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Thawing Java on AWS Lambda: Reducing cold start times from 6 seconds to .1

Daniel Raniz Raneland

from factor10 (Varberg, Sweden)

About speaker

Sourceror @ factor10

Raniz is a programmer, architect, speaker and coach at factor10. He is a problem solver who keeps track of the bigger picture. He is prestigeless, likes to get into new domains, and loves sharing knowledge and ideas.

About speakers company

We are consultants. Software consultants, actually. Business-oriented coding architects, when we describe ourselves. Our ambition is to contribute to making the world a radically better place, and we are doing it through the power of outstanding software. We know that we are succeeding when: - Customers choose us because they want to make more out of their business. - People in our business believe they can make more of an impact by working with us. - People develop their capability to make outstanding software by interacting with us.

Abstracts

specific

Java has never been a perfect fit for Function as a Service platforms such as AWS Lambda or Azure Functions. While both platforms have official support for Java, Java functions unfortunately suffer from significantly longer cold start times than many other runtimes.

In this talk I will show a simple Spring Cloud Java function running on AWS Lambda with fairly horrible cold start times of around 6 seconds and then compare a few different approaches for significantly improving it. Eventually ending up with a cold start time of just 600 milliseconds - making Java a viable, though not without drawbacks, choice for FaaS platforms.


Running Java on Function as a Service platforms like AWS Lambda can be hit or miss. The startup times can be glacially slow - and that may or may not be an issue.

In this talk, I'll explain why Java takes so long to start up and what we can do about it. Eventually reaching performance comparable to a language renowned for its speed: Rust.

The Program Committee has not yet taken a decision on this talk

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