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Comment by niahmiah | Hacker News Reader

Try running a few docker containers to support development work. A few DBs, messaging servers, Lucene indices, etc. Try prototyping applications using map-reduce for huge datasets.

"Pro" doesn't always refer to the artistic line of professionals. Many developers see this as a huge problem, and there are a lot of us.

Our options now include the 2005-era looking systems at system76.com, running Linux. I love Linux for servers, but I really don't like the GUIs, or acting as my own systems integrator. I want a true modern "Pro" macOS system, and that doesn't exist right now.

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> Our options now include the 2005-era looking systems at system76.com, running Linux.

Or in fairness a Dell XPS15 which aside from supporting 32GB of RAM (and is orderable with that) has the quad-core i7HQ vs the Macbook Pro's and it's about 500 quid cheaper in the UK.

>Try prototyping applications using map-reduce for huge datasets.

Yep, a Spark job I was running recently used up my Mac's 16GB rather quickly.

> Try running a few docker containers to support development work.

Docker containers should not take more memory than the same app running without docker + a few megs for duplicated libraries. What matters is what's running in the containers.

Doesn't Docker on Mac run the containers inside a Virtualbox VM running Linux? That should take quite a bit more memory than just running the app directly.

I'm comparing running on linux+docker vs running on linux. Virtualisation is present in both. If you've got the possibility to run the same app directly on OSX and you're not preparing for deployment on another system... why wouldn't you do that instead?

Docker for Mac uses the built-in Hypervisor.framework through xhyve. Still virtualizating Linux, though, so there's some overhead.

It used to, but the newer Docker for Mac uses xhyve which is more lightweight. It also by default runs a pretty stripped down version of Linux. The default VM size is 2Gb, but you can increase that if you need to.

I'm currently working on a project which involves a Docker replication of a production environment. The Docker Compose environment has 7 docker containers including Cassandra, Kafka and Flink plus some nodejs micro-services. This all runs happily in a 6Gb docker container leaving memory free for Eclipse, Atom, Outlook and a bunch of other applications on a 16Gb 2015 MacBook Pro. At no point have I felt that the machine is performing poorly due to memory exhaustion.

> Try running a few docker containers to support development work

If I don't do that, then am I not a professional?

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