The user must note that these modules are based on custom behaviour called gen_db (defined in graph_db). Users can write their custom db modules, place them in the src directory of graph_db app. By default graph_db uses ETS for ram storage and levelDB for disk storage but the user is not restricted The following configurations can be found in file graph_db.app.src located at grapherl/apps/graph_db/src/graph_db.app.srcĬache_mod defines the module to be used to ram storage and db_mod defines the module to be used forĭisk storage. After a year, points at granularity of hour are purged to day and kept indefinitely.After a week, points at granularity of minute are purged to granularity of hour and kept for a year.Points at a granularity of minute are stored for a week. all points in one minute are purged and value is averaged (or processed according to the metric type). After one day these point are purged to a granularity of one minute i.e.So, we would have around 86400 points at the end of the day. Points which are aggregated each 1 sec are kept as is for one day.a server which send total number of online users each second). To understand this scheme let consider thatĪ client (i.e. Grapherl constantly purges data according to a predefined scheme.

All incoming points are aggregated into ramįurther Grapherl expects huge amount of data, so storing such amount of data as is for long is not feasible. These received packets are forwarded to a process called db_worker (which is pool of worker processes) whichĭecodes this received packet and stores it in ram (inside ETS tables). (known as router_workers) wait on the socket to receive high amount of UDP traffic. All incoming data is received by graph_db, multiple processes So that the user can wisely configure these options. graph_dbīefore we discuss the various configurations we give an overview of how this subapp works Grapherl consists of 2 components graph_db which receives UDP data and stores it, graph_web which retrieves thisĭata and creates nice visualizations for the user. If you have any queries regarding feeding data into Grapherl mail them at kansi13 at gmail dot com. You can also play around with Grapherl by feeding data using these modules. Sample python ( data_feed.py) and erlang ( testing.erl) modules which feed data into Grapherl located under the grapherl/tests directory. By default for a gauge metric values are averaged over and interval and for counter metric values are added over an interval. metric_type: there are 2 types allowed g (gauge) and c (counter).NOTE Grapherl considers client_name just as plane string meaning that there is no special interpretation for website_101.com as compared website_101, they are both just (different) strings for Grapherl. client_name: metric_name along with client_name are used to uniquely identify a point.metric_name: Specify the metric name for eg.Client_name/metric_name:metric_type/time_stamp:value

Ejabberd monitoring