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Building Globally Distributed Services using Kubernetes Cluster Federation
Editor's note: Today’s post is by Allan Naim, Product Manager, and Quinton Hoole, Staff Engineer at Google, showing how to deploy a multi-homed service behind a global load balancer and have requests sent to the closest cluster.
In Kubernetes 1.3, we announced Kubernetes Cluster Federation and introduced the concept of Cross Cluster Service Discovery, enabling developers to deploy a service that was sharded across a federation of clusters spanning different zones, regions or cloud providers. This enables developers to achieve higher availability for their applications, without sacrificing quality of service, as detailed in our previous blog post.
In the latest release, Kubernetes 1.4, we've extended Cluster Federation to support Replica Sets, Secrets, Namespaces and Ingress objects. This means that you no longer need to deploy and manage these objects individually in each of your federated clusters. Just create them once in the federation, and have its built-in controllers automatically handle that for you.
Federated Replica Sets leverage the same configuration as non-federated Kubernetes Replica Sets and automatically distribute Pods across one or more federated clusters. By default, replicas are evenly distributed across all clusters, but for cases where that is not the desired behavior, we've introduced Replica Set preferences, which allow replicas to be distributed across only some clusters, or in non-equal proportions (define annotations).
Starting with Google Cloud Platform (GCP), we’ve introduced Federated Ingress as a Kubernetes 1.4 alpha feature which enables external clients point to a single IP address and have requests sent to the closest cluster with usable capacity in any region, zone of the Federation.
Federated Secrets automatically create and manage secrets across all clusters in a Federation, automatically ensuring that these are kept globally consistent and up-to-date, even if some clusters are offline when the original updates are applied.
Federated Namespaces are similar to the traditional Kubernetes Namespaces providing the same functionality. Creating them in the Federation control plane ensures that they are synchronized across all the clusters in Federation.
Federated Events are similar to the traditional Kubernetes Events providing the same functionality. Federation Events are stored only in Federation control plane and are not passed on to the underlying kubernetes clusters.
Let’s walk through how all this stuff works. We’re going to provision 3 clusters per region, spanning 3 continents (Europe, North America and Asia).
The next step is to federate these clusters. Kelsey Hightower developed a tutorial for setting up a Kubernetes Cluster Federation. Follow the tutorial to configure a Cluster Federation with clusters in 3 zones in each of the 3 GCP regions, us-central1, europe-west1 and asia-east1. For the purpose of this blog post, we’ll provision the Federation Control Plane in the us-central1-b zone. Note that more highly available, multi-cluster deployments are also available, but not used here in the interests of simplicity.
The rest of the blog post assumes that you have a running Kubernetes Cluster Federation provisioned.
Let’s verify that we have 9 clusters in 3 regions running.
$ kubectl --context=federation-cluster get clusters
NAME STATUS AGE
gce-asia-east1-a Ready 17m
gce-asia-east1-b Ready 15m
gce-asia-east1-c Ready 10m
gce-europe-west1-b Ready 7m
gce-europe-west1-c Ready 7m
gce-europe-west1-d Ready 4m
gce-us-central1-a Ready 1m
gce-us-central1-b Ready 53s
gce-us-central1-c Ready 39s
| You can download the source used in this blog post here. The source consists of the following files: | |
|---|---|
| configmaps/zonefetch.yaml | retrieves the zone from the instance metadata server and concatenates into volume mount path |
| replicasets/nginx-rs.yaml | deploys a Pod consisting of an nginx and busybox container |
| ingress/ingress.yaml | creates a load balancer with a global VIP that distributes requests to the closest nginx backend |
| services/nginx.yaml | exposes the nginx backend as an external service |
In our example, we’ll be deploying the service and ingress object using the federated control plane. The ConfigMap object isn’t currently supported by Federation, so we’ll be deploying it manually in each of the underlying Federation clusters. Our cluster deployment will look as follows:
We’re going to deploy a Service that is sharded across our 9 clusters. The backend deployment will consist of a Pod with 2 containers:
- busybox container that fetches the zone and outputs an HTML with the zone embedded in it into a Pod volume mount path
- nginx container that reads from that Pod volume mount path and serves an HTML containing the zone it’s running in
Let’s start by creating a federated service object in the federation-cluster context.
$ kubectl --context=federation-cluster create -f services/nginx.yaml
It will take a few minutes for the service to propagate across the 9 clusters.
$ kubectl --context=federation-cluster describe services nginx
Name: nginx
Namespace: default
Labels: app=nginx
Selector: app=nginx
Type: LoadBalancer
IP:
LoadBalancer Ingress: 108.59.xx.xxx, 104.199.xxx.xxx, ...
Port: http 80/TCP
NodePort: http 30061/TCP
Endpoints: <none>
Session Affinity: None
Let’s now create a Federated Ingress. Federated Ingresses are created in much that same way as traditional Kubernetes Ingresses: by making an API call which specifies the desired properties of your logical ingress point. In the case of Federated Ingress, this API call is directed to the Federation API endpoint, rather than a Kubernetes cluster API endpoint. The API for Federated Ingress is 100% compatible with the API for traditional Kubernetes Services.
$ cat ingress/ingress.yaml
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
name: nginx
spec:
backend:
serviceName: nginx
servicePort: 80
$ kubectl --context=federation-cluster create -f ingress/ingress.yaml
ingress "nginx" created
Once created, the Federated Ingress controller automatically:
- 1.creates matching Kubernetes Ingress objects in every cluster underlying your Cluster Federation
- 2.ensures that all of these in-cluster ingress objects share the same logical global L7 (i.e. HTTP(S)) load balancer and IP address
- 3.monitors the health and capacity of the service “shards” (i.e. your Pods) behind this ingress in each cluster
- 4.ensures that all client connections are routed to an appropriate healthy backend service endpoint at all times, even in the event of Pod, cluster, availability zone or regional outages We can verify the ingress objects are matching in the underlying clusters. Notice the ingress IP addresses for all 9 clusters is the same.
$ for c in $(kubectl config view -o jsonpath='{.contexts[*].name}'); do kubectl --context=$c get ingress; done
NAME HOSTS ADDRESS PORTS AGE
nginx \* 80 1h
NAME HOSTS ADDRESS PORTS AGE
nginx \* 130.211.40.xxx 80 40m
NAME HOSTS ADDRESS PORTS AGE
nginx \* 130.211.40.xxx 80 1h
NAME HOSTS ADDRESS PORTS AGE
nginx \* 130.211.40.xxx 80 26m
NAME HOSTS ADDRESS PORTS AGE
nginx \* 130.211.40.xxx 80 1h
NAME HOSTS ADDRESS PORTS AGE
nginx \* 130.211.40.xxx 80 25m
NAME HOSTS ADDRESS PORTS AGE
nginx \* 130.211.40.xxx 80 38m
NAME HOSTS ADDRESS PORTS AGE
nginx \* 130.211.40.xxx 80 3m
NAME HOSTS ADDRESS PORTS AGE
nginx \* 130.211.40.xxx 80 57m
NAME HOSTS ADDRESS PORTS AGE
nginx \* 130.211.40.xxx 80 56m
Note that in the case of Google Cloud Platform, the logical L7 load balancer is not a single physical device (which would present both a single point of failure, and a single global network routing choke point), but rather a truly global, highly available load balancing managed service, globally reachable via a single, static IP address.
Clients inside your federated Kubernetes clusters (i.e. Pods) will be automatically routed to the cluster-local shard of the Federated Service backing the Ingress in their cluster if it exists and is healthy, or the closest healthy shard in a different cluster if it does not. Note that this involves a network trip to the HTTP(S) load balancer, which resides outside your local Kubernetes cluster but inside the same GCP region.
The next step is to schedule the service backends. Let’s first create the ConfigMap in each cluster in the Federation.
We do this by submitting the ConfigMap to each cluster in the Federation.
$ for c in $(kubectl config view -o jsonpath='{.contexts[\*].name}'); do kubectl --context=$c create -f configmaps/zonefetch.yaml; done
Let’s have a quick peek at our Replica Set:
$ cat replicasets/nginx-rs.yaml
apiVersion: extensions/v1beta1
kind: ReplicaSet
metadata:
name: nginx
labels:
app: nginx
type: demo
spec:
replicas: 9
template:
metadata:
labels:
app: nginx
spec:
containers:
- image: nginx
name: frontend
ports:
- containerPort: 80
volumeMounts:
- name: html-dir
mountPath: /usr/share/nginx/html
- image: busybox
name: zone-fetcher
command:
- "/bin/sh"
- "-c"
- "/zonefetch/zonefetch.sh"
volumeMounts:
- name: zone-fetch
mountPath: /zonefetch
- name: html-dir
mountPath: /usr/share/nginx/html
volumes:
- name: zone-fetch
configMap:
defaultMode: 0777
name: zone-fetch
- name: html-dir
emptyDir:
medium: ""
The Replica Set consists of 9 replicas, spread evenly across 9 clusters within the Cluster Federation. Annotations can also be used to control which clusters Pods are scheduled to. This is accomplished by adding annotations to the Replica Set spec, as follows:
apiVersion: extensions/v1beta1
kind: ReplicaSet
metadata:
name: nginx-us
annotations:
federation.kubernetes.io/replica-set-preferences: ```
{
"rebalance": true,
"clusters": {
"gce-us-central1-a": {
"minReplicas": 2,
"maxReplicas": 4,
"weight": 1
},
"gce-us-central10b": {
"minReplicas": 2,
"maxReplicas": 4,
"weight": 1
}
}
}
For the purpose of our demo, we’ll keep things simple and spread our Pods evenly across the Cluster Federation.
Let’s create the federated Replica Set:
$ kubectl --context=federation-cluster create -f replicasets/nginx-rs.yaml
Verify the Replica Sets and Pods were created in each cluster:
$ for c in $(kubectl config view -o jsonpath='{.contexts[\*].name}'); do kubectl --context=$c get rs; done
NAME DESIRED CURRENT READY AGE
nginx 1 1 1 42s
NAME DESIRED CURRENT READY AGE
nginx 1 1 1 14m
NAME DESIRED CURRENT READY AGE
nginx 1 1 1 45s
NAME DESIRED CURRENT READY AGE
nginx 1 1 1 46s
NAME DESIRED CURRENT READY AGE
nginx 1 1 1 47s
NAME DESIRED CURRENT READY AGE
nginx 1 1 1 48s
NAME DESIRED CURRENT READY AGE
nginx 1 1 1 49s
NAME DESIRED CURRENT READY AGE
nginx 1 1 1 49s
NAME DESIRED CURRENT READY AGE
nginx 1 1 1 49s
$ for c in $(kubectl config view -o jsonpath='{.contexts[\*].name}'); do kubectl --context=$c get po; done
NAME READY STATUS RESTARTS AGE
nginx-ph8zx 2/2 Running 0 25s
NAME READY STATUS RESTARTS AGE
nginx-sbi5b 2/2 Running 0 27s
NAME READY STATUS RESTARTS AGE
nginx-pf2dr 2/2 Running 0 28s
NAME READY STATUS RESTARTS AGE
nginx-imymt 2/2 Running 0 30s
NAME READY STATUS RESTARTS AGE
nginx-9cd5m 2/2 Running 0 31s
NAME READY STATUS RESTARTS AGE
nginx-vxlx4 2/2 Running 0 33s
NAME READY STATUS RESTARTS AGE
nginx-itagl 2/2 Running 0 33s
NAME READY STATUS RESTARTS AGE
nginx-u7uyn 2/2 Running 0 33s
NAME READY STATUS RESTARTS AGE
nginx-i0jh6 2/2 Running 0 34s
Below is an illustration of how the nginx service and associated ingress deployed. To summarize, we have a global VIP (130.211.23.176) exposed using a Global L7 load balancer that forwards requests to the closest cluster with available capacity.
To test this out, we’re going to spin up 2 Google Cloud Engine (GCE) instances, one in us-west1-b and the other in asia-east1-a. All client requests are automatically routed, via the shortest network path, to a healthy Pod in the closest cluster to the origin of the request. So for example, HTTP(S) requests from Asia will be routed directly to the closest cluster in Asia that has available capacity. If there are no such clusters in Asia, the request will be routed to the next closest cluster (in this case the U.S.). This works irrespective of whether the requests originate from a GCE instance or anywhere else on the internet. We only use a GCE instance for simplicity in the demo.
We can SSH directly into the VMs using the Cloud Console or by issuing a gcloud SSH command.
$ gcloud compute ssh test-instance-asia --zone asia-east1-a
-----
user@test-instance-asia:~$ curl 130.211.40.186
<!DOCTYPE html>
<html>
<head>
<title>Welcome to the global site!</title>
</head>
<body>
<h1>Welcome to the global site! You are being served from asia-east1-b</h1>
<p>Congratulations!</p>
user@test-instance-asia:~$ exit
----
$ gcloud compute ssh test-instance-us --zone us-west1-b
----
user@test-instance-us:~$ curl 130.211.40.186
<!DOCTYPE html>
<html>
<head>
<title>Welcome to the global site!</title>
</head>
<body>
<h1>Welcome to the global site! You are being served from us-central1-b</h1>
<p>Congratulations!</p>
----
Federations of Kubernetes Clusters can include clusters running in different cloud providers (e.g. GCP, AWS), and on-premises (e.g. on OpenStack). However, in Kubernetes 1.4, Federated Ingress is only supported across Google Cloud Platform clusters. In future versions we intend to support hybrid cloud Ingress-based deployments.
To summarize, we walked through leveraging the Kubernetes 1.4 Federated Ingress alpha feature to deploy a multi-homed service behind a global load balancer. External clients point to a single IP address and are sent to the closest cluster with usable capacity in any region, zone of the Federation, providing higher levels of availability without sacrificing latency or ease of operation.
We'd love to hear feedback on Kubernetes Cross Cluster Services. To join the community:
- Post issues or feature requests on GitHub
- Join us in the #federation channel on Slack
- Participate in the Cluster Federation SIG
- Download Kubernetes
- Follow Kubernetes on Twitter @Kubernetesio for latest updates