Scaling limits

Maximum Model Size: SysON is built to manage large models, but there are practical limits to its capacity. The system can efficiently handle models up to about 10 MB in size. Models larger than this might experience performance degradation, especially in terms of loading times and responsiveness.

Impact on Performance: As model size increases, users might meet longer loading times and slower response rates when performing operations such as editing or navigating the model. It’s recommended to break down exceptionally large models into smaller, manageable sub-models where feasible.

Element Capacity: SysON can manage models containing up to 150,000 semantic elements. These elements include elements, relationships, and attributes that define the structure and behavior of the model.

Performance Considerations: Exceeding this number might lead to increased memory usage and slower query responses. For optimal performance, it’s advisable to maintain a balance and avoid overly complex models that push the upper limit of this capacity.

Representation Limits: The system supports up to 2,000 distinct representations per project.

Complexity and Usability: While the system can handle a high number of representations, maintaining a clear and organized structure is crucial. Overloading a project with too many representations can complicate navigation and reduce usability.

Element Density: A single representation can display up to 1,000 elements. Beyond this, the representation might become cluttered, making it difficult to interpret and work with the visual data.

Performance and Visualization: High-density representations may slow down rendering times and interaction speed. It’s beneficial to segment large visualizations into smaller, more focused views to maintain clarity and performance.

Project Management: SysON can support up to 1,000 concurrent projects per server. This allows organizations to manage multiple initiatives simultaneously without significant performance degradation.

Server Load: The number of projects impacts server load and resource allocation. While the system can support a high number of projects, each project adds to the computational and storage demands, so server capacity should be scaled so.

User Capacity: The system is designed to support up to 80 concurrent users on a single server. This capacity ensures that people can collaborate in real-time without encountering significant slowdowns or access issues.

Collaboration Dynamics: The performance of collaborative features, such as live editing and real-time updates, might vary depending on the number of users and the complexity of the operations being performed. For larger teams, it’s important to monitor server load and possibly segment users across multiple servers if necessary.

Model Partitioning: To manage large models, consider breaking them down into smaller, modular sub-models. This can help maintain performance and make it easier to manage and navigate complex data.

Efficient Representations: Limit the number of elements displayed in each representation to avoid clutter and maintain responsiveness. Use multiple, focused representations instead of one overloaded view.

Scalable Infrastructure: Ensure that your server infrastructure is scalable to handle increases in project load and user concurrency. This might involve using cloud-based solutions that can dynamically allocate resources as needed.

Regular Monitoring: Implement regular monitoring of system performance and user activity to identify and address potential bottlenecks. This can help maintain smooth operation even as the scale of use increases.

Contact us for custom solutions: If your needs exceed the outlined limits or you require specific performance optimizations, please contact us. Our team can provide tailored solutions and advice to ensure that SysON meets your scaling requirements effectively.