A SQL-powered framework for instrumenting, monitoring, and analyzing operating systems across Linux, macOS, and Windows.
osquery is an operating system instrumentation framework that exposes OS data as relational database tables queryable with SQL. It allows security and operations teams to monitor system state, detect anomalies, and perform analytics across Linux, macOS, and Windows hosts. By representing concepts like running processes, network connections, and file changes as SQL tables, it provides a unified interface for system exploration and monitoring.
Security engineers, DevOps professionals, and system administrators who need to monitor and analyze endpoint security, compliance, and operational state across large fleets of computers. It's particularly valuable for teams building security monitoring platforms or internal infrastructure tooling.
Developers choose osquery because it replaces fragmented OS-specific tools with a consistent SQL interface, enabling complex joins and aggregations across system data. Its extensible plugin architecture and cross-platform support make it uniquely suited for building scalable monitoring solutions without reinventing low-level instrumentation.
SQL powered operating system instrumentation, monitoring, and analytics.
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Enables familiar SQL syntax for querying OS data, allowing complex joins and aggregations like in the example queries for processes and network connections, replacing fragmented command-line tools.
Provides uniform table schemas across Linux, macOS, and Windows, simplifying monitoring in heterogeneous environments as highlighted in the README's support for multiple platforms.
Supports adding custom tables via a plugin API, allowing teams to instrument specific OS abstractions beyond the built-in set, fostering customization for unique use cases.
Offers ad-hoc shell, scheduled queries via osqueryd, and Thrift API integration, catering to exploratory analysis or continuous monitoring workflows as described in the documentation.
Running resource-intensive SQL queries can consume significant CPU and memory, potentially affecting system performance, especially during frequent scheduled checks on constrained hardware.
For scalable deployments, osquery requires external fleet managers like Fleet or Kolide, adding setup and maintenance complexity, as the README notes these are not endorsed or tested by the project.
Developing new tables or extensions involves understanding the C++ plugin API, which can be prohibitive for teams without deep programming expertise, limiting rapid adaptation.