Enhancing Enterprise Software Reliability Using Retry Queues and Message Persistence in Event-Driven Cloud Environments

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@article{1710020,
      author = {Eseoghene Daniel Erigha, Ehimah Obuse, Babawale Patrick Okare, Abel Chukwuemeke Uzoka, Samuel Owoade; Noah Ayanbode},
      title = {Enhancing Enterprise Software Reliability Using Retry Queues and Message Persistence in Event-Driven Cloud Environments},
      journal = {Iconic Research And Engineering Journals},
      year = {2019},
      volume = {2},
      number = {11},
      pages = {481-496},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1710020.pdf},
      abstract = {In an era where enterprise software systems are increasingly deployed on cloud platforms and built upon event-driven architectures, ensuring consistent reliability across distributed components becomes a critical concern. These modern architectures promote scalability and responsiveness through asynchronous communication, but they also introduce new complexities in handling transient failures, message delivery guarantees, and fault tolerance. This explores the role of retry queues and message persistence as foundational mechanisms for enhancing software reliability in such environments. Retry queues enable services to automatically attempt message processing again after initial failures, using configurable strategies such as exponential backoff, jitter, and maximum retry limits. These mechanisms help prevent message loss, reduce system downtime, and improve end-to-end transaction success rates. When integrated with dead-letter queues and observability tools, retry queues offer not only recovery but also insight into persistent system weaknesses and transient bottlenecks. Message persistence further strengthens reliability by ensuring that messages are durably stored?often across distributed logs or message brokers?until they are successfully processed or safely discarded. Leveraging technologies such as Apache Kafka, AWS SQS with Dead-Letter Queues, and Azure Service Bus, developers can implement various delivery semantics (at-least-once, exactly-once, at-most-once) suited to different application requirements. Persistence protects against system crashes, network partitions, and service restarts, thereby maintaining data integrity and continuity across the system. This synthesizes architectural best practices, cloud-native tooling, and design patterns for implementing retry logic and persistent messaging in microservice-based systems. It also highlights real-world use cases?including transactional processing, notification systems, and event sourcing?demonstrating how these reliability mechanisms can be effectively employed. Finally, the discussion explores future directions such as AI-assisted retry strategies, serverless queue orchestration, and cross-cloud persistence standards. In conclusion, retry queues and message persistence are indispensable tools for building fault-tolerant, enterprise-grade, event-driven software in dynamic cloud environments.},
      keywords = {Enterprise, Software reliability, Retry queues, Message persistence, Event-driven, Cloud environments},
      month = {May},
  }