MLOps
Empowering Real-World Applications with Artificial Intelligence
Why is this solution best for you?
What problems does MLOps help to solve?
Flexible Deployment Options
With Devopsbay, you do not have to readjust your business to meet the stringent requirements of the limited deployment options of an ML project. We believe it is the software that has to be tailored to the business and production needs. Thus, making it compatible with the existing infrastructure is one of our highest priorities.
Deep Learning Resource Orchestration
Scalability is one of the most-wanted features in any modern software and AI-based tools offered by Devopsbay are designed for smart autoscaling. An intelligent scaling process understands the optimal amount of resources required for desired software performance and is capable of dynamic correction to fulfill the computational demands of a changing workload.
Elastic GPU Scheduler
A fixed GPU amount allocated to tasks featuring high resource consumption can significantly prolong their completion and make them less efficient. For Deep Learning, it means extended training time. An elastic GPU scheduler we offer is capable of dynamic modification for better matching the available resources to the exact needs of the training process.
Performance Monitoring
Automation is a key to cost-effectiveness, and we know some processes are ideal candidates for automation. Performance monitoring can be considerably improved by the automation of an incident management system that can handle a resource provision issue and allocate more resources if needed without human supervision. This functionality reduces downtime and related costs.
Why us?
Our employees about MLOps
Launching a powerful ML-based application with Devopsbay
Building ML software can be challenging with its costly, complex and large-scale infrastructure, design and development bottlenecks. Fortunately, we know ways to address these issues and make artificial intelligence work for you. At Devopsbay, we have established reliable guidelines and best practices for our ML-powered applications that helped us to complete demanding projects in collaboration with world-known brands of the AI world.