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

Serverless Deep Learning

Session

Until February 11:
✓ Transformation Day for free
✓ Team discounts
✓ Save up to £330

Register Now

Until February 11:
✓ Transformation Day for free
✓ Team discounts
✓ Save up to £330

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
Until Conference starts:
✓ Group Discount
✓ Freelancer Special
Register now
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
Register now
Until December 12:
✓ Workshop Day for free
✓ Raspberry Pi or C64 Mini for free
✓ Save up to $690
Register now
Infos

Deep learning achieves the best performance for many computer vision, natural language processing, and recommendation tasks and thus it’s becoming increasingly more popular. However, it’s quite difficult to use deep learning in production as it requires a lot of effort to develop proper infrastructure for serving deep learning models.Platforms for serverless computing, such as AWS Lambda, provide a good alternative: they take care of scaling up and down and offer attractive pricing based only on actual usage. These platforms, unfortunately, have other limitations that make it problematic. In this talk, we show how to come around these limitations and be able to use AWS lambda and TensorFlow to serve deep learning models. We also discuss important maintenance aspects such as cost optimization, monitoring, deploying, and release management. Finally, we cover the limitations of AWS lambda, compare it with “serverful” solutions, and suggest workloads for which serverless is not the best option.

This Session Diese Session Take me to the current program of . Hier geht es zum aktuellen Programm von London London , Berlin Berlin , New York New York , Munich München or oder Singapore Singapur .

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Behind the Tracks

 

Kubernetes Ecosystem

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Microservices & Software Architecture

Maximize development productivity

Continuous Delivery & Automation

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Cloud Platforms & Serverless

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Monitoring, Traceability & Diagnostics

Handle the complexity of microservices applications

Security

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Business & Company Culture

Radically optimize IT

Organizational Change

Overcome obstacles on the way towards DevOps

Live Demo #slideless

Showing how technology really works