The Transition from Monolithic SIEMs to Data Lakes for Security Monitoring

This generation of security analytics tools is based on a decoupled data architecture combining cloud storage, open data formats, and highly performant distributed query engines. While this provides improved performance, scalability, and new pricing models for security teams, it comes with a nuance in usability and technical understanding. This blog explores the transition from SIEM to security data lakes, discusses their key components, strategies for interoperability, and query engines for such workloads. The roles of detection engineers and security analysts are distinctly different and mirrored in the technologies that cater to each. Security analysts are often experts in understanding attacker TTPs, and detection engineers specialize in tool accuracy, performance, and capabilities to identify those TTPs. Thus, when responding to incidents, analysts need tools that provide exhaustive answers, and platforms like Splunk and Elastic enabled that by indexing all of the data and couplin

This generation of security analytics tools is based on a decoupled data architecture combining cloud storage, open data formats, and highly performant distributed query engines. While this provides improved performance, scalability, and new pricing models for security teams, it comes with a nuance in usability and technical understanding. This blog explores the transition from SIEM to security data lakes, discusses their key components, strategies for interoperability, and query engines for such workloads. The roles of detection engineers and security analysts are distinctly different and mir