ID: 8052 Title: Speedup availability queries by new caching (disabled per default) Component: Livestatus Level: 3 Class: New feature Version: 1.2.5i4 The Check_MK Micro Core now has an alternative implementation of the Livestatus table <tt>statehist</tt>. This table is the basis for all availability computations. In the current implementation, which is still the only when using the Nagios core, for each query all historic logfiles that cover the query range have to be evaluated. Despite caching this can mean an intense effort in CPU and IO usage. If you have a larger number of hosts and services then a query for a larger time frame could last for minutes. The new implementation needs to be enabled in the global settings for the Check_MK Micro Core: <i>In-memory cache for availability data (experimental)</i>. You also have to configure a time range. This limits how long into the past you can do availability queries. The default setting is two years. During the start of The Core all historic log files for that time ranged are parsed into a very efficient in-memory database so that future availability queries do not need any disk IO or logfile parsing. The cache is automatically updated when new alerts happen. Please also note that The Core is not restarted during normal operation and activation of changes, so the cache is just invalidated when you reboot your server or do a software update of Check_MK. The parser can process 500.000 messages per second and more, so if your disk IO is fast enough even parsing a large history does not take longer than a couple of minutes. This is done in the background and does not prevent The Core from working or queries from being answered. Even availability queries are being answered while the cache is still being built up. If the queried time range is already in the cache then the query can immediately be processed. Otherwise it waits for the cache to be ready. When it comes to timeperiod definitions the new implementation has a different behaviour: It reflects later changes in the definitions of your timeperiods. This is conveniant when you want to work with service periods for your availability queries. The classical implementation evaluates the <tt>TIMEPERIOD TRANSITION</tt> entries in your logfiles. The new one directly takes the current definitions into account and computes them for the time range in the past. <b>Note:</b> As of today this implemention is still highly <i>experimental</i> and might not only produce wrong results, but might crash your core.