What is the recommended action when Confluence experiences memory issues?

• A. Increase the number of users
• B. Disable backups
• C. Clear logs
• D. Increase the heap memory

Answer: (D)

When Confluence runs into memory issues, the usual first step is to increase the Java heap memory. Confluence operates on the JVM, and its runtime memory is largely determined by the heap size. If the heap is too small for the workload—lots of users, large pages, many attachments, or heavy caching—the JVM spends more time in garbage collection or may run out of memory, causing slow performance or outages. Allocating a larger heap gives the application more room to create and manage objects, which often reduces GC pauses and stabilizes the instance.

Implement this by adjusting the JVM startup options (for example, increasing -Xms and -Xmx) and then monitoring memory usage and garbage collection behavior to ensure the change helps without overcommitting physical RAM. If memory issues persist after widening the heap, other factors like memory leaks, large attachments, indexing tasks, or problematic plugins may need investigation.

Increasing the number of users or disabling backups won’t fix memory problems, and clearing logs might help with diagnostics but doesn’t address memory pressure directly.