Sun Java System Messaging Server 6.3 Administration Guide

19.3 Configutil Parameters for MeterMaid

MeterMaid's configuration is stored in msg.conf and is maintained by configutil. Here are some of the settings currently supported by MeterMaid. Defaults are in parenthesis. See configutil Parameters in Sun Java System Messaging Server 6.3 Administration Reference for complete list of MeterMaid parameters.

Chapter 19, Throttling Incoming Connections Using MeterMaid

These settings are used by the check_metermaid client:

Lastly, the throttling tables are also defined in msg.conf as shown here. The * in each configuration parameter is the name of the particular table being defined. For example, for a table called internal, the first parameter would be called metermaid.table.internal.data_type.


Note –

Metermaid was coded to be as efficient as possible, but may not match your expectations as it uses weighted averages to limit the connection rate rather than maintaining a list of just how many connections there have been over the previous quota_time period.

For example, let's say you are trying to limit connections to 1250 mails per hour (metermaid.table.tcp_auth_msg_throttle.quota = 1250). This limits connections to an average rate of 1250/hour. In other words, if all 1250 connections are used up in the first second, then half an hour later, an additional 625 are provided. After another 15 minutes, you'd get another 362, and so on.

A common misconception is that one hour after the initial connection attempt, all will be forgiven. But Metermaid looks at an average connection rate rather than a specific count. The net effect is the same in the long run (over a 24 hour period, a total of 1250 * 24 would be allowed), but it's not mathematically precise in a short period.

A future goals for Metermaid is that instead of offering an average throughput rate, it would maintain a distinct list of connection attempts, and be able to expire each attempt after the precise time. This has not yet been done because it's a much more computationally expensive operation to maintain than computing an average rate.