Collectd 101.

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Presentation transcript:

Collectd 101

What is collectd? collectd is a system statistics collection daemon; it uses plugins to collect system statistics and can publish those statistics in a number of ways. Free open source project, GNU General Public License, version 2 (GPLv2), the remaining files are licensed under other open source licenses collectd also provides some simple thresholding and event notification capabilities Most plugins in collectd fall under one of the following categories: Input plugins: read system statistics at a regular interval, and dispatch the values to the collectd daemon. Output plugins: receive dispatched values from the daemon and output/write/dispatch those values in various output formats (e.g. JSON, SNMP, AMQP, MySQL, HTTP, etc).

Collectd data flow

Other collectd plugin catagories Binding plugins: which provide language bindings for collectd to allow plugins to be written in languages other than C. Logging plugins: which write information to log files or dispatch messages to syslog. Notification plugins: enable limited monitoring support in collectd. Other plugins which can both read and dispatch values.

Collectd plugin architecture Many collectd plugins can be enabled simultaneously, with input plugins collecting statistics/metrics on the platform and dispatching those values to the collectd daemon. The daemon will then pass the values to all enabled write plugins

Why use collectd? The collectd API, the selection of available plugins (90+) coupled with the modular nature of collectd architecture, provides a generic path to expose platform statistics from all existing plugins and newly developed plugins to OpenStack or other fault management applications. collectd also has bindings for several programming languages, which allows a developer to implement a plug-in in their language of choice, without having to modify the receiver of the collected metrics, for example Ceilometer itself.

collectd Statistics Statistics in collectd consist of a value list. A value list includes: Values Value length: the number of values in the data set. Time: timestamp at which the value was collected. Interval: interval at which to expect a new value. Host: used to identify the host. Plugin: used to identify the plugin. Plugin instance (optional): used to group a set of values together. For e.g. values belonging to a DPDK interface. Type: unit used to measure a value. In other words used to refer to a data set. Type instance (optional): used to distinguish between values that have an identical type. meta data: an opaque data structure that enables the passing of additional information about a value list. “Meta data in the global cache can be used to store arbitrary information about an identifier”  Within collectd notifications and performance data are dispatched in the same way Host, plugin, plugin instance, type and type instance uniquely identify a collectd value. Host, plugin, plugin instance, type and type instance uniquely identify a collectd value

collectd Values Values, can be one of: Derive: used for values where a change in the value since it’s last been read is of interest. Can be used to calculate and store a rate. Counter: similar to derive values, but take the possibility of a counter wrap around into consideration. Gauge: used for values that are stored as is. Absolute: used for counters that are reset after reading

collectd Data Sets Values lists are often accompanied by data sets that describe the values in more detail. Data sets consist of: A type: a name which uniquely identifies a data set. One or more data sources (entries in a data set) which include: The name of the data source. If there is only a single data source this is set to “value”. The type of the data source, one of: counter, gauge, absolute or derive. A min and a max value. Values lists are often accompanied by data sets that describe the values in more detail. Data sets consist of: A type: a name which uniquely identifies a data set. One or more data sources (entries in a data set) which include: The name of the data source. If there is only a single data source this is set to “value”. The type of the data source, one of: counter, gauge, absolute or derive. A min and a max value. Types in collectd are defined in types.db. Examples of types in types.db: bitrate value:GAUGE:0:4294967295 counter value:COUNTER:U:U if_octets rx:COUNTER:0:4294967295, tx:COUNTER:0:4294967295 In the example above if_octets has two data sources: tx and rx.

Examples of types in collectd Examples of types in types.db: bitrate value:GAUGE:0:4294967295 counter value:COUNTER:U:U if_octets rx:COUNTER:0:4294967295, tx:COUNTER:0:4294967295 In the example above if_octets has two data sources: tx and rx.

collectd notifications Notifications in collectd are generic messages containing: An associated severity, which can be one of OKAY, WARNING, and FAILURE. A time. A Message A host. A plugin. A plugin instance (optional). A type. A types instance (optional). Meta-data.

Filter Configuration Starting with collectd 4.6 there is a powerful filtering infrastructure implemented in the daemon. The concept has mostly been copied from ip_tables. Terminology: Match:  criteria to select specific values.  Target: action that is to be performed with data. Rule: The combination of any number of matches and at least one target Chain: a list of rules and possibly default targets. Rules tried in order and if one matches, the associated target will be called.

Precache and post cache chains When "read" plugins call the dispatch functions to dispatch values, the pre-cache chain is run. The values are then added to the internal cache. The post-cache chain is run after the values have been added to the cache.  Allows you to remap value names. The cache is also used to convert counter values to rates. More info @ https://collectd.org/documentation/manpages/collect d.conf.5.shtml#filter_configuration

Platform Metrics and Information Can be divided into static and dynamic information. Supported metrics by collectd: https://wiki.opnfv.org/display/fastpath/Collectd+Metrics+and+Events Next Steps: start defining list of static and dynamic metrics under category sets.