Machine learning (ML) observability tools are indispensable for data scientists and developers to understand, monitor, and improve the performance of machine learning models. These tools provide deep insights into understanding, monitoring, and improving model performance, identifying potential issues such as prediction drift or data anomalies, and facilitating performance improvements. Beyond real-time performance and ensuring model accuracy, observability tools promote accountability, especially in navigating complex ethical issues in AI. Arize AI is a platform that offers AI observability, automated model monitoring, embedding, and cluster evaluation, and prompt iteration/troubleshooting. However, alternative tools like Encord Active, Aporia, DeepChecks, Fiddler AI, Superwise, SageMaker Model Monitor, WhyLabs, IBM Watson Studio, Voxel51, Azure Machine Learning, Databricks, and Vertex AI offer larger scalability, more customization freedom, better insights, and other diverse features to consider.