Solutions for Cloud-Native and Microservices to Streamline Your MLOps Practices webinar

When:  Feb 24, 2021 from 10:00 AM to 10:30 AM (ET)
Webinar Summary

If machine learning (ML)-based analytics is part of your organization’s current or future IT strategy, then you need to focus on how to optimize your machine learning operations (“MLOps”). Certainly MLOps is largely about deploying good processes and leveraging deep expertise, but technology can also play a significant role in making ML efforts more effective by enabling machine learning to fully leverage modern architectures such as microservices and cloud-native.


ML is increasingly becoming important for today’s business objectives, so it’s important to learn from past experience. MLOps is the missing piece that enables your applications to become truly AI-First. Hazelcast and IBM work together to help joint customers deploy successful ML implementations, using popular patterns like microservices and event-driven architectures, in cloud-native environments.


In this webinar, we will cover:
The challenges of deploying ML models into production that can and should be overcome.
How Microservices and Cloud-Native create new challenges and new opportunities for ML Ops. 
Recommendations on how to enhance your MLOps practices.
Key technologies that can help you get more value from ML and allow faster deployments, greater scalability, and greater resilience while creating smarter, more AI-driven applications.

John DesJardins
John DesJardins
CTO
Hazelcast

John DesJardins is currently Field CTO and VP Solution Architecture for North America at Hazelcast, where he is championing the growth of our Developer and Customer Community. His expertise in large scale computing spans Data Grids, Microservices, Cloud, Big Data, Internet of Things, and Machine Learning. He is an active blogger and speaker. John brings over 20 years of experience in architecting and implementing global scale computing solutions, including working with top Global 2000 companies while at Hazelcast, Cloudera, Software AG and webMethods. He holds a BS in Economics from George Mason University, where he first built predictive models, long before that was considered cool.

Matt Rodkey
Matt Rodkey
Program Director Offering Management, IBM Hybrid Cloud Management and Watson AIOps
IBM

Matt is a Program Director of Offering Manager for IBM Cloud. In his 20 years at IBM Matt has worked in Development, Advanced Technology Group, and Offering Management. These roles have covered many parts of the IBM's Management Portfolio including Security, Application Performance Management, Cloud Management, Operations Analytics. Currently, Matt is focused on multicloud management capabilities.