If you are using a released version of Kubernetes, you should refer to the docs that go with that version.
The latest release of this document can be found [here](http://releases.k8s.io/release-1.2/examples/cassandra/README.md).Documentation for other releases can be found at releases.k8s.io.
The following document describes the development of a cloud native
Cassandra deployment on Kubernetes. When we say
cloud native, we mean an application which understands that it is running
within a cluster manager, and uses this cluster management infrastructure to
help implement the application. In particular, in this instance, a custom
Cassandra SeedProvider
is used to enable Cassandra to dynamically discover
new Cassandra nodes as they join the cluster.
This example also uses some of the core components of Kubernetes:
This example assumes that you have a Kubernetes cluster installed and running,
and that you have installed the kubectl
command line tool somewhere in your path. Please see the
getting started guides
for installation instructions for your platform.
This example also has a few code and configuration files needed. To avoid
typing these out, you can git clone
the Kubernetes repository to you local
computer.
This is a somewhat long tutorial. If you want to jump straight to the "do it now" commands, please see the tl; dr at the end.
In Kubernetes, the atomic unit of an application is a Pod. A Pod is one or more containers that must be scheduled onto the same host. All containers in a pod share a network namespace, and may optionally share mounted volumes.
In this simple case, we define a single container running Cassandra for our pod:
apiVersion: v1
kind: Pod
metadata:
labels:
app: cassandra
name: cassandra
spec:
containers:
- args:
- /run.sh
resources:
limits:
cpu: "0.1"
image: gcr.io/google-samples/cassandra:v8
name: cassandra
ports:
- name: cql
containerPort: 9042
- name: thrift
containerPort: 9160
volumeMounts:
- name: data
mountPath: /cassandra_data
env:
- name: MAX_HEAP_SIZE
value: 512M
- name: HEAP_NEWSIZE
value: 100M
- name: POD_NAMESPACE
valueFrom:
fieldRef:
fieldPath: metadata.namespace
volumes:
- name: data
emptyDir: {}
There are a few things to note in this description. First is that we are
running the gcr.io/google-samples/cassandra:v8
image from Google's container registry.
This is a standard Cassandra installation on top of Debian. However it also
adds a custom
SeedProvider
to Cassandra. In
Cassandra, a SeedProvider
bootstraps the gossip protocol that Cassandra
uses to find other nodes.
The KubernetesSeedProvider
discovers the Kubernetes API Server using the built in Kubernetes
discovery service, and then uses the Kubernetes API to find new nodes (more on
this later). See the image directory of this example for specifics on
how the container image was built and what it contains.
You may also note that we are setting some Cassandra parameters (MAX_HEAP_SIZE
and HEAP_NEWSIZE
) and adding information about the
namespace.
We also tell Kubernetes that the container exposes
both the CQL
and Thrift
API ports. Finally, we tell the cluster
manager that we need 0.1 cpu (0.1 core).
In theory, we could create a single Cassandra pod right now, but since
KubernetesSeedProvider
needs to learn what nodes are in the Cassandra
deployment we need to create a service first.
In Kubernetes, a Service describes a set of Pods that perform the same task. For example, the set of Pods in a Cassandra cluster can be a Kubernetes Service, or even just the single Pod we created above. An important use for a Service is to create a load balancer which distributes traffic across members of the set of Pods. But a Service can also be used as a standing query which makes a dynamically changing set of Pods (or the single Pod we've already created) available via the Kubernetes API. This is the way that we use initially use Services with Cassandra.
Here is the service description:
apiVersion: v1
kind: Service
metadata:
labels:
app: cassandra
name: cassandra
spec:
ports:
- port: 9042
selector:
app: cassandra
The important thing to note here is the selector
. It is a query over
labels, that identifies the set of Pods contained by the Service. In this
case the selector is app=cassandra
. If you look back at the Pod
specification above, you'll see that the pod has the corresponding label, so it
will be selected for membership in this Service.
Create this service as follows:
$ kubectl create -f examples/cassandra/cassandra-service.yaml
Now, as the service is running, we can create the first Cassandra pod using the mentioned specification.
$ kubectl create -f examples/cassandra/cassandra.yaml
After a few moments, you should be able to see the pod running, plus its single container:
$ kubectl get pods cassandra
NAME READY STATUS RESTARTS AGE
cassandra 1/1 Running 0 55s
You can also query the service endpoints to check if the pod has been correctly selected.
$ kubectl get endpoints cassandra -o yaml
apiVersion: v1
kind: Endpoints
metadata:
creationTimestamp: 2015-06-21T22:34:12Z
labels:
app: cassandra
name: cassandra
namespace: default
resourceVersion: "944373"
selfLink: /api/v1/namespaces/default/endpoints/cassandra
uid: a3d6c25f-1865-11e5-a34e-42010af01bcc
subsets:
- addresses:
- ip: 10.244.3.15
targetRef:
kind: Pod
name: cassandra
namespace: default
resourceVersion: "944372"
uid: 9ef9895d-1865-11e5-a34e-42010af01bcc
ports:
- port: 9042
protocol: TCP
Of course, a single node cluster isn't particularly interesting. The real power of Kubernetes and Cassandra lies in easily building a replicated, scalable Cassandra cluster.
In Kubernetes a Replication Controller is responsible for replicating sets of identical pods. Like a Service, it has a selector query which identifies the members of its set. Unlike a Service, it also has a desired number of replicas, and it will create or delete Pods to ensure that the number of Pods matches up with its desired state.
Replication controllers will "adopt" existing pods that match their selector query, so let's create a replication controller with a single replica to adopt our existing Cassandra pod.
apiVersion: v1
kind: ReplicationController
metadata:
labels:
app: cassandra
name: cassandra
spec:
replicas: 2
selector:
app: cassandra
template:
metadata:
labels:
app: cassandra
spec:
containers:
- command:
- /run.sh
resources:
limits:
cpu: 0.1
env:
- name: MAX_HEAP_SIZE
value: 512M
- name: HEAP_NEWSIZE
value: 100M
- name: POD_NAMESPACE
valueFrom:
fieldRef:
fieldPath: metadata.namespace
image: gcr.io/google-samples/cassandra:v8
name: cassandra
ports:
- containerPort: 9042
name: cql
- containerPort: 9160
name: thrift
volumeMounts:
- mountPath: /cassandra_data
name: data
volumes:
- name: data
emptyDir: {}
Most of this replication controller definition is identical to the Cassandra pod
definition above; it simply gives the replication controller a recipe to use
when it creates new Cassandra pods. The other differentiating parts are the
selector
attribute which contains the controller's selector query, and the
replicas
attribute which specifies the desired number of replicas, in this
case 1.
Create this controller:
$ kubectl create -f examples/cassandra/cassandra-controller.yaml
Now this is actually not that interesting, since we haven't actually done anything new. Now it will get interesting.
Let's scale our cluster to 2:
$ kubectl scale rc cassandra --replicas=2
Now if you list the pods in your cluster, and filter to the label app=cassandra
, you should see two cassandra pods:
$ kubectl get pods -l="app=cassandra"
NAME READY STATUS RESTARTS AGE
cassandra 1/1 Running 0 3m
cassandra-af6h5 1/1 Running 0 28s
Notice that one of the pods has the human-readable name cassandra
that you
specified in your config before, and one has a random string, since it was named
by the replication controller.
To prove that this all works, you can use the nodetool
command to examine the
status of the cluster. To do this, use the kubectl exec
command to run
nodetool
in one of your Cassandra pods.
$ kubectl exec -ti cassandra -- nodetool status
Datacenter: datacenter1
=======================
Status=Up/Down
|/ State=Normal/Leaving/Joining/Moving
-- Address Load Tokens Owns (effective) Host ID Rack
UN 10.244.0.5 74.09 KB 256 100.0% 86feda0f-f070-4a5b-bda1-2eeb0ad08b77 rack1
UN 10.244.3.3 51.28 KB 256 100.0% dafe3154-1d67-42e1-ac1d-78e7e80dce2b rack1
Now let's scale our cluster to 4 nodes:
$ kubectl scale rc cassandra --replicas=4
In a few moments, you can examine the status again:
$ kubectl exec -ti cassandra -- nodetool status
Datacenter: datacenter1
=======================
Status=Up/Down
|/ State=Normal/Leaving/Joining/Moving
-- Address Load Tokens Owns (effective) Host ID Rack
UN 10.244.2.3 57.61 KB 256 49.1% 9d560d8e-dafb-4a88-8e2f-f554379c21c3 rack1
UN 10.244.1.7 41.1 KB 256 50.2% 68b8cc9c-2b76-44a4-b033-31402a77b839 rack1
UN 10.244.0.5 74.09 KB 256 49.7% 86feda0f-f070-4a5b-bda1-2eeb0ad08b77 rack1
UN 10.244.3.3 51.28 KB 256 51.0% dafe3154-1d67-42e1-ac1d-78e7e80dce2b rack1
Before you start this section, delete the replication controller you created above:
$ kubectl delete rc cassandra
In Kubernetes a Daemon Set can distribute pods onto Kubernetes nodes, one-to-one. Like a ReplicationController, it has a selector query which identifies the members of its set. Unlike a ReplicationController, it has a node selector to limit which nodes are scheduled with the templated pods, and replicates not based on a set target number of pods, but rather assigns a single pod to each targeted node.
An example use case: when deploying to the cloud, the expectation is that instances are ephemeral and might die at any time. Cassandra is built to replicate data across the cluster to facilitate data redundancy, so that in the case that an instance dies, the data stored on the instance does not, and the cluster can react by re-replicating the data to other running nodes.
DaemonSet
is designed to place a single pod on each node in the Kubernetes
cluster. If you're looking for data redundancy with Cassandra, let's create a
daemonset to start our storage cluster:
apiVersion: extensions/v1beta1
kind: DaemonSet
metadata:
labels:
name: cassandra
name: cassandra
spec:
template:
metadata:
labels:
app: cassandra
spec:
# Filter to specific nodes:
# nodeSelector:
# app: cassandra
containers:
- command:
- /run.sh
env:
- name: MAX_HEAP_SIZE
value: 512M
- name: HEAP_NEWSIZE
value: 100M
- name: POD_NAMESPACE
valueFrom:
fieldRef:
fieldPath: metadata.namespace
image: gcr.io/google-samples/cassandra:v8
name: cassandra
ports:
- containerPort: 9042
name: cql
- containerPort: 9160
name: thrift
resources:
request:
cpu: 0.1
volumeMounts:
- mountPath: /cassandra_data
name: data
volumes:
- name: data
emptyDir: {}
Most of this daemon set definition is identical to the Cassandra pod and
ReplicationController definitions above; it simply gives the daemon set a recipe
to use when it creates new Cassandra pods, and targets all Cassandra nodes in
the cluster. The other differentiating part from a Replication Controller is
the nodeSelector
attribute which allows the daemonset to target a specific
subset of nodes, and the lack of a replicas
attribute due to the 1 to 1 node-
pod relationship.
Create this daemonset:
$ kubectl create -f examples/cassandra/cassandra-daemonset.yaml
You may need to disable config file validation, like so:
$ kubectl create -f examples/cassandra/cassandra-daemonset.yaml --validate=false
Now, if you list the pods in your cluster, and filter to the label
app=cassandra
, you should see one new cassandra pod for each node in your
network.
$ kubectl get pods -l="app=cassandra"
NAME READY STATUS RESTARTS AGE
cassandra-af6h5 1/1 Running 0 28s
cassandra-2jq1b 1/1 Running 0 32s
cassandra-34j2a 1/1 Running 0 29s
To prove that this all works, you can use the nodetool
command to examine the
status of the cluster. To do this, use the kubectl exec
command to run
nodetool
in one of your Cassandra pods.
$ kubectl exec -ti cassandra-af6h5 -- nodetool status
Datacenter: datacenter1
=======================
Status=Up/Down
|/ State=Normal/Leaving/Joining/Moving
-- Address Load Tokens Owns (effective) Host ID Rack
UN 10.244.0.5 74.09 KB 256 100.0% 86feda0f-f070-4a5b-bda1-2eeb0ad08b77 rack1
UN 10.244.4.2 32.45 KB 256 100.0% 0b1be71a-6ffb-4895-ac3e-b9791299c141 rack1
UN 10.244.3.3 51.28 KB 256 100.0% dafe3154-1d67-42e1-ac1d-78e7e80dce2b rack1
For those of you who are impatient, here is the summary of the commands we ran in this tutorial.
# create a service to track all cassandra nodes
kubectl create -f examples/cassandra/cassandra-service.yaml
# create a single cassandra node
kubectl create -f examples/cassandra/cassandra.yaml
# create a replication controller to replicate cassandra nodes
kubectl create -f examples/cassandra/cassandra-controller.yaml
# scale up to 2 nodes
kubectl scale rc cassandra --replicas=2
# validate the cluster
kubectl exec -ti cassandra -- nodetool status
# scale up to 4 nodes
kubectl scale rc cassandra --replicas=4
# delete the replication controller
kubectl delete rc cassandra
# then create a daemonset to place a cassandra node on each kubernetes node
kubectl create -f examples/cassandra/cassandra-daemonset.yaml
See here.