Serving ML at scale with KServe / Animesh Singh @ IBM CTO

**** REGISTRATION IS A MUST VIA THE LINK ****
https://www.eventbrite.com/e/serving-ml-at-scale-with-kserve-animesh-singh-ibm-cto-tickets-187680616777

• The meetup will be online (via Zoom)

# Agenda:

19:00 - 19:10 - What is MLOps? What is this group?

19:00 - 20:00 - Special Guest: Serving ML at scale using KServe

## Serving ML at scale using KServe
Join us for an insightful meeting about one of the leading open sources projects in the MLOps industry - KServe.

KServe (previously known as KFServing) is a serverless open source solution to serve machine learning models. With machine learning becoming more widely adopted in organizations, the trend is to deploy larger numbers of models. Plus, there is an increasing need to serve models using GPUs. As GPUs are expensive, engineers are seeking ways to serve multiple models with one GPU.

The KServe community designed a Multi-Model Serving solution to scale the number of models that can be served in a Kubernetes cluster. By sharing the serving container that is enabled to host multiple models, Multi-Model Serving addresses three limitations that the current ‘one model, one service’ paradigm encounters: 1) Compute resources (including the cost for public cloud), 2) Maximum number of pods, 3) Maximum number of IP addresses. 4) Maximum number of services This talk will present the design of Multi-Model Serving, describe how to use it to serve models for different frameworks, and share benchmark stats that demonstrate its scalability.

### Animesh Sigh / Bio
IBM CTO for Watson AI/ML Open Technology. Watson Distinguished Engineer and Executive, responsible for Watson AI/ML Platform Open Technology strategy, architecture and execution, delivering joint IBM Watson and Red Hat technical roadmap and products, working with Watson customers and partners, leading IBM leadership and engagement in Linux Foundation Data and AI, Trusted AI (AI Fairness, Robustness, and Explainability) and MLOps (Kubeflow, ML Pipelines, ML Serving) communities. Has led globally dispersed teams, managed globally distributed projects, and served as a trusted adviser to Fortune 500 firms. Drove the strategy and execution for Kubeflow, OpenDataHub, and in products like IBM Cloud Private for Data, Watson OpenScale, and Watson Machines Learning. In the past, led IBM Developer launch, first IBM public cloud offering launch, launched initiatives around Kubernetes and Istio, Bluemix (Cloud Foundry) launch, and worked with associated customers in the telco, banking, and healthcare industries.