Ask HN: How will using containers save me money?
In the ancient world they would be running on a large colocated server under different users, perhaps using something like chroot, etc. The resources would be very well utilized but it would be a security and operations nightmare.
In the IAAS world I can rent instances of various sizes, one per my small application. This would improve on security and operations, but the resources are horribly allocated. I need every server to be sized so it can carry it's app at peak traffic, but otherwise they are all idling most of the time.
In the container (CAAS?) world security and operations are basically solved, but I am still not convinced about resource utilization.
Both AWS and GCE promise to deploy containers on top of their "compute platform" and charge me for used instances + some more for the management of the container platform.
So it seems by using containers to deploy my application I am still paying for the same underutilized resources, while giving the platform provider the possibility to optimize things behind my back. Basically I am saving THEM money.
I know could just pay for one big box and run all my applications on it, running docker and deploying containers by hand, but then I would be back managing things myself.
So how can I use containers to better utilize resources and save ME money?
4 comments
[ 4.6 ms ] story [ 20.5 ms ] threadThis is where I think containers would save me the most time and money.
Once you determine your application needs, you can set your cpu/memory resource needs per container/service. Then you can run these containers inside your fleet more smartly.
This really comes into play for memory and cpu ratio. Look at the price difference between:
one m4.2xlarge = 32gb mem, 8 cores = $350 a month
eight t2 medium = 32gb memory, 8 cores = $300 a month
You get twice as much compute for less money with the ability to mix and match service needs instead of being constrained to individual instances.
You set the cpu limit per container based on cpu units. There are 1024 available per core.