* Adjust firewall rules, security groups, cloud load balancers,
and generated kubeconfig's
* Facilitates some future simplifications and cost reductions
* Bare-Metal users who exposed kube-apiserver on a WAN via their
router or load balancer will need to adjust its configuration.
This is uncommon, most apiserver are on LAN and/or behind VPN
so no routing infrastructure is configured with the port number
* Choose the Container Linux derivative Flatcar Linux on
bare-metal by setting os_channel to flatcar-stable, flatcar-beta
or flatcar-alpha
* As with Container Linux from Red Hat, the version (os_version)
must correspond to the channel being used
* Thank you to @dongsupark from Kinvolk
* Replace os_channel variable with os_image to align naming
across clouds. Users who set this option to stable, beta, or
alpha should now set os_image to coreos-stable, coreos-beta,
or coreos-alpha.
* Default os_image to coreos-stable. This continues to use
the most recent image from the stable channel as always.
* Allow Container Linux derivative Flatcar Linux by setting
os_image to `flatcar-stable`, `flatcar-beta`, `flatcar-alpha`
* Add `worker_price` to allow worker spot instances. Defaults
to empty string for the worker autoscaling group to use regular
on-demand instances.
* Add `spot_price` to internal `workers` module for spot worker
pools
* Note: Unlike GCP `preemptible` workers, spot instances require
you to pick a bid price.
* Allow multi-controller clusters on Google Cloud
* GCP regional network load balancers have a long open
bug in which requests originating from a backend instance
are routed to the instance itself, regardless of whether
the health check passes or not. As a result, only the 0th
controller node registers. We've recommended just using
single master GCP clusters for a while
* https://issuetracker.google.com/issues/67366622
* Workaround issue by switching to a GCP TCP Proxy load
balancer. TCP proxy lb routes traffic to a backend service
(global) of instance group backends. In our case, spread
controllers across 3 zones (all regions have 3+ zones) and
organize them in 3 zonal unmanaged instance groups that
serve as backends. Allows multi-controller cluster creation
* GCP network load balancers only allowed legacy HTTP health
checks so kubelet 10255 was checked as an approximation of
controller health. Replace with TCP apiserver health checks
to detect unhealth or unresponsive apiservers.
* Drawbacks: GCP provision time increases, tailed logs now
timeout (similar tradeoff in AWS), controllers only span 3
zones instead of the exact number in the region
* Workaround in Typhoon has been known and posted for 5 months,
but there still appears to be no better alternative. Its
probably time to support multi-master and accept the downsides
* Change EBS volume type from `standard` ("prior generation)
to `gp2`. Prometheus alerts are tuned for SSDs
* Other platforms have fast enough disks by default
* Calico isn't viable on Digital Ocean because their firewalls
do not support IP-IP protocol. Its not viable to run a cluster
without firewalls just to use Calico.
* Remove the caveat note. Don't allow users to shoot themselves
in the foot
* Fix issue where worker firewall rules didn't apply to
additional workers attached to a GCP cluster using the new
"worker pools" feature (unreleased, #148). Solves host
connection timeouts and pods not being scheduled to attached
worker pools.
* Add `name` field to GCP internal worker module to represent
the unique name of of the worker pool
* Use `cluster_name` field of GCP internal worker module for
passing the name of the cluster to which workers should be
attached
* This reverts commit cce4537487.
* Provider passing to child modules is complex and the behavior
changed between Terraform v0.10 and v0.11. We're continuing to
allow both versions so this change should be reverted. For the
time being, those using our internal Terraform modules will have
to be aware of the minimum version for AWS and GCP providers,
there is no good way to do enforcement.
* Allow groups of workers to be defined and joined to
a cluster (i.e. worker pools)
* Move worker resources into a Terraform submodule
* Output variables needed for passing to worker pools
* Add usage docs for AWS worker pools (advanced)
* Set defaults for internal worker module's count,
machine_type, and os_image
* Allow "pools" of homogeneous workers to be created
using the google-cloud/kubernetes/workers module
