The SymantecDLPDetectionServerController service* on Enforce may use more memory in later versions of DLP than in earlier ones. The memory usage is dependent on a number of factors:
In general, large deployments may run into a need for more memory for the Monitor Controller.
*Note - prior to 15.1, this service was known as the Monitor Controller.
Perhaps you are seeing frequent "RSODs" (a red bar error appearing in Enforce Server), with the following detail:
In many cases, the addition of a second or third Cloud Detector puts these detection servers into a "Disconnected" state - usually resolved by recycling the DS Controller service.
All supported versions of DLP.
Based on load and conditions listed, the DetectionServerController (aka MonitorController) would benefit from tuning for better performance.
To increase the memory for the Monitor Controller, modify your installation as per the following:
In supported versions, update SymantecDLPDetectionServerController.conf file, located by default in this DLP directory:
Below are the current defaults for all supported versions (15.8 and 16.0 as of 2023):
# Initial Java Heap Size (in MB) wrapper.java.initmemory=1024 # Maximum Java Heap Size (in MB) wrapper.java.maxmemory=2048
For customers of the DLP Cloud Services, it is recommended to increase this default further.
# Initial Java Heap Size (in MB)
# Maximum Java Heap Size (in MB)
After making the above changes, be sure to restart the SymantecDLPDetectionServerController process or service.
Note: For better performance, or in very large enterprises, these settings can be increased further, even to 8 and 16 GB, respectively. Be sure to confirm the amount of memory installed on the server before modifying beyond above recommendations. A good rule of thumb is to set the maxmemory to <= 25% of RAM on the box.
Sometimes the following errors are present for the performance issues given in this KB, but the absence of these errors does not mean performance issues do not exist.
SEVERE: Could not reload command instructions
java.lang.OutOfMemoryError: GC overhead limit exceeded
Exception in thread "Incidents_application_updaterWorker_1" java.lang.OutOfMemoryError: Java heap space