Skip to content

Latest commit

 

History

History
 
 

cassandra

WARNING WARNING WARNING WARNING WARNING

PLEASE NOTE: This document applies to the HEAD of the source tree

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.

Cloud Native Deployments of Cassandra using Kubernetes

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:

Prerequisites

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.

A note for the impatient

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.

Simple Single Pod Cassandra Node

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: {}

Download example

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.

Cassandra Service

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

Download example

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

Adding replicated nodes

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: {}

Download example

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

Using a DaemonSet

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: {}

Download example

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

tl; dr;

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

Seed Provider Source

See here.

Analytics