Centralized log management is essential for understanding and troubleshooting modern cloud infrastructures by unifying log data collection, processing, storage, and analysis, thus accelerating mean time to recovery (MTTR) and simplifying administrative tasks. While it offers numerous advantages, such as improved data security and streamlined access to log data, it also presents challenges like high data volumes and associated costs, which can lead to inefficiencies and security issues if not managed properly. Best practices to mitigate these issues include organizing log data by team, filtering out unnecessary logs to reduce costs, and utilizing machine learning for faster log analytics. Ensuring flexibility to avoid vendor lock-in and integrating log data with metrics and traces for a comprehensive observability strategy are crucial for effective log management. Various log management tools like Fluentd, Fluent Bit, ELK Stack, OpenSearch, Splunk, and Logz.io offer different strengths and should be chosen based on priorities like data security, cost, and flexibility.