Best Practices for Building Security Data Lakes on Amazon S3

This whitepaper outlines best practices for building and maintaining security data lakes and lakehouses using Amazon S3. It begins by introducing Amazon S3 as a long-standing option for storing raw and archival data, essential for big data and security teams. The document details key features and AWS-native tools for creating a security data lake, including writing data effectively, managing the 'small file problem', and applying best practices for data formats, compression, partitioning, and indexing. The paper also discusses efficient query patterns aimed at improving query performance through optimization techniques. Furthermore, it explains the distinct architectures of security data lakes and lakehouses, highlighting their costs and operational efficiencies compared to traditional databases or Security Information & Event Management (SIEM) tools. By employing these practices, users can optimize their security data lake performance and ensure effective data management, while also detailing the major AWS services involved in the architecture.