You deployed a model to a managed online endpoint in Azure Machine Learning. During a marketing campaign, the endpoint begins returning HTTP 503 'Service Unavailable' responses under peak load, while returning correct scores at normal load. The deployment currently uses a single instance with autoscaling disabled. You need to resolve the errors with the least code change while keeping cost proportional to demand. What should you do?