Moodss is a modular monitoring application, which supports operating systems (Linux, UNIX, Windows, etc.), databases (MySQL, Oracle, PostgreSQL, DB2, ODBC, etc.), networking (SNMP, Apache, etc.), and any device or process for which a module can be developed (in Tcl, Python, Perl, Java, and C). An intuitive GUI with full drag'n'drop support allows the construction of dashboards with graphs, pie charts, etc., while the thresholds functionality includes emails and user defined scripts. Monitored data can be archived in a SQL database by both the GUI and the companion daemon, so that complete history over time can be made available from Web pages or common spreadsheet software. It can even be used for future behavior prediction or capacity planning, from the included predictor tool, based on powerful statistical methods and artificial neural networks.
|Tags||Database Internet Web Site Management Scientific/Engineering Systems Administration Operating System Kernels Linux Networking Monitoring|
|Implementation||C Perl Python Tcl|
Release Notes: The ability to edit thresholds per page was added in order to easily manage large quantities of thresholds. The email library was patched to ensure that messages' data sections are properly terminated. The usual minor improvements and bugfixes were also made.
Release Notes: In this release, an important bug in the File/Modules/Manage/Loaded dialog box was fixed. The thresholds dialog box opening and closing times were significantly improved. Usual minor improvements were also included.
Release Notes: In this release, performance on big dashboards with many thresholds was significantly improved, and the snmptrap module was made compatible with the Tnm SNMP library version 3, also successfully tested on OS X. Several minor improvements and bugfixes were made.
Release Notes: This release makes sure that when the moodss or moomps applications exit, the modules perform their termination procedure. The Apache modules load properly again. Many improvements and bugfixes related to 64-bit platform support were made.
Release Notes: In the predictor tool, finding the main period of the analyzed data using a Fast Fourier Transform is allowed. A new myshow module was added for monitoring either the status or the system variables of a MySQL database server. Minor improvements and bugfixes were also made.