Conference: Jun 26-28, 2017
Workshops: Jun 29-30, 2017
Presentation: Fearless AWS Lambdas
What You’ll Learn
- Gain practical knowledge about experiences running JVM-based Applications on AWS Lambda.
- Learn about some of the performance numbers and metrics captured from running on a serverless platform.
- Understand best practices and hear recommendations on how to effectively leverage cloud serverless function.
Abstract
The modern Java Virtual Machine (JVM) is the culmination of millions of hours of expert engineering, and is the foundation on which enormous portions of the digital landscape are built. However, as a runtime for AWS Lambda functions, the JVM is often derided as being a poor fit for an ephemeral world. The truth of the matter is that the JVM is an excellent choice of runtime for a wide range of AWS Lambda use cases, and developers need not even constrain themselves to just the Java language to use it.
In this talk, John Chapin gives an overview of the JVM runtime for AWS Lambda, as well as a comprehensive look at JVM-based Lambda performance across a range of use cases. He outlines a set of criteria to help architects and engineers decide whether or not to choose the JVM over the other runtime options. He also gives strategies, tips, and examples for developing efficient, performant AWS Lambda functions in a variety of JVM languages, including Java, Clojure, and Scala.
Interview
John: You have to be very cognizant of the cold-start initialization behavior of your application (and the underlying runtime) versus the warm-start behavior of your application (and that runtime).
Both the beauty (and the challenge) of a platform like Lambda is you give up control. As we moved along this path, where we went from running on premise (where we did everything from bare metal on up) to a managed functions as a service platform, we're losing dials and losing opportunities to control the behavior of the runtime. So with Lambda, we only have a couple of knobs left to turn to adjust the behavior of the runtime. The thing that affects Java the most is of course artifact size.
As Java developers, we are used to just plugging the library that we need into a pom file, and it downloads. So I go into some detail about how to be circumspect and conscious of your application dependencies.
John: The good news is that the platform itself only undergoes cold starts when it needs to create a new container. For example, like the first time you run your Lambda, reconfigure your lambda, or maybe when you scale out, you will see it. What we see (and we have a lot of data on this) is that it tends to be four to six hours before you have to have a cold start.
[If you're running a fairly regularly invoked lambda function (and not having a ton of failing behavior), you may only actually pay that cold start penalty a few times a day. If you're doing something in the execution of your Lambda function that's even marginally complex, this is usually enough to see the performance of the JVM drastically exceed that of a Node or Python. By the way, I'll caveat that statement by saying Python not using some of it's C/native library stuff. So so do the math. We'll talk about how to do that and how to go into some detail about how the benchmark standards because the platform is very very hard.
John: You have you have no control over any of the runtime parameters of the JVM, other than you can set the memory allocated for a Lambda and the max heap for the JVM is 85 percent of that.
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