Appendix B. GFS2 Tracepoints and the debugfs glocks File

There are currently three types of GFS2 tracepoints: glock (pronounced "gee-lock") tracepoints, bmap tracepoints and log tracepoints. These can be used to monitor a running GFS2 file system and give additional information to that which can be obtained with the debugging options supported in previous releases of Red Hat Enterprise Linux. Tracepoints are particularly useful when a problem, such as a hang or performance issue, is reproducible and thus the tracepoint output can be obtained during the problematic operation. In GFS2, glocks are the primary cache control mechanism and they are the key to understanding the performance of the core of GFS2. The bmap (block map) tracepoints can be used to monitor block allocations and block mapping (lookup of already allocated blocks in the on-disk metadata tree) as they happen and check for any issues relating to locality of access. The log tracepoints keep track of the data being written to and released from the journal and can provide useful information on that part of GFS2.

The tracepoints are designed to be as generic as possible. This should mean that it will not be necessary to change the API during the course of Red Hat Enterprise Linux 7. On the other hand, users of this interface should be aware that this is a debugging interface and not part of the normal Red Hat Enterprise Linux 7 API set, and as such Red Hat makes no guarantees that changes in the GFS2 tracepoints interface will not occur.

Tracepoints are a generic feature of Red Hat Enterprise Linux 7 and their scope goes well beyond GFS2. In particular they are used to implement the blktrace infrastructure and the blktrace tracepoints can be used in combination with those of GFS2 to gain a fuller picture of the system performance. Due to the level at which the tracepoints operate, they can produce large volumes of data in a very short period of time. They are designed to put a minimum load on the system when they are enabled, but it is inevitable that they will have some effect. Filtering events by a variety of means can help reduce the volume of data and help focus on obtaining just the information which is useful for understanding any particular situation.