DevOps Conference
The Conference for Continuous Delivery, Microservices,
Containers, Clouds and Lean Business

Creating a Distributed AI/ML Enterprise Fabric Using Kubernetes and Serverless

Session
Until Conference starts:
✓ Group Discount
✓ Freelancer Special
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Bis 31. Oktober
✓ Kollegenrabatt
✓ Bis zu 375 € sparen
Jetzt anmelden
Until December 12:
✓ Workshop Day for free
✓ Raspberry Pi or C64 Mini for free
✓ Save up to $690
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Until December 12:
✓ Workshop Day for free
✓ Raspberry Pi or C64 Mini for free
✓ Save up to $690
Register now
Until January 30:
✓ Team Discounts
✓ Raspberry Pi or C64 Mini for free
✓ Save over £329
Register Now

Until January 30:
✓ Team Discounts
✓ Raspberry Pi or C64 Mini for free
✓ Save over £329
Register Now

Until March 5:
✓ Transformation Day for free
✓ Raspberry Pi or C64 Mini for free
✓ Save over 850 €
Register now
Bis 5. März:
✓ Transformation Day for free
✓ Raspberry Pi oder C64 Mini for free
✓ Über 850 € sparen
Jetzt anmelden
Until June 18:
✓ Workshop Day for free
✓ Raspberry Pi or C64 Mini for free
✓ Save over $840
Register now
Until June 18:
✓ Workshop Day for free
✓ Raspberry Pi or C64 Mini for free
✓ Save over $840
Register now
Infos
Wednesday, June 12 2019
18:15 - 19:15
Room:
MOA 9+10

Artificial intelligence (AI) and Machine Learning (ML) offer incredible opportunities for enterprises to introduce new business models, optimize their offerings and interactions with their end users, improve customer experience, and increase efficiency of their business processes and operations.

Kubernetes combined with Serverless/Function-as-a-Service (FaaS) offer the perfect stack for creating a production-ready ML framework that can power a myriad of applications and use cases within the organization — supporting granular scalability, ease of use, and portability across mixed environments spanning cloud resources as well as on-prem datacenters.

Through a live demo of a sample use case, this talk covers the suggested architecture and design patterns for enabling a distributed, scalable, ML framework that can be consumed (in a self-service/API) by various stakeholders/apps – enabling them to easily leverage ML models and data in a reliable way.

We share best practices around the various components of the stack- comprising of a managed Kubernetes solution, open source Serverless framework, data streams integrations, stateful data store recommendations, as well as key consideration for Day2 operations and maintain-ability.

Stay tuned:

Behind the Tracks

 

Kubernetes Ecosystem

Docker, Kubernetes & Co

Microservices & Software Architecture

Maximize development productivity

Continuous Delivery & Automation

Build, test and deploy agile

Cloud Platforms & Serverless

Cloud-based & native apps

Monitoring, Traceability & Diagnostics

Handle the complexity of microservices applications

Security

DevSecOps for safer applications

Business & Company Culture

Radically optimize IT

Organizational Change

Overcome obstacles on the way towards DevOps

Live Demo #slideless

Showing how technology really works