AWS Platform Guide
Container Size
Unlike some other platforms, containers are not constrained to a predetermined size. When you deploy your application, you decide how much RAM and CPU to allocate to each container. This is done using resource requests in your pod manifests. Here is an example container which requests 512MiB of RAM and expects to use half a CPU core:
spec:
containers:
- name: main
image: example:latest
resources:
requests:
memory: 512Mi
cpu: "500m"
We strongly recommend adding resource requests to all your containers. This will tell the cluster how much space it should expect to allocate to run your container.
Vertical Autoscaling
Many applications experience fluctuation in memory or CPU requirements as the application scales. Rather than manually tracking the resources your containers require and updating your resource requests as the application grows, you can tell the cluster to automatically adjust the requirements using the vertical pod autoscaler, which is deployed as part of the Flightdeck platform. Here is an example which will automatically adjust the size of the pods for a deployment, but will never scale it beyond 2 CPU cores or 4GiB of memory:
apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
name: example
spec:
targetRef:
apiVersion: apps/v1
kind: Deployment
name: example
updatePolicy:
updateMode: Auto
resourcePolicy:
containerPolicies:
- containerName: "main"
maxAllowed:
cpu: 2000m
memory: 4Gi
AWS Platform Guide
The guide for building and maintaining production-grade Kubernetes clusters with built-in support for SRE best practices.
Source available on GitHub.