ITGSS Certified DevOps Engineer Practice Test 2025 - Free DevOps Practice Questions and Exam Preparation Guide

In Kubernetes, cluster-based logging is a pivotal method for aggregating and managing logs from various containers and applications running within the cluster. This approach involves collecting logs from multiple sources in a centralized repository, making it easier to analyze and monitor the system's overall performance. Cluster-based logging typically integrates various tools and systems tailored for log aggregation, such as Elasticsearch, Fluentd, and Kibana (often referred to as the EFK stack).

By leveraging cluster-based logging, administrators and DevOps engineers can gain insight into container behavior, troubleshoot issues, and perform audits more effectively. This method enhances observability, allowing for real-time log collection and analysis across all containers, regardless of where they are hosted within the Kubernetes environment.

Other logging methods, such as file-based logging, focus on logs generated on individual containers, which may lead to difficulties in managing and analyzing logs when scaling to multiple containers. Database logging centers around storing logs in a database format, which may not be as efficient or straightforward for large volumes of transient log data common in containerized environments. Memory logging would involve temporary/logging in volatile memory, which is not practical for persistent log storage or aggregation since it would be lost with a restart or crash. Thus, cluster-based logging is the most