# Evaluating your ML project with the MLOps checklist
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*Charles Frenzel, Sharath Nagaraja, and Spencer Romo, Amazon Web Services*

The MLOps checklist is a workable checklist that you can use at any phase in your machine learning (ML) project. The checklist is a tool for assessing overall readiness, examining system coverage, and identifying new areas of opportunity in distributed ML systems. MLOps is the combination of people, technology, and processes** **for delivering ML solutions. Well-architected MLOps helps businesses to deploy ML models to production effectively and consistently, and can deliver business value.

Using the MLOps checklist helps you to do the following:
+ Assess your MLOps system.
+ Find areas of opportunity.
+ Find areas for improvement.
+ Evaluate and update your strategic roadmap on AWS.
+ Generate backlog items.

We recommend using the MLOps checklist at the start of your MLOps project, but it's possible to use parts of it during any phase.

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