The Advantage of MLOps for Risk and Compliance Departments
MLOps is a solution that allows teams to control their models automatically with a single, centralized hub to deploy, monitor, and update models in a consistent way.
MLOps can help risk and compliance professionals in these four areas:
MLOps makes model deployment easy. Operations teams, not data scientists, can deploy models written in a variety of modern programming languages like Python and R onto modern runtime environments in the cloud or on-premise. Users of the MLOps system don’t have to know any of these technologies to drag and drop a model into the system, create a container, and deploy the model to a production environment.
MLOps gives you monitoring that is designed for machine learning. Monitoring includes service health, data drift, model accuracy, and proactive alerts that are sent to stakeholders using a variety of channels like email, Slack, and Pagerduty. With MLOps monitoring in place, your teams can deploy and manage thousands of models, and your business will be ready to scale production AI.
Production Lifecycle Management
Models need to be updated frequently and seamlessly. MLOps model lifecycle management supports the testing and warm-up of replacement models, A/B testing of new models against older versions, seamless rollout of updates, failover procedures, and full version control for simple rollback to prior model versions.
Production Model Governance
MLOps governance provides the integrations and capabilities you need to ensure consistent, repeatable, and reportable processes for your models in production. Key capabilities include access control for production models and systems, including integration to LDAP and role-based access control systems (RBAC), as well as approval flows, logging, version storage, and traceability of results for legal and regulatory compliance.
Observe, Diagnose, and Mitigate Issues with Production Models
The majority of AI-enabled organizations are still struggling to stay atop the ever-expanding repository of production models. A myriad of issues can interfere with the performance and delivery of these models, resulting in poor or incomplete predictions and ill-informed decision-making.
DataRobot MLOps functionality addresses these and many other challenges. Experience granular model-level insights, observability of production models, and higher level of confidence for decisions informed by models.Get the Ebook