Integrating DevOps Practices in Cloud-Based Analytics Platforms to Optimize Large-Scale Data Processing Systems
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Integrating DevOps Practices in Cloud-Based Analytics Platforms to Optimize Large-Scale Data Processing Systems
Authors:
Satyadeepak Bollineni
Senior DevOps Engineer
Databricks
Texas, USA
Email: deepu2020@gmail.com
Abstract— In this study, the application of DevOps practices in cloud-based analytics platforms indicates a way to enhance the performance of large-scale data processing systems. This integration would positively affect increased agility, scalability, and efficiency due to the implementation of continuous integration, automated deployment, and consistent monitoring. Also explored is how these practices enhance reliability in operations and adapt to changing business landscapes. The study confirms that the operational metrics gained significant improvements, such as throughput, uptime, downtime, and resource utilization, offering a big capacity and performance boost to data operations. These results illustrate the enormous impact and value of DevOps in complex data environments, thus encouraging the application of DevOps as a key strategy in contemporary data management.
Keywords— DevOps Practices, Cloud-Based Analytics, Data Processing Systems, Operational Efficiency, Continuous Integration, Automated Deployment