DataRobot has recently acquired Agnostic, a company known for its open-source distributed computing platform called Covalent. This platform will be integrated into DataRobot’s machine learning operations, creating a powerful orchestration tool for IT teams. Covalent, built on Python, allows organizations to efficiently manage their IT infrastructure using serverless computing. It supports deploying applications across hybrid environments by simplifying the management of Kubernetes and other systems. As companies increasingly deploy AI applications, Covalent will help control resource allocation without locking them into specific platforms. With over 5,000 users and wide adoption, Covalent aims to streamline how IT teams oversee the lifecycle of AI inference engines in collaboration with data science teams.
DataRobot Expands Capabilities with Agnostic Acquisition
DataRobot, a leading platform for creating artificial intelligence (AI) applications, has taken a significant step forward by acquiring Agnostic, which provides the Covalent platform for distributed computing. This new integration aims to enhance DataRobot’s machine learning operations (MLOps) framework.
Covalent is a unique orchestration platform based on Python. It offers IT teams a serverless computing environment, allowing them to make better use of their IT resources. Venky Veeraraghavan, DataRobot’s chief product officer, explained that Covalent will facilitate application deployment and orchestration on a large scale within hybrid IT settings. The platform utilizes Git-based workflows, simplifying cluster management for technologies like Kubernetes, Slurm, and Nomad.
One of Covalent’s key features is its ability to configure rules based on cost and latency. This allows IT teams to prioritize specific processes, an increasingly important capability as organizations deploy AI applications across various processors.
The Covalent platform has over 5,000 users and has been downloaded more than 140,000 times, mostly by data science teams. However, the growing focus on AI is shifting the responsibility for managing inference engines to IT departments. This trend highlights a crucial need for integrating AI deployment with existing DevOps workflows.
With the rising demand for AI applications, many will need to be deployed in on-premises environments due to latency needs. As organizations navigate the integration of MLOps and DevOps, they will face technical and cultural challenges.
This acquisition not only strengthens DataRobot’s offerings but also pushes the boundaries of how AI can be integrated into business operations. Organizations must now consider how to effectively blend their MLOps with infrastructure management, ensuring smooth deployment and operation of AI models.
Tags: DataRobot, Agnostic, AI Applications, Covalent, MLOps, IT Management
What is the main reason DataRobot acquired Agnostic?
DataRobot acquired Agnostic to enhance its capabilities in developing AI applications, using Agnostic’s Covalent platform.
What is the Covalent platform?
The Covalent platform is a distributed system that helps build and manage AI applications more efficiently and effectively.
How will this acquisition benefit DataRobot users?
Users will gain access to advanced tools and features for building AI solutions faster and with improved performance.
Are there any changes expected for Agnostic’s current customers?
Current customers of Agnostic can expect to see improvements in service and new features as DataRobot integrates the platform into its offerings.
What is DataRobot’s main focus with this acquisition?
DataRobot aims to streamline the development of AI applications and make it easier for businesses to implement AI solutions tailored to their needs.
