eBay manages an immense volume of data, processing 1.2 petabytes of logs daily and 5 million metric data points per second, by employing a sophisticated system of containerization and monitoring tools. Initially, eBay's team faced challenges in adapting to the dynamic nature of applications and environments, prompting the adoption of Docker and Kubernetes to streamline deployments. To handle the rapidly evolving data landscape, they turned to Beats, specifically Filebeat and Metricbeat, for log and metric collection, and developed Collectbeat for autodiscovery of new pods in Kubernetes clusters. They further enhanced data tagging with the 'add_kubernetes_metadata' processor to append essential metadata, enabling better analysis and visualization. As data volumes continue to grow, eBay employs strategies like tier-based quota and retention limits and prioritizing event data to efficiently manage resources. These efforts are part of their broader strategy, demonstrated in their internal system, Sherlock.io, to maintain operational visibility and adapt to technological advancements.