Self Evaluation Guide

Step-by-step guide to installing and evaluating StorageOS

Our self-evaluation guide is a step by step recipe for installing and testing StorageOS. This guide is divided into three sections:

  • Installation - install StorageOS with a single command
  • Feature Testing - short walkthrough of some of our features
  • Benchmarking - a recipe to benchmark StorageOS on your infrastructure

For more comprehensive documentation including installation advice for complex setups, operational guides, and use-cases, please see our main documentation site.

Support for Self Evaluations

Should you have questions or require support, there are several ways to get in touch with us. The fastest way to get in touch is to join our public Slack channel. You can also get in touch via email to [email protected].

Furthermore you can fill out the form below and we will get in touch.

 

 

Installation

In this document we detail a simple installation suitable for evaluation purposes. The etcd we install uses a 3 node cluster with ephemeral storage, and as such is not suitable for production workloads. However, for evaluation purposes it should be sufficient. For production deployments, please see our main documentation pages.

A standard StorageOS installation uses the StorageOS operator, which performs most platform-specific configuration for you. The StorageOS operator has been certified by Red Hat and is open source.

The basic installation steps are:

  • Check prerequisites
  • Install an etcd cluster
  • Install the StorageOS Operator
  • Install StorageOS by applying a CR for the Operator to action

Prerequisites

While we do not require custom kernel modules or additional userspace tooling, StorageOS does have a few basic prerequisites that are met by default by most modern distributions:

  • At least 1 CPU core, 2GB RAM free
  • TCP ports 5701-5710 and TCP & UDP 5711 open between all nodes in the cluster
  • A 64bit supported operating system - StorageOS can run without additional packages in Debian 9, RancherOS, RHEL7.5,8 and CentOS7,8 and need the package linux-image-extra for Ubuntu.
  • Mainline kernel modules target_core_mod, tcp_loop, target_core_file, target_core_user, configfs, and ui. These are present by default on most modern linux distributions, and can be installed with standard package managers. See our system configuration page for instructions.

Quick Installation

For those feeling brave and/or lucky, we have encapsulated the installation instructions in this guide into a short bash script. As with similar instructions elsewhere on the internet, caution is advised here. The script is liberally commented and we recommend that you inspect it in your text editor of choice before running.

Run the following command where kubectl is installed and with the context set for your Kubernetes cluster

curl -sL https://storageos.run | bash

Note that this script deploys a cluster with etcd on transient storage, suitable for evaluation purposes only. Do not use this cluster for production workloads.

Your new cluster can be used straight away. You can now jump to the Provision a Volume section below to provision your first volume and license the cluster.

Installing StorageOS Step By Step

This section describes the installation steps in some more detail.

Install etcd

Here we install a 3 node etcd cluster using the CoreOS operator to install on ephemeral storage within your Kubernetes cluster. This is suitable for evaluation purposes. For production deployment instructions, please see our production etcd page.

  1. Download repo

    $ git clone https://github.com/coreos/etcd-operator.git
    
  2. Configure NS, Role and RoleBinding

    $ export ROLE_NAME=etcd-operator
    $ export ROLE_BINDING_NAME=etcd-operator
    $ export NAMESPACE=etcd
    
  3. Create Namespace

    $ kubectl create namespace $NAMESPACE
    
  4. Deploy Operator

    $ ./etcd-operator/example/rbac/create_role.sh
    $ kubectl -n $NAMESPACE create -f - <<END
    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: etcd-operator
    spec:
      selector:
        matchLabels:
          app: etcd-operator
      replicas: 1
      template:
        metadata:
          labels:
            app: etcd-operator
        spec:
          containers:
          - name: etcd-operator
            image: quay.io/coreos/etcd-operator:v0.9.4
            command:
            - etcd-operator
            env:
            - name: MY_POD_NAMESPACE
              valueFrom:
                fieldRef:
                  fieldPath: metadata.namespace
            - name: MY_POD_NAME
              valueFrom:
                fieldRef:
                  fieldPath: metadata.name
    END
    
  5. Create the EtcdCluster resource

    $ kubectl -n etcd create -f - <<YAML
    apiVersion: "etcd.database.coreos.com/v1beta2"
    kind: "EtcdCluster"
    metadata:
     name: "storageos-etcd"
    spec:
     size: 3 # Set to 1 if insufficient nodes
     version: "3.4.7"
     pod:
       etcdEnv:
       - name: ETCD_QUOTA_BACKEND_BYTES
         value: "2147483648"  # 2 GB 
       - name: ETCD_AUTO_COMPACTION_RETENTION
         value: "1000" # Keep 1000 revisions
       - name: ETCD_AUTO_COMPACTION_MODE
         value: "revision" # Set the revision mode
       resources:
         requests:
           cpu: 200m
           memory: 300Mi
       securityContext:
         runAsNonRoot: true
         runAsUser: 9000
         fsGroup: 9000
       tolerations:
       - operator: "Exists" # add tolerations to match all taints on the master nodes where etcd will be deployed
       affinity:
         podAntiAffinity:
           preferredDuringSchedulingIgnoredDuringExecution:
           - weight: 100
             podAffinityTerm:
               labelSelector:
                 matchExpressions:
                 - key: etcd_cluster
                   operator: In
                   values:
                   - storageos-etcd
               topologyKey: kubernetes.io/hostname
    YAML
    

This creates a 3 node etcd cluster and associated service in Kubernetes. We can use the service endpoint when creating the StorageOS cluster.

Install StorageOS Operator

In order to install the StorageOS operator download the requisite yaml manifests or apply them with kubectl.

$ kubectl create -f https://github.com/storageos/cluster-operator/releases/download/v2.2.0/storageos-operator.yaml

You can verify the operator is running using the following command

$ kubectl get pods -n storageos-operator

 

Install StorageOS

Once the StorageOS operator has been installed a StorageOS cluster can be generated by creating a StorageOSCluster resource.

A StorageOSCluster resource describes the state of the StorageOS cluster that is desired and the StorageOS operator will create the desired StorageOS cluster. For examples of StorageOSCluster resources please see our examples page here. For a full list of the configurable spec parameters of the StorageOSCluster resource please see here.

  1. Create a secret defining the API username and password

    $ kubectl create -f - <<END
    apiVersion: v1
    kind: Secret
    metadata:
     name: "storageos-api"
     namespace: "storageos-operator"
     labels:
       app: "storageos"
    type: "kubernetes.io/storageos"
    data:
     # echo -n '<secret>' | base64
     apiUsername: c3RvcmFnZW9z
     apiPassword: c3RvcmFnZW9z
     # CSI Credentials
     csiProvisionUsername: c3RvcmFnZW9z
     csiProvisionPassword: c3RvcmFnZW9z
     csiControllerPublishUsername: c3RvcmFnZW9z
     csiControllerPublishPassword: c3RvcmFnZW9z
     csiNodePublishUsername: c3RvcmFnZW9z
     csiNodePublishPassword: c3RvcmFnZW9z
     csiControllerExpandUsername: c3RvcmFnZW9z
     csiControllerExpandPassword: c3RvcmFnZW9z
    END
    
  2. Create a StorageOSCluster resource

    $ kubectl create -f - <<END
    apiVersion: storageos.com/v1
    kind: StorageOSCluster
    metadata:
     name: example-storageoscluster
     namespace: "storageos-operator"
    spec:
     # StorageOS Pods are in kube-system by default
     secretRefName: "storageos-api"
     secretRefNamespace: "storageos-operator"
     k8sDistro: "upstream"  # Set the Kubernetes distribution for your cluster (upstream, eks, aks, gke, rancher, dockeree)
     # storageClassName: fast # The storage class creates by the StorageOS operator is configurable
     kvBackend:
       address: "storageos-etcd-client.etcd.svc.cluster.local:2379"
    END
    
  3. Confirm that the cluster has been created and that StorageOS pods are running

    $ kubectl -n kube-system get pods
    

    StorageOS pods enter a ready state after a minimum of 45s has passed.

  4. Deploy the StorageOS CLI as a container

    $ kubectl -n kube-system run \
    --image storageos/cli:v2.2.0 \
    --restart=Never                          \
    --env STORAGEOS_ENDPOINTS=storageos:5705 \
    --env STORAGEOS_USERNAME=storageos       \
    --env STORAGEOS_PASSWORD=storageos       \
    --command cli                            \
    -- /bin/sh -c "while true; do sleep 999999; done"
    

Provision a StorageOS Volume

Now that we have a working StorageOS cluster, we can provision a volume to test everything is working as expected.

  1. Create a PVC

    $ kubectl create -f - <<END
    apiVersion: v1
    kind: PersistentVolumeClaim
    metadata:
      name: pvc-1
    spec:
      storageClassName: "fast"
      accessModes:
        - ReadWriteOnce
      resources:
        requests:
          storage: 5Gi
    END
    
  2. Verify that the volume was created with the CLI

    pvc-1 should be listed in the CLI output

    $ kubectl -n kube-system exec -it cli -- storageos get volumes
    
  3. Create a pod that consumes the PVC

    $ kubectl create -f - <<END
    apiVersion: v1
    kind: Pod
    metadata:
     name: d1
    spec:
     containers:
       - name: debian
         image: debian:9-slim
         command: ["/bin/sleep"]
         args: [ "3600" ]
         volumeMounts:
           - mountPath: /mnt
             name: v1
     volumes:
       - name: v1
         persistentVolumeClaim:
           claimName: pvc-1
    END
    
  4. Check that the pod starts successfully. If the pod starts successfully then the StorageOS cluster is working correctly

    $ kubectl get pod d1 -w
    

    The pod mounts a StorageOS volume under /mnt so any files written there will persist beyond the lifetime of the pod. This can be demonstrated using the following commands.

  5. Execute a shell inside the pod and write some data to a file

    $ kubectl exec -it d1 -- bash
    [email protected]:/# echo Hello World! > /mnt/hello
    [email protected]:/# cat /mnt/hello
    

    Hello World! should be printed out.

  6. Delete the pod

    $ kubectl delete pod d1
    
  7. Recreate the pod

    $ kubectl create -f - <<END
    apiVersion: v1
    kind: Pod
    metadata:
     name: d1
    spec:
     containers:
       - name: debian
         image: debian:9-slim
         command: ["/bin/sleep"]
         args: [ "3600" ]
         volumeMounts:
           - mountPath: /mnt
             name: v1
     volumes:
       - name: v1
         persistentVolumeClaim:
           claimName: pvc-1
    END
    
  8. Open a shell inside the pod and check the contents of /mnt/hello

    $ kubectl exec -it d1 -- cat /mnt/hello
    

    Hello World! should be printed out.

License cluster

Newly installed StorageOS clusters must be licensed within 24 hours. Our developer license is free, and supports up to 5TiB of provisioned storage.

You will need access to the StorageOS API on port 5705 of any of your nodes. For convenience, it is often easiest to port forward the service using the following kubectl incantation (this will block, so a second terminal window may be advisable):

$ kubectl port-forward -n kube-system svc/storageos 5705

Now follow the instructions on our operations licensing page to obtain and apply a license.

Installation of StorageOS is now complete.

StorageOS Features

Now that you have a fully functional StorageOS cluster we will explain some of our features that may be of use to you as you complete application and synthetic benchmarks.

StorageOS features are all enabled/disabled by applying labels to volumes. These labels can be passed to StorageOS via persistent volume claims (PVCs) or can be applied to volumes using the StorageOS CLI or GUI.

The following is not an exhaustive feature list but outlines features which are commonly of use during a self-evaluation.

Volume Replication

StorageOS enables synchronous replication of volumes using the storageos.com/replicas label.

The volume that is active is referred to as the master volume. The master volume and its replicas are always placed on separate nodes. In fact if a replica cannot be placed on a node without a replica of the same volume, the volume will fail to be created. For example, in a three node StorageOS cluster a volume with 3 replicas cannot be created as the third replica cannot be placed on a node that doesn’t already contain a replica of the same volume.

See our replication documentation for more information on volume replication.

  1. To test volume replication create the following PersistentVolumeClaim

    $ kubectl create -f - <<END
    apiVersion: v1
    kind: PersistentVolumeClaim
    metadata:
     name: pvc-replicated
     labels:
       storageos.com/replicas: "1"
    spec:
     storageClassName: "fast"
     accessModes:
     - ReadWriteOnce
     resources:
       requests:
         storage: 5Gi
    END
    

    Note that volume replication is enabled by setting the storageos.com/replicas label on the volume.

  2. Confirm that a replicated volume has been created by using the StorageOS CLI or UI

    $ kubectl -n kube-system exec -it cli -- storageos get volumes
    
  3. Create a pod that uses the PVC

    $ kubectl create -f - <<END
    apiVersion: v1
    kind: Pod
    metadata:
    name: replicated-pod
    spec:
    containers:
      - name: debian
        image: debian:9-slim
        command: ["/bin/sleep"]
        args: [ "3600"  ]
        volumeMounts:
          - mountPath: /mnt
            name: v1
    volumes:
      - name: v1
        persistentVolumeClaim:
          claimName: pvc-replicated
    END
    
  4. Write data to the volume

    $ kubectl exec -it replicated-pod -- bash
    [email protected]:/# echo Hello World! > /mnt/hello
    [email protected]:/# cat /mnt/hello
    

    Hello World! should be printed out.

  5. Find the location of the master volume and shutdown the node

    Shutting down a node causes all volumes, with online replicas, on the node to be evicted. For replicated volumes this immediately promotes a replica to become the new master.

    $ kubectl get pvc
    NAME           STATUS   VOLUME                                     CAPACITY   ACCESS MODES   STORAGECLASS   AGE
    pvc-replicated Bound    pvc-29e2ad6e-8c4e-11e9-8356-027bfbbece86   5Gi        RWO            fast           1m
    
    $ kubectl exec -it -n kube-system cli -- storageos get volumes
    NAMESPACE  NAME                                      SIZE     LOCATION              ATTACHED ON   REPLICAS  AGE
    default    pvc-4e796a62-0271-45f9-9908-21d58789a3fe  5.0 GiB  kind-worker (online)  kind-worker2  1/1       26 seconds ago
    
    
  6. Check the location of the master volume and notice that it is on a new node. If the pod that mounted the volume was located on the same node that was shutdown then the pod will need to be recreated.

    $ kubectl exec -it -n kube-system cli -- storageos get volumes
    NAMESPACE  NAME                                      SIZE     LOCATION               ATTACHED ON   REPLICAS  AGE
    default    pvc-4e796a62-0271-45f9-9908-21d58789a3fe  5.0 GiB  kind-worker2 (online)  kind-worker2  1/1       46 seconds ago
    
  7. Check that the data is still accessible to the pod

    $ kubectl exec -it replicated-pod -- bash
    [email protected]:/# cat /mnt/hello
    

    Hello World! should be printed out.

 

Benchmarking

Benchmarking storage is a complex topic. Considering the many books and papers that have been written about benchmarking, we could write many paragraphs here and only begin to scratch the surface.

Taking this complexity into account we present recipes for both synthetic benchmarks using FIO, and a sample application benchmark to test PostgreSQL using pgbench. The approaches are complementary - synthetic benchmarks allow us to strictly control the parameters of the IO we put through the system in order to stress various aspects of it. Application benchmarks allow us to get a sense of the performance of the system when running an actual representative workload - which of course is the ultimate arbiter of performance.

Despite the inherent complexity of benchmarking storage there are a few general considerations to keep in mind.

Considerations

Local vs. Remote Volumes

When a workload is placed on the same node as a volume, there is no network round trip for IO, and performance is consequently improved. When considering the performance of StorageOS it is important to evaluate both local and remote volumes; since for certain workloads we want the high performance of a local attachment, but we also desire the flexibility of knowing that our less performance-sensitive workloads can run from any node in the cluster.

The Effect of Synchronous Replication

Synchronous replication does not impact the read performance of a volume, but it can have a significant impact on the write performance of the volume, since all writes must be propagated to replicas before being acked to the application. The impact varies in proportion to the inter-node latency. For an inter-node latency of 1ms, we have a max ceiling of 1000 write IOPS, and in reality a little less than that to allow for processing time on the nodes. This is less concerning then it may first appear, since many applications will issue multiple writes in parallel (known as increasing the queue depth).

Synthetic Benchmarks

Prerequisites

  • Kubernetes cluster with a minimum of 3 nodes and a minimum of 30 Gb available capacity
  • StorageOS CLI running as a pod in the cluster

Synthetic benchmarks using tools such as FIO are a useful way to begin measuring StorageOS performance. While not fully representative of application performance, they allow us to reason about the performance of storage devices without the added complexity of simulating real world workloads, and provide results easily comparable across platforms.

FIO has a number of parameters that can be adjusted to simulate a variety of workloads and configurations. Parameters that are particularly important are:

  • Block Size - the size of the IO units performed.
  • Queue Depth - the amount of concurrent IOs in flight
  • IO Pattern - access can be random across the disk, or sequentially. IO subsystems typically perform better with sequential IO, because of the effect of read ahead caches, and other factors

For this self-evaluation we will run a set of tests based on the excellent DBench, which distills the numerous FIO options into a series of well-crafted scenarios:

  • Random Read/Write IOPS and BW - these tests measure the IOPS ceiling (with a 4k block size) and bandwidth ceiling (with a 128K block size) of the volume using a random IO pattern and high queue depth
  • Average Latency - these tests measure the IO latency of the volume under favourable conditions using a random access pattern, low queue depth and low block size
  • Sequential Read/Write - these tests measure the sequential read/write throughput of the volume with a high queue depth and high block size
  • Mixed Random Read/Write IOPS - these tests measure the performance of the volume under a 60/40 read/write workload using a random access pattern and low blocksize

For convenience we present a single script to run the scenarios using local and remote volumes both with and without a replica. Deploy the FIO tests for the four scenarios using the following command:

curl -sL https://docs.storageos.com/sh/deploy-synthetic-benchmarks.sh | bash

The script will take approximately 20 minutes to complete, and will print the results to STDOUT.

The exact results observed will depend on the particular platform and environment, but the following trends should be observable:

  • local volumes perform faster than remote volumes
  • read performance is independent of the number of replicas
  • write performance is dependent on the number of replicas

Application Benchmarks

While synthetic benchmarks are useful for examining the behaviour of StorageOS with very specific workloads, in order to get a realistic picture of StorageOS performance actual applications should be tested.

Many applications come with test suites which provide standard workloads. For best results, test using your application of choice with a representative configuration and real world data.

As an example of benchmarking an application the following steps lay out how to benchmark a Postgres database backed by a StorageOS volume.

  1. Start by cloning the StorageOS use cases repository. Note this is the same repository that we cloned earlier so if you already have a copy just cd storageos-usecases/pgbench.

    $ git clone https://github.com/storageos/use-cases.git storageos-usecases
    
  2. Move into the Postgres examples folder

    $ cd storageos-usecases/pgbench
    
  3. Decide which node you want the pgbench pod and volume to be located on. The node needs to be labelled app=postgres

    $ kubectl label node <NODE> app=postgres
    
  4. Then set the storageos.com/hint.master label in 20-postgres-statefulset.yaml file to match the StorageOS nodeID for the node you have chosen before creating all the files. The StorageOS nodeID can be obtained using the cli and doing a describe node

    $ kubectl create -f .
    
  5. Confirm that Postgres is up and running

    $ kubectl get pods -w -l app=postgres
    
  6. Use the StorageOS CLI or the GUI to check the master volume location and the mount location. They should match

    $ kubectl -n kube-system exec -it cli -- storageos get volumes
    
  7. Exec into the pgbench container and run pgbench

    $ kubectl exec -it pgbench -- bash -c '/opt/cpm/bin/start.sh'
    

 

Conclusion

After completing these steps you will have benchmark scores for StorageOS. Please keep in mind that benchmarks are only part of the story and that there is no replacement for testing actual production or production like workloads.

StorageOS invites you to provide feedback on your self-evaluation to the slack channel or by directly emailing us at [email protected]]