[pharaohgeek]

Compiling Java to native code via GraalVM is really amazing. The Quarkus framework supports this, and the startup time and memory utilization is incredible compared to the JVM. I deploy native-built Java apps as AWS Lambdas and the startup time and resource utilization are so much better by comparison.

[willsmith72]

what are the cold starts like?

[metadat]

Faster, because it's a native executable.

[willsmith72]

Right, but I mean there's faster than spring boot (30 seconds), then there's fast enough for a typical web experience (<500ms)

My experience on lambda is with node and python, and I've always needed to pay for concurrency. Cold starts were 1-3s, which is not good enough for a web api

[shitlord]

Depending on how your program is written, you might be able to use Lambda SnapStart and eliminate most of the cold start overhead.

[mike_hearn]

A GraalVM native executable can start faster than a C program. Think tens of milliseconds.

[willsmith72]

i know what graalvm is, but that doesn't mean the cold start response time of a lambda from the perspective of a user will be anything like that.

[mike_hearn]

It does. This is one of those times where nothing is hidden from you. You don't have to believe me. Believe AWS:

https://aws.amazon.com/blogs/opensource/improving-developer-...

> The same Lambda function with 3008 MB of memory that took 3.6 seconds to start with the JVM, started in under 100 milliseconds once compiled to a native executable using GraalVMs native-image tool. We were able to achieve sub second response times as shown in the graph below, and as an added bonus were also able to reduce the memory size and cost.

They go on to describe the main caveat - you have to predeclare what will be accessed via reflection - and how some frameworks like Micronaut do work up-front at source compile time to ensure the needed metadata is generated. So if your app is compatible with native image the benefits are really there.

There are some other caveats:

• In some cases you may need config files to make libraries compatible with the process. There's a central collection of them, and libraries are increasingly including their own metadata. The biggest app compat problems are with apps built using old versions of frameworks like Spring where you can't afford to update them to the newest versions of things.

• Out of the box the native executable runs a bit slower. To get throughput that's competitive with HotSpot you'll need to do a C++ style workflow with profile guided optimization, which is obviously more runtime efficient but less devops-time efficient than what HotSpot does.

• The actual compile process is slow, so you'll be developing on HotSpot.

Disclosure: I work part time with the GraalVM team.

[degaart]

Source and benchmarks please

[mike_hearn]

There are lots. Everyone gets those sorts of results so you can just try it, or here are some experience reports:

https://debijenkorf.tech/speed-up-application-launch-time-wi...

> The app went from starting in 463ms to a whopping 7ms, awesome!

> As you can see the memory usage went from 215.924kB to 18.104kB

Or for Lambdas (this result is reported by the GraalVM team):

> The same Lambda function with 3008 MB of memory that took 3.6 seconds to start with the JVM, started in under 100 milliseconds once compiled using GraalVM

https://aws.amazon.com/blogs/opensource/improving-developer-...

Native Image is a fully independent JVM and compiler implementation that was written from day one for startup time and memory footprint as the only goals that mattered. What it sacrifices to get that is some semantic compatibility. The big differences are:

- It compiles all code ahead of time. As machine code is much bigger than the equivalent bytecode, it uses a dead code ("tree shaking") analysis to only compile code that's statically reachable or declared via config files. It's like a mandatory WebPack or ProGuard step if you're familiar with those.

- It runs (some) class initializers at compile time, not startup time. So if you do something like "public static final Thread thread = ...." then you'll need to exclude that class from build-time init, including if it's in libraries etc.

- It snapshots the post-compile heap into the binary.

So this is changing the normal Java semantics and that means some apps won't run on native image without some up front work. It's not an entirely free capability. You have to "port" your app to it. Fortunately, because the startup and memory footprint wins are so huge and definitive the JVM ecosystem is rallying around this approach and making frameworks and such compatible with it. For instance if you use the latest versions of any of the modern Java web frameworks (Spring, Micronaut, Quarks, etc) then you can easily run a single build system target to get a Docker container with a native executable inside, that has those startup times you're seeing here.

At this point the startup time bottleneck for (compatible) Java apps has shifted to the kernel; the container infrastructure itself takes longer to start than the Java program does.