Redefining MLOps with Model Deployment, Management and Observability in Production
- 2. Younes Amar Younes is the head of product at Wallaroo. Prior to joining Wallaroo, Younes was the data science and AI product lead at Tempus Labs, working with a large team of data scientists, on the mission of leveraging large scale multimodal clinical and genomic data to develop AI-enabled products that help accelerate scientific discovery and improve patients’ outcomes. Younes has extensive experience in software engineering and product development with focus on delivering high impact analytics and ML platforms in various industries such as ESG, Government, logistics, healthcare and insurance. Head of Product, Wallaroo
- 3. Proprietary and Confidential, Wallaroo Labs, Inc. (2022) What is MLOps? A cross-functional collaboration with one mission: Operationalize Machine Learning Data Scientist Data Engineer ML Engineer ML Infrastructure Data Infrastructure ML tooling ML/AI research labs
- 4. Proprietary and Confidential, Wallaroo Labs, Inc. (2022) How is MLOps applied today? Data load & prep Model Training Model deployment - Model Monitoring Model Development Model Productionization
- 5. Proprietary and Confidential, Wallaroo Labs, Inc. (2022) Last mile of ML Objectives • Close the gap between insight creation and value realization • Transition from Experimental AI to Industrialized AI Challenges • Scale: Deploying and Serving thousands of models • Operational efficiency: Managing and Measuring models at scale • Repeatability: Consistent process and technology • Actionability: Timely preventative and corrective actions
- 6. How does Wallaroo think about the last Mile of ML?
- 7. Proprietary and Confidential, Wallaroo Labs, Inc. (2022) Wallaroo is breakthrough performance for the last mile of ML Seamless integration into any data and ML ecosystem
- 8. Proprietary and Confidential, Wallaroo Labs, Inc. (2022) 1 purpose-built platform. 3 integrated components. Self-Service Toolkit Blazingly Fast Compute Engine Stream of full audit logs + advanced model monitoring and explainability insights to help drive results Written in Rust-Lang for breakthrough scalability and performance Easy-to-use SDK, UI, and API designed for expert data scientists and ML Engineers Advanced Observability
- 9. Proprietary and Confidential, Wallaroo Labs, Inc. (2022) The last mile of ML in Wallaroo Model Deployment Model Management Model Observability Model Optimization Goals Empower data scientists and Machine Learning engineers to: ✓ Collaborate effectively to launch faster ✓ Scale deployment, management and observability of ML in production ✓ Deliver Actionable ML
- 10. Proprietary and Confidential, Wallaroo Labs, Inc. (2022) Model Deployment Key capabilities • Model Upload with open format conversion across all ML frameworks • Self-service ML deployment Pipelines Configuration • Single and batch inferencing • Compute utilization auto-scaling for optimal performance and user experience
- 11. Proprietary and Confidential, Wallaroo Labs, Inc. (2022) Model Management Key capabilities • Workspace management & Collaboration • Integrated Jupyter environments for experimentation and validation • Configurable model rollout strategies (Canary deploys, Shadow deploys, A/B testing, blue/green deployment) • Model (Hot) Swapping • Model Versioning
- 12. Proprietary and Confidential, Wallaroo Labs, Inc. (2022) Model Observability Key capabilities • Performance and health metrics: Latency and throughput • Model + Data Anomaly and Drift detection with configurable validation checks and alerts (Wallaroo assays ™) • Model explainability and troubleshooting reports • Native and integrated 3rd party reporting tools
- 13. Proprietary and Confidential, Wallaroo Labs, Inc. (2022) Model Optimization Key capabilities • Actionable insights • Proactive model tuning • Automated retraining and redeployment
- 14. Demo
- 15. Q&A
- 16. Proprietary and Confidential, Wallaroo Labs, Inc. (2022) Need more information? https:/ /docs.wallaroo.ai www.wallaroo.ai/blog [email protected] www.wallaroo.ai