Daniel Berman's blog post explores the installation of the ELK Stack—comprising Elasticsearch, Logstash, and Kibana—using Docker, highlighting its practicality despite Docker's ephemeral nature. Typically installed on Linux or Unix-based systems, the post emphasizes Docker's convenience for setting up the stack, with Docker Compose facilitating the process by deploying three containers for each ELK component. The article details the steps for cloning the necessary repository, configuring Docker Compose files, and starting the stack, as well as verifying its successful deployment through port mapping and container status checks. Berman also covers data shipping into the Dockerized ELK Stack, suggesting the use of Filebeat or Metricbeat to forward logs and metrics, and provides a brief guide on configuring Metricbeat to send data to Elasticsearch. Finally, he notes that while Docker is effective for development and testing environments, it is increasingly being adopted for production use, though such deployments require more complex architectural considerations.