How can I run more than one analysis at a time?

Overview

By default, CAST Imaging executes two concurrent fast scan/analysis jobs on each analysis node. You can modify this setting to increase performance based on your infrastructure needs.

⚠️ Warning: Proceed with Caution Increasing parallel executions can overload your analysis node, leading to:

  • Performance degradation
  • Timeouts and errors
  • Job crashes

Recommendations:

  • Increase the job count by one at a time only
  • Test thoroughly after each increment
  • Consider your hardware specifications before making changes
  • Best practice: Add additional analysis nodes to distribute load rather than increasing parallel jobs on a single node

Configuration process

Step 1 - Locate configuration file

The configuration file exists on each analysis node. If you have multiple nodes, repeat this process for each one.

Microsoft Windows

%PROGRAMDATA%\CAST\Imaging\CAST-Imaging-Analysis-Node\application.yml

Linux via Docker/Podman/Kubernetes

/opt/cast/installation/imaging-node/docker-compose.override.yml

Step 2 - Configure the number of jobs

Edit the configuration file to set your desired parallel job count.

Example: Changing from 2 to 3 parallel jobs:

Microsoft Windows (application.yml)

jobs:
  threadPoolSize: 3

Linux via Docker/Podman/Kubernetes (docker-compose.override.yml)

services:
    nodev3:
        environment:
            NB_OF_THREADS_FOR_NODE: 3

Save the file after making changes.

Step 3 - Apply the changes

Restart the analysis node service to apply your configuration.

Microsoft Windows

  • Open Services (services.msc)
  • Locate CAST Imaging Analysis Node
  • Right-click and select Restart
  • Repeat for each modified analysis node

Linux via Docker/Podman/Kubernetes

$ cd /opt/cast/installation/imaging-node    # navigate to installation folder    
$ sudo docker compose down                    # stop the containers
$ sudo docker compose up -d                   # start the containers in detached mode
$ sudo docker ps                              # check containers are running

Step 4 - Verification

After restarting the service, monitor your analysis node to ensure:

  • Jobs complete successfully
  • System resources remain stable
  • No timeout or memory errors occur

If issues arise, reduce the parallel job count and restart the service again.