The ELK Stack, consisting of Elasticsearch, Logstash, Kibana, and Beats, offers a comprehensive solution for monitoring applications by providing scalable data storage, data processing, visualization, and data collection capabilities. This article details the process of installing the ELK Stack on an Azure virtual machine, starting with setting up the Azure environment and proceeding through the installation and configuration of each component. Notably, Elasticsearch and Kibana were closed-sourced by Elastic in 2021, leading AWS to introduce OpenSearch as an open-source alternative. While setting up ELK can be straightforward, scaling it to handle large cloud workloads presents challenges, such as the need for additional architectural components like a buffering layer. For organizations seeking to avoid the complexity of managing ELK themselves, Logz.io offers a managed solution with enhanced features and seamless integration with Azure.