Kigred, Another possible solution base on the error "out-of-memory" is to set the value of the Java Virtual Machine heap maximum size, also make sure it is not limited and depending on your deployment the value must be set in the docker compose, the K8s descriptor, the Tomcat environment file, etc.
If you set this value for your Apache Fineract instance (this is ONLY an example): JAVA_TOOL_OPTIONS="-Xmx6G" It means “limit Apache Fineract heap size to 6 GB.” Try to use different values not greater than the available memory of your system. And use different workloads. This process is called fine tuning. Regards Victor El mié, 10 sept 2025 a las 7:16, Kigred Developer (< [email protected]>) escribió: > Hello Devs, > > You find that when groups are starting financial operations with small > number of transactions (both loans and savings) and the minimum machine > specs will work fine for sometime. This changes with time as the number of > transactions grows and overnight jobs hit out-of-memory issues. > > Is it a good idea to tweak a job such that it approaches the task > batch-wise? For example you find the an 8GB machine will process 1000 > standing instructions without a problem but run into memory exceptions when > the number of instructions changes to 1200. So it a good idea to tweak the > job such it handles the 1000 to 1200 instructions in batches of say 250 > instructions, then another 250 etc? With the same machine job will handle > task without running into memory issues. > > Is this the way it should work? What is the other way (without changing > server specs)? > > Regards. > Wilfred >
