High memory usage with collectd

collectd itself is intended as lightweight collecting agent for metrics and events. In larger infrastructure, the data is sent over the network to a central point, where data is stored and processed further.

This introduces a potential issue: what happens, if the remote endpoint to write data to is not available. The traditional network plugin uses UDP, which is by definition unreliable.

Collectd has a queue of values to be written to an output plugin, such was write_http or amqp1. At the time, when metrics should be written, collectd iterates on that queue and tries to write this data to the endpoint. If writing was successful, the data is removed from the queue. The little word if also hints, there is a chance that data doesn't get removed. The question is: what happens, or what should be done?

There is no easy answer to this. Some people tend to ignore missed metrics, some don't. The way to address this is to cap the queue at a given length and to remove oldest data when new comes in. The parameters are WriteQueueLimitHigh and WriteQueueLimitLow. If they are unset, the queue is not limited and will grow until memory is out. For predictability reasons, you should set these two values to the same number. To get the right value for this parameter, it would require a bit of experimentation. If values are dropped, one would see that in the log file.

When collectd is configured as part of Red Hat OpenStack Platform, the following config snippet can be used:

      collectd::write_queue_limit_high: 100
      collectd::write_queue_limit_low: 100

Another parameter can be used to limit explicitly the queue length in case the amqp1 plugin is used for sending out data: the SendQueueLimit parameter, which is used for the same purpose, but can differ from the global WriteQueueLimitHigh and WriteQueueLimitLow.

        collectd::plugin::amqp1::send_queue_limit: 50

In almost all cases, the issue of collectd using much memory could be tracked down to a write endpoint not being available, dropping data occasionally, etc.