Change:
I propose that we default to for the master node (and maybe for 150 nodes?). We've seen problems with running out of memory on the master with the , and we've seen pauses that look like CPU exhaustion on the t2 class in general. Also the master is the hardest instance to resize. It is doable to reconfigure the ASG for the nodes (or add a new one, but the master is tricky). what do you think? cc

Discussion:
# Dynamically set the master size by the number of nodes, these are guesses # TODO: gather some data if [[ -z ${MASTER_SIZE} ]]; then <del> if (( ${NUM_NODES} < 50 )); then MASTER_SIZE="t2.micro" elif (( ${NUM_NODES} < 150 )); then MASTER_SIZE="t2.small" </del> <ins> if (( ${NUM_NODES} < 150 )); then MASTER_SIZE="m3.medium" </ins> else <del> MASTER_SIZE="t2.medium" </del> <ins> MASTER_SIZE="m3.large" </ins> fi fi

```bash export KUBE_AWS_ZONE=eu-west-1c export NUM_NODES=2 <ins> export MASTER_SIZE=m3.medium </ins> export NODE_SIZE=m3.medium export AWS_S3_REGION=eu-west-1 export AWS_S3_BUCKET=mycompany-kubernetes-artifacts

... ``` <del> If you don't specify master and minion sizes, the scripts will attempt to guess the correct size of the master and worker nodes based on `${NUM_NODES}`. In particular, for clusters less than 50 nodes it will use a `t2.micro`, for clusters between 50 and 150 nodes it will use a `t2.small` and for clusters with greater than 150 nodes it will use a `t2.medium`. </del> <ins> If you don't specify master and minion sizes, the scripts will attempt to guess the correct size of the master and worker nodes based on `${NUM_NODES}`. In version 1.2 these default are: * For the master, for clusters of less than 150 nodes it will use an `m3.medium`, for clusters of greater than 150 nodes it will use an `m3.large`. * For worker nodes, for clusters less than 50 nodes it will use a `t2.micro`, for clusters between 50 and 150 nodes it will use a `t2.small` and for clusters with greater than 150 nodes it will use a `t2.medium`. </ins> WARNING: beware that `t2` instances receive a limited number of CPU credits per hour and might not be suitable for clusters where the CPU is used consistently. As a rough estimation, consider 15 pods/node the absolute limit a `t2.large` instance can handle before it starts exhausting its CPU credits steadily, although this number depends heavily on the usage. <ins> In prior versions of kubernetes, we defaulted the master node to a t2-class instance, but found that this sometimes gave hard-to-diagnose problems when the master ran out of memory or CPU credits.  If you are running a test cluster and want to save money, you can specify `export MASTER_SIZE=t2.micro` but if your master pauses do check the CPU credits in the AWS console. For production usage, we recommend at least `export MASTER_SIZE=m3.medium` and `export NODE_SIZE=m3.medium`.  And once you get above a handful of nodes, be aware that one m3.large instance has more storage than two m3.medium instances, for the same price. We generally recommend the m3 instances over the m4 instances, because the m3 instances include local instance storage.  Historically local instance storage has been more reliable than AWS EBS, and performance should be more consistent. The ephemeral nature of this storage is a match for ephemeral container workloads also! If you use an m4 instance, or another instance type which does not have local instance storage, you may want to increase the `NODE_ROOT_DISK_SIZE` value, although the default value of 32 is probably sufficient for the smaller instance types in the m4 family. </ins> The script will also try to create or reuse a keypair called "kubernetes", and IAM profiles called "kubernetes-master" and "kubernetes-minion". If these already exist, make sure you want them to be used here.