MLOps with Databricks on AWS

MLOps with Databricks on AWS is an offering from Mantel Group to help your organisation overcome the common challenges of operationalising machine learning. With Mantel Group’s extensive experience with MLOps, Databricks and AWS native data services, we guide you through the complexities to ensure that your ML projects are not just experiments but integral parts of your business processes.

• The Challenge of MLOps: Many organisations struggle to transition ML projects into production due to the intricate nature of managing code, data, and models. Mantel Group addresses these pain points by providing a streamlined process that integrates DevOps, DataOps, and ModelOps practices.
• Data-Centric Workflow: At the core of Mantel Group’s offering is a data-centric workflow that unifies the best practices from DevOps, DataOps, and ModelOps. This approach facilitates collaboration among data teams and simplifies the management of ML pipelines, from data ingestion through to model deployment.
• Feature Store Integration: Mantel Group’s solution includes integration with the Databricks Feature Store, allowing for the joint productionisation of models and features. This enables data scientists to create models that are “aware” of the necessary features, simplifying the deployment process for ML engineers.
• Adherence to Open Standards: Mantel Group prioritises open standards, integrating with tools like Git for DevOps, Delta Lake for DataOps, and MLflow for ModelOps. This commitment to openness ensures that the platform can adapt to your organisation’s unique requirements and evolve with industry-wide standards.
• Simplified Operational Processes: Mantel Group’s approach extends DevOps principles to ML, defining clear semantics for “moving to production” and allowing existing tooling and CI/CD processes to manage ML pipeline code alongside data pipelines.