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| 主要作者: | |
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| 格式: | Recurso digital |
| 語言: | 英语 |
| 出版: |
Zenodo
2024
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| 主題: | |
| 在線閱讀: | https://doi.org/10.5281/zenodo.18033015 |
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書本目錄:
- <p><span>More and more people are using cloud-native architectures, which has made it harder to make applications that work well, scale well, and stay up in very dynamic situations. Conventional performance optimization methods, typically utilized after deployment, are inadequate for managing the intricacies of microservices, container orchestration, and elastic infrastructure. This hypothetical research puts up a systematic performance engineering path for creating cloud-native applications that can handle a lot of traffic and stay up and running. The roadmap includes analyzing performance needs, modeling workloads, evaluating scalability, injecting faults, continuously monitoring, and optimizing the application over time. Simulated findings show that systems built using this roadmap are more scalable when there are a lot of users or a lot of work to do, they can handle more errors, they can recover from failures faster, and they use resources more efficiently. The results show how important it is to make performance engineering a regular and proactive part of cloud-native systems to help with reliability and operational excellence.</span></p>