WhyLabs is the second observability platform I have ever used, and I can say the core features I like about the platform is that it is easy to set up and implement the features, the checks and metrics were already pre-loaded so I did not need to do much in configuring the application, and monitoring was not difficult to get started with. It also integrates well with the serving and data libraries we used for the production tutorial setup.

WhyLabs is an exceptional observability tool for applications built with large language models. Its ease of use enables us to integrate langkit into the existing architecture. Additionally, they have an excellent customer support community.

I've used WhyLabs for a few weeks and I was extremely pleased with it! I will evaluate some dimensions of the tool that summarize my experience with it. Easy Data Ingestion: The ingestion API is straightforward to use and supports multiple connectors such as BigQuery, Databricks, and Spark, making data importation easy. Whylabs' use of Data Profiling ensures fast and secure data processing, eliminating the need to upload entire datasets, and making all the process very secure, since your data doesn't leave your servers. Reliable Data Features: Whylabs delivers all standard feature metrics accurately. Tracking data and model drift is very straightforward using Monitors. Also, the platform supports custom metrics creation during or after ingestion. Grouping by variables (segments) works well but must be defined during ingestion. Then you can analyze dataset features and track model performance per segment. Flexible Monitors: The monitoring system in Whylabs is highly adaptable and user-friendly, covering multiple variables with ease. Monitors are easy to set up via the UI or JSON import, with summarized notifications for each monitor, keeping users informed without overwhelming them. Additionally, monitors are JSON serializable, which is very helpful since you can track them with version control. User-Friendly Usability: Whylabs have a clean and intuitive UI, simplifying navigation for users. While some advanced features may require programming knowledge, most tasks can be accomplished within the UI. Thanks to data profiling, Whylabs delivers speedy performance without compromising on accuracy. Solid Documentation: The documentation provided by Whylabs is comprehensive and easy to understand, enabling users to make the most of the platform. Pricing: It's simply cheaper than its competition while having top notch features. Customer Support: They are always very helpful, answering all our questions and having several calls showcasing us different uses cases directly on the platform. Overall, Whylabs offers a straightforward, efficient and affordable solution for monitoring Machine Learning models, with easy data ingestion, reliable feature analysis, and flexible monitoring options.