Metadata-Version: 2.2 Name: pcp Version: 5.0 Summary: Performance Co-Pilot collector, monitor and instrumentation APIs Home-page: https://pcp.io Author: Performance Co-Pilot Development Team Author-email: pcp@groups.io License: GPLv2+ Keywords: performance,analysis,monitoring Platform: Windows Platform: Linux Platform: FreeBSD Platform: NetBSD Platform: OpenBSD Platform: Solaris Platform: Mac OS X Platform: AIX Classifier: Development Status :: 5 - Production/Stable Classifier: Intended Audience :: Developers Classifier: Intended Audience :: System Administrators Classifier: Intended Audience :: Information Technology Classifier: License :: OSI Approved :: GNU General Public License (GPL) Classifier: Natural Language :: English Classifier: Operating System :: MacOS :: MacOS X Classifier: Operating System :: Microsoft :: Windows Classifier: Operating System :: POSIX Classifier: Operating System :: POSIX :: AIX Classifier: Operating System :: POSIX :: BSD :: NetBSD Classifier: Operating System :: POSIX :: BSD :: OpenBSD Classifier: Operating System :: POSIX :: BSD :: FreeBSD Classifier: Operating System :: POSIX :: Linux Classifier: Operating System :: POSIX :: SunOS/Solaris Classifier: Operating System :: Unix Classifier: Topic :: System :: Logging Classifier: Topic :: System :: Monitoring Classifier: Topic :: System :: Networking :: Monitoring Classifier: Topic :: Software Development :: Libraries Description-Content-Type: text/x-rst Dynamic: author Dynamic: author-email Dynamic: classifier Dynamic: description Dynamic: description-content-type Dynamic: home-page Dynamic: keywords Dynamic: license Dynamic: platform Dynamic: summary Performance Co-Pilot ==================== Performance Co-Pilot (PCP) provides a framework and services to support system-level performance monitoring and management. It presents a unifying abstraction for all of the performance data in a system, and many tools for interrogating, retrieving and processing that data. PCP is a feature-rich, mature, extensible, cross-platform toolkit supporting both live and retrospective analysis. The distributed PCP architecture makes it especially useful for those seeking centralized monitoring of distributed processing. For more information and details on how to contribute to the PCP project visit `pcp.io `_.