Vol. 4 No. 2 (2024): Journal of AI-Assisted Scientific Discovery
Articles

Resilience Engineering in Container Orchestration: Managing Failures in Distributed Systems

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  • Sandeep Chinamanagonda,
  • Hitesh Allam,
  • Jayaram Immaneni
Sandeep Chinamanagonda
Senior Software Engineer at Oracle Cloud infrastructure, USA
Hitesh Allam
Software Engineer at Concor IT, USA
Jayaram Immaneni
SRE Lead at JP Morgan Chase, USA
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Published 29-08-2024

Keywords

  • Resilience Engineering,
  • Container Orchestration
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Sandeep Chinamanagonda, Hitesh Allam, and Jayaram Immaneni, “Resilience Engineering in Container Orchestration: Managing Failures in Distributed Systems”, Journal of AI-Assisted Scientific Discovery, vol. 4, no. 2, pp. 301–324, Aug. 2024, Accessed: Dec. 29, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/274

Abstract

Resilience engineering in container orchestration focuses on designing systems that anticipate, withstand, and recover from failures, ensuring reliable performance even in unpredictable environments. As modern applications increasingly rely on distributed systems, the complexity of managing these environments has grown significantly. Container orchestration platforms, like Kubernetes, offer a robust solution for automating containerized application deployment, scaling, and operations. However, these systems are not immune to failure. Hardware malfunctions, software bugs, network issues, or unexpected load spikes can all lead to disruptions. Resilience engineering addresses these challenges by proactively identifying weaknesses, implementing fail-safe mechanisms, and enhancing system adaptability. This involves self-healing processes, redundancy, automated rollbacks, and dynamic load balancing to mitigate risks and reduce downtime. Practical resilience engineering also relies on thorough monitoring, logging, and real-time analysis to detect anomalies early. By understanding how failures propagate through a distributed system, teams can design for graceful degradation rather than catastrophic collapse. A key aspect is fostering a culture where failure is expected and prepared for, encouraging continuous improvement and learning from incidents. In container orchestration, resilience is not just about preventing failure, ensuring rapid recovery, and maintaining service quality. By embracing principles of resilience engineering, organizations can build more reliable, fault-tolerant distributed systems, improving customer satisfaction and maintaining business continuity. As technology landscapes evolve, managing failure efficiently in containerized environments will remain crucial for organizations seeking to confidently deploy at scale.

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