Enterprises who are actively increasing their AI maturity in a bid to achieve business transformations often find that with increased maturity comes increased complexity. For use cases that require very large datasets, the tech stacks required to meet business needs quickly become unwieldy.

In 2022, AI and ML came into the mainstream consciousness, with generative AI applications like Dall-E and GPT AI becoming massively popular among the general public, and ethical questions of AI usage stirring up impassioned public debate. No longer a side project for forward-thinking businesses or CEOs that find it intriguing, AI and ML are now moving towards the center of the business.

The IDC MarketScape: Worldwide Machine Learning Operations Platforms 2022 Vendor Assessment is an annual study that evaluates technology vendors based on a comprehensive framework. It provides an in-depth quantitative and qualitative assessment of MLOps solution vendors in a long-form research report, to help buyers make important technology decisions that will create long term business success.

The GigaOm Radar reports support leaders looking to evaluate technologies with an eye towards the future. In this year's Radar for MLOps report, GigaOm gave Iguazio top scores on multiple evaluation metrics, including Advanced Monitoring, Autoscaling & Retraining, CI/CD, and Deployment. Iguazio was therefore named a leader and also classified as an Outperformer for its rapid pace of innovation.

Hugging Face is a popular model repository that provides simplified tools for building, training and deploying ML models. The growing adoption of Hugging Face usage among data professionals, alongside the increasing global need to become more efficient and sustainable when developing and deploying ML models, make Hugging Face an important technology and platform to learn and master.

With the Apache Spark 3.1 release in early 2021, the Spark on Kubernetes project has been production-ready for a few years. Spark on Kubernetes has become the new standard for deploying Spark. In the Iguazio MLOps platform, we built the Spark Operator into the platform to make the deployment of Spark Operator much simpler.