Getting a quick view of your PostgreSQL stats by

Database health monitoring is important, especially if you are running your servers 24x7 and aiming for no downtime. There are a number of tools to show interesting database-related statistics in a pretty web interface, from home- grown solutions based on Nagios or Zabbix to specialized web apps; one of them, PGObserver, is developed by our colleagues at Zalando. On other occasions one needs a detailed real-time view of the database and system metrics that can be launched from the terminal: for instance, a DBA might want to monitor system load, query locks and I/O utilization during the lengthy data migration. Previously, we used a combination of  Linux system utilities like uptime or iostat, information from /proc and data from pg_stat_activity put together as a shell alias. But nowadays we have something more powerful, a new tool called pg_view.

pg_viewscreenshot

pg_view’s basic idea is to combine the indicators commonly displayed by sar or iostat with the output from PostgreSQL process activity view to present global and per-process statistics in a way that is easy to interpret on a quick glance.

The default output includes every database running on the current host. For each of them, various measurements for the xlog and data partitions are displayed, as well as the combined output from pg_stat_activity and process information, i.e. read/write rates in MB/s, processor time spent in system and user mode, unix process state and some other details. The upper part of the screen contains overall system statistics, like the CPU utilization, memory used/available, host uptime and other parameters typically included in the top-like monitoring utilities.

With the help of ncurses module, pg_view highlights problematic values to be instantly noticeable by a DBA. For example, on the screenshot above the query waiting on a lock is highlighted in red, indicating a potential problem, and the idle in transaction status is displayed in blue (warning). Both of those conditions may lead to overall performance decrease and unplanned maintenance. The indicators that require immediate attention are also shown in red, i.e. the fact that the data partition will be full in just a couple of seconds is highlighted.

The curses library also provides necessary facilities to make the interface scalable, so one can view multiple hosts at once on a split terminal screen or have a small window open for a mission-critical database to keep an eye on it at load peaks. We tried to keep the system requirements reasonable, opting for Python 2.6 and PostgreSQL python adapter psycopg2 as the only external module. At the moment, the script relies heavily on the /proc/ filesystem, meaning that it only works in Linux environment.

Among the many features pg_view has an ability to switch its output to a plain text or json format, so the data collected can be processed by other applications. The script is designed to be extensible: adding other output methods (i.e. storing results in a database) shouldn't be a problem. The best part, of course, is that it is the latest addition to the growing Zalando open-source toolchain:


More posts about backend database development open-source pg-view postgresql