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Informative Article | Engineering Science | India | Volume 9 Issue 7, July 2020 | Rating: 3.5 / 10
Operationalizing Batch Workloads in the Cloud with Case Studies
Abstract: The rapid adoption of cloud computing has transformed the landscape of batch processing, offering unprecedented scalability, flexibility, and cost-efficiency. However, simply migrating existing batch workloads to the cloud (the "lift-and-shift" approach) often fails to fully leverage the cloud's potential. This paper explores strategies and best practices for operationalizing batch workloads in the cloud, going beyond mere migration to achieve true cloud-native optimization. We delve into key considerations such as orchestration, data management, monitoring, error handling, security, and cost optimization. Through a comparative analysis of leading cloud platforms (AWS, Azure, and GCP) and real-world use cases, we provide a comprehensive guide for organizations seeking to unlock the full potential of batch processing in the cloud-native era.
Keywords: Cloud-Native, Batch Processing, AWS, Azure, GCP, Orchestration, Data Management, Monitoring, Error Handling, Security, Cost Optimization
Edition: Volume 9 Issue 7, July 2020,
Pages: 2031 - 2041