Operational Excellence: Best Practices for Monitoring in Data - Intensive Applications

Mahidhar Mullapudi, Aditya Vamsi Mamidi, Mahesh Babu Munjala

Abstract: This paper delves into advanced strategies for fortifying operational excellence in data - intensive applications, with a specific emphasis on harnessing the capabilities of Microsoft Azure's comprehensive cloud stack. Focusing on key Azure services such as Azure Functions, Azure Data Factory (ADF) Pipelines, Kusto, Azure Service Bus, and Event Grid. This study highlights the best practices for monitoring and maintaining critical services. Recognizing the pivotal role of monitoring and alerting, the paper underscores their significance in ensuring the stability and performance of data - intensive applications. In addition to established metrics like total artifacts generated, ingestion success rate, and runtime statistics, the discussion introduces nuanced approaches to monitoring real - time latency, resource utilization patterns, and anomaly detection mechanisms. These refined metrics provide a comprehensive view of system health, enabling organizations to proactively address challenges and optimize performance in large - scale data applications on the Azure cloud stack.

Keywords: Modern DataIngestion Platform, Artifact Analytics, Azure Event Hub, Azure Service Bus, Azure Data Factory (ADF) Pipelines, Azure Functions, Azure Kusto (Azure Data Explorer), Operational Excellence

How to Cite?: Mahidhar Mullapudi, Aditya Vamsi Mamidi, Mahesh Babu Munjala, "Operational Excellence: Best Practices for Monitoring in Data - Intensive Applications", Volume 10 Issue 3, March 2021, International Journal of Science and Research (IJSR), Pages: 1950-1955, https://www.ijsr.net/getabstract.php?paperid=SR24203225052, DOI: https://dx.doi.org/10.21275/SR24203225052