Key Metrics
- Projects: Keep track of the number of projects allocated within your subscription. Projects serve as organizational units for managing data annotation, model training, and deployment tasks.
- Team Members: Monitor the number of team members invited to collaborate within your workspace. Team members play vital roles in project execution and collaboration.
- Datasets: Track the number of images uploaded to your workspace datasets. Datasets serve as the foundation for training and validation data used in model development.
- Dataset Versions: Keep tabs on the number of dataset versions created within your workspace. Dataset versioning allows for iterative improvements and tracking changes over time.
- Models: Monitor the number of model versions trained within your workspace. Models are trained using annotated data from datasets to perform specific tasks such as image classification or object detection.
- Inference: Track the number of API calls made to make predictions on trained models. Inference activity indicates the utilization of deployed models for real-world applications, such as making predictions on new data.
Optimizing Resource Utilization
By monitoring usage metrics across these key areas, you can:- Allocate Resources Effectively: Understand resource consumption patterns to allocate resources efficiently based on project needs and priorities.
- Scale Workloads Appropriately: Identify areas of high usage and scale resources accordingly to maintain performance and meet demand.
- Optimize Collaboration: Manage team member invitations and project allocations to facilitate effective collaboration and project management.
- Budget Planning: Use usage insights to inform budget planning and resource allocation decisions, ensuring alignment with organizational objectives and constraints.