christiansen, H. L. (2019). A Survey of the Functional Splits Proposed for 5G Mobile Crosshaul Networks. IEEE Communications Surveys Tutorials, 21(1):146–172.
Lee, S., Levanti, K., and Kim, H. S. (2014). Network monitoring: Present and future. Computer Networks, 65:84–98.
Mace, J., Roelke, R., and Fonseca, R. (2015). Pivot Tracing: Dynamic Causal Monitoring for Distributed Systems. page 378–393. Association for Computing Machinery.
Meng, S. and Liu, L. (2013). Enhanced Monitoring-as-a-Service for Effective Cloud Management. IEEE Transactions on Computers, 62(9):1705–1720.
Microsoft (2021). Cloud monitoring guide: Observability. Disponível em: [link]. Acessado em 03/02/2022.
Morais, F. Z. et al. (2021). OPlaceRAN – a Placement Orchestrator for Virtualized Next-Generation of Radio Access Network.
Narayanan, A. et al. (2021). A Variegated Look at 5G in the Wild: Performance, Power, and QoE Implications. In Proceedings of the 2021 ACM SIGCOMM 2021 Conference, page 610–625, New York, NY, USA. Association for Computing Machinery.
Picoreti, R. et al. (2018). Multilevel Observability in Cloud Orchestration. In 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, pages 776–784.
Polese, M. et al. (2022). Understanding O-RAN: Architecture, Interfaces, Algorithms, Security, and Research Challenges.
Russ, M. (2019). Chaos Engineering Observability. O’Reilly Media, Inc. Saavedra, A. et al. (2018). WizHaul: On the Centralization Degree of Cloud RAN Next Generation Fronthaul. IEEE Transactions on Mobile Computing, 17(10):2452–2466.
Scrocca, M. et al. (2020). The Kaiju Project: Enabling Event-Driven Observability. Proceedings of the 14th ACM International Conference on Distributed and Event-Based Systems, pages 84–91.
Sigelman, B. H. et al. (2010). Dapper, a Large-Scale Distributed Systems Tracing Infrastructure. Technical report, Google, Inc.
Sridharan, C. (2018). Distributed Systems Observability. O’Reilly Media, Inc.
Tan, T.-J. et al. (2020). A Reliable Intelligent Routing Mechanism in 5G Core Networks. Association for Computing Machinery.
3GPP (2020b). Study on New Radio Access Technology; Radio Access Architecture and Interfaces (Release 14). Technical report, 3GPP.
Aceto, G. et al. (2013). Cloud monitoring: A survey. Computer Networks, 57(9):2093–2115.
Agiwal, M., Roy, A., and Saxena, N. (2016). Next Generation 5G Wireless Networks: A Comprehensive Survey. IEEE Communications Surveys Tutorials, 18(3):1617–1655.
Alliance, O. S. (2020a). OpenAirInterface — 5G software alliance for democratising wireless innovation. Disponível em: https://openairinterface.org/. Acessado em 01/02/2022.
Alliance, O. S. (2020b). Openairinterface 5G Wireless Implementation. Disponível em: https://gitlab.eurecom.fr/oai/openairinterface5g/. Acessado em 01/02/2022.
Balalaie, A., Heydarnoori, A., and Jamshidi, P. (2016). Microservices Architecture Enables DevOps: Migration to a Cloud-Native Architecture. IEEE Software, 33(3):42–52.
Bhanage, D. A., Pawar, A. V., and Kotecha, K. (2021). IT Infrastructure Anomaly Detection and Failure Handling: A Systematic Literature Review Focusing on Datasets, Log Preprocessing, Machine & Deep Learning Approaches and Automated Tool. IEEE Access, 9:156392–156421.
Both, C. B. et al. (2020). Soft5G+: explorando a softwarização nas redes 5G. In Minicursos do XXXVIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, chapter 3, pages 91–139. Sociedade Brasileira de Computação.
Chen, B. and Jiang, Z. M. J. (2021). A Survey of Software Log Instrumentation. ACM Comput. Surv., 54(4).
CNCF (2022). Cloud native glossary. Disponível em: https://glossary.cncf.io/observability/. Acessado em 03/02/2022.
Contreras, L. M. et al. (2020). Computing at the Edge: But, what Edge? In NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium, pages 1–9.
Esposito, C., Castiglione, A., and Choo, K.-K. R. (2016). Challenges in Delivering Software in the Cloud as Microservices. IEEE Cloud Computing, 3(5):10–14.
Esteves, T., Neves, F., Oliveira, R., and Paulo, J. a. (2021). CAT: Content-Aware Tracing and Analysis for Distributed Systems. In Proceedings of the 22nd International Middleware Conference, page 223–235. Association for Computing Machinery.
Free5GC (2021). Open source 5G core network base on 3GPP R15. Disponível em: https://github.com/free5gc/free5gc. Acessado: 01/02/2022.
Google (2022). Google Cloud’s operations suite (formerly Stackdriver). Disponível em: https://cloud.google.com/products/operations. Acessado em 03/02/2022.
John, W. et al. (2017). Meeting the Observability Shallenges for VNFs in 5G Systems. In 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM), pages 1127–1130.
Kaltenberger, F. et al. (2020). OpenAirInterface: Democratizing innovation in the 5G Era. Computer Networks, 176:107284.
Karumuri, S. et al. (2020). Towards Observability Data Management at Scale. In SIGMOD Record, volume 49.
Larsen, L. M. P., Checko, A., and Christiansen, H. L. (2019). A Survey of the Functional Splits Proposed for 5G Mobile Crosshaul Networks. IEEE Communications Surveys Tutorials, 21(1):146–172.
Lee, S., Levanti, K., and Kim, H. S. (2014). Network monitoring: Present and future. Computer Networks, 65:84–98.
Mace, J., Roelke, R., and Fonseca, R. (2015). Pivot Tracing: Dynamic Causal Monitoring for Distributed Systems. page 378–393. Association for Computing Machinery.
Meng, S. and Liu, L. (2013). Enhanced Monitoring-as-a-Service for Effective Cloud Management. IEEE Transactions on Computers, 62(9):1705–1720.
Microsoft (2021). Cloud monitoring guide: Observability. Disponível em: [link]. Acessado em 03/02/2022.
Morais, F. Z. et al. (2021). OPlaceRAN – a Placement Orchestrator for Virtualized Next-Generation of Radio Access Network.
Narayanan, A. et al. (2021). A Variegated Look at 5G in the Wild: Performance, Power, and QoE Implications. In Proceedings of the 2021 ACM SIGCOMM 2021 Conference, page 610–625, New York, NY, USA. Association for Computing Machinery.
Picoreti, R. et al. (2018). Multilevel Observability in Cloud Orchestration. In 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, pages 776–784.
Polese, M. et al. (2022). Understanding O-RAN: Architecture, Interfaces, Algorithms, Security, and Research Challenges.
Russ, M. (2019). Chaos Engineering Observability. O’Reilly Media, Inc. Saavedra, A. et al. (2018). WizHaul: On the Centralization Degree of Cloud RAN Next Generation Fronthaul. IEEE Transactions on Mobile Computing, 17(10):2452–2466.
Scrocca, M. et al. (2020). The Kaiju Project: Enabling Event-Driven Observability. Proceedings of the 14th ACM International Conference on Distributed and Event-Based Systems, pages 84–91.
Sigelman, B. H. et al. (2010). Dapper, a Large-Scale Distributed Systems Tracing Infrastructure. Technical report, Google, Inc.
Sridharan, C. (2018). Distributed Systems Observability. O’Reilly Media, Inc.
Tan, T.-J. et al. (2020). A Reliable Intelligent Routing Mechanism in 5G Core Networks. Association for Computing Machinery.
Publicado
23/05/2022
Como Citar
RODRIGUES, Karlla B. Chaves; BRUNO, Gustavo Zanatta; CARDOSO, Kleber Vieira; CORRÊA, Sand Luz; BOTH, Cristiano.
Uma Investigação Empírica sobre Observabilidade em Sistemas 5G Nativos de Nuvem. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 40. , 2022, Fortaleza.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 252-265.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2022.222304.
