The IDC survey highlights the critical role of log analytics in modern IT infrastructures, emphasizing the increasing reliance on actionable insights from machine-generated data to manage complex environments. Traditional log management systems face challenges due to the vast volume and diversity of data generated by modern technologies like cloud computing, mobile, and IoT, leading to issues such as high storage costs, integration difficulties, and manual processing requirements. As organizations handle over 100GB of log data daily, the need for next-generation log analytics with advanced capabilities such as AI and machine learning becomes evident, enabling better anomaly detection, automation, and integration within DevOps and CI/CD pipelines. Coralogix, for example, offers solutions that utilize machine learning to streamline log management and enhance software development practices by providing real-time operational intelligence and automated insights. Despite widespread adoption, many organizations still struggle to use log management effectively, underscoring the need for more sophisticated tools to address the evolving demands of IT environments.