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DataRobot MLOps Agents: Visibility for All Your Production Models

December 28, 2020
· 2 min read

The extraordinary benefits of AI in today’s business climate are abundantly clear. But as more machine learning solutions are implemented in organizations, the need for a centralized MLOps platform becomes even more significant. However, scaling such a solution across all lines of business has its challenges, with the production gap and cost of additional resources being two of the most influential ones.

The production gap means building a model but lacking the ability to deploy and manage it successfully in production. There are a lot of factors that can contribute to this gap. For example, even within one company, different lines of business often use different technology platforms and programming languages to solve their own unique issues, making it hard for IT to manage production models in a centralized way.  

Cost of additional resources is the other major challenge. Many off-the-shelf tools designed to support production machine learning are simply cost prohibitive. They either require additional expenditure on unwanted infrastructure, or they drive up time and resources cost to manually code around gaps in their functionality. 

DataRobot MLOps Agents Are the Solution.

MLOps Agents are designed to support any model, written in any language, deployed in any environment. This means that with minimal time or performance overhead, you can centrally monitor models created in any location and deployed on any infrastructure. This provides organizations with the flexibility required to meet model monitoring business needs by quickly providing health metrics for any deployed model. 

There are three distinct layers to DataRobot’s remote model monitoring architecture: The MLOps Library, the Channel, and the Agent.

The MLOps Library tracks service, drift, and accuracy metrics. It provides near real-time, scalable monitoring to a highly scalable channel, such as Amazon SQS. It can also be used to report metrics outside of the prediction path to avoid any unwanted impacts. 

Using a Channel, versus doing it directly, is the preferred way to pass metrics. DataRobot’s Agents provide multiple channels to provide more configuration options, including support for disconnected models that do not have network connectivity to the MLOps application.  

The Agent is the third and final layer within the model architecture. It monitors and collects metrics from the channel and passes them back to the MLOps application to drive analytics on model service health, accuracy and data drift. 

MLOps Agents provide centralized monitoring for all your production models, and they are undoubtedly the best solution for overcoming most significant production AI challenges. 

To learn how to vastly improve your machine learning pipeline with our Agents, read our ebook, DataRobot MLOps Agents. 

This ebook takes a deeper dive into the topics mentioned above and shows how to integrate MLOps Agents with your models. We’ll also show you how to configure and start the software. 

DataRobot MLOps Agents: Visibility for All Your Production Models
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About the author

Value-Driven AI

DataRobot is the leader in Value-Driven AI – a unique and collaborative approach to AI that combines our open AI platform, deep AI expertise and broad use-case implementation to improve how customers run, grow and optimize their business. The DataRobot AI Platform is the only complete AI lifecycle platform that interoperates with your existing investments in data, applications and business processes, and can be deployed on-prem or in any cloud environment. DataRobot and our partners have a decade of world-class AI expertise collaborating with AI teams (data scientists, business and IT), removing common blockers and developing best practices to successfully navigate projects that result in faster time to value, increased revenue and reduced costs. DataRobot customers include 40% of the Fortune 50, 8 of top 10 US banks, 7 of the top 10 pharmaceutical companies, 7 of the top 10 telcos, 5 of top 10 global manufacturers.

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