MLOps Platform Architecture for End-to-End ML Pipelines

Explore the MLOps maturity journey at Avast in this 42-minute conference talk by Joao Da Silva, Lead Data Engineer. Gain insights into the architecture, tooling, and cultural shifts that have enhanced velocity, collaboration, and structure for productizing machine learning. Learn about Avast's approach to integrating model tracking, storage, cross-system orchestration, and end-to-end model deployments for comprehensive, modern machine learning pipelines. Discover how Avast handles challenges faced by data scientists, including inconsistent environments, transitioning from research to production, access management, and model deployment. Understand how these strategies support Avast's mission to provide crucial online protection, including over 17 million daily phishing detections. Apply the lessons learned from this real-world MLOps adoption journey to your own organization, regardless of its size or industry.

MLOps Platform Architecture for e2e ML Pipelines