MLOps Platforms
MLOps (Machine Learning Operations) platforms are software products and services that help companies to create and manage software development, deployment, and management of machine learning processes and pipelines in an automated manner. MLOps platforms enable organizations to automate their DevOps processes for machine learning applications. MLOps is relatively new and is enabled by the availability of modern computing resources and software development tools.
MLOps platforms automate the process of versioning and deployment for ML models. Versioning enables teams to compare different versions of the models with each other and helps data scientists work collaboratively on an ML project. It also secures models and helps with compliance by enabling the traceability of the models. MLOps platforms handle the deployment process, orchestrating the different components of the product and making sure the model is deployed properly.
The MLOps process typically consists of five steps, which are: Continuous Integration (CI), Continuous Delivery (CD), Continuous Training (CT), Model Quality Assurance (MQA), and Model Stability Assurance (MSA). Continuous Integration builds and tests the model in an automated process. Continuous Delivery focuses on deployment of the model. Continuous Training is the process of making sure the model remains up to date by applying newly available data. Model Quality Assurance focuses on measuring and improving the quality of the model. Model Stability Assurance focuses on improving the stability of the model.
MLOps platforms can deploy models to Kubernetes-based clusters, cloud systems, and on-premises hardware. Additionally, MLOps platforms typically have tools for improving the model’s performance, such as automated hyperparameter tuning, and for measuring the ML model’s quality and stability.
MLOps platforms enable organizations to develop and deploy ML pipelines with high fidelity, in an efficient and automated manner. By automating and streamlining the ML development process, MLOps platforms make it easier to secure, manage, and optimize machine learning pipelines.
