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Skydive Operator

Skydive is an open source real-time network topology and protocols analyzer found here:

This operator includes two default installation options of Skydive:

  • A full Skydive version
  • Skydive as netflow collector

Each option defines the default parameters required, and can be used as is for testing. For production it is adviced to customize the defaults.

This document shows how to install the skydive-operator, and deploy the Skydive different options

Pre Requisites

  • Kubernetes version 1.10.0 and higher

  • Persistent volume is needed only if you want to "look back in time" with skydive (that is, if you are interested in the monitoring history); if you don't , then it is not required (an elastic search container will not be created). You can create a persistent volume via the IBM Cloud Private interface or through a yaml file. For example:

apiVersion: v1
kind: PersistentVolume
metadata:
  name: <persistent volume name>
spec:
  capacity:
    storage: 10Gi
  accessModes:
    - ReadWriteOnce
  hostPath:
    path: <PATH>
  • S3 compatible Object Storage available either locally on the same cluster, or at some other location. It is required only if you want to store the netflows collected by skydive for some future analysis; if you don't , then it is not required (an exporter container will not be created).

Installing the Operator

To install the operator:

First deploy the custom resource definitions:

$ kubectl create -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/crds/charts.helm.k8s.io_skydives_crd.yaml
$ kubectl create -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/crds/charts.helm.k8s.io_netflowcollectors_crd.yaml

The charts.helm.k8s.io_skydives_crd.yaml defines a resource type skydive and charts.helm.k8s.io_netflowcollectors_crd.yaml defines skydive as a netflow collector

then install the operator:

$ kubectl create -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/service_account.yaml
$ kubectl create -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/role.yaml
$ kubectl create -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/role_binding.yaml
$ kubectl create -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/operator.yaml

The commands deploy skydive-operator on the Kubernetes cluster. The operator now will monitor the defined custom resources (netflowcollectors and skydives). At this point there are no such actual resources present in the cluster, only definitions of the 2 possible types.

Next an actuall resource can be created - either one of the two predefined possible types:

  • To create a general Skydive resource run:
kubectl create -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/crds/charts.helm.k8s.io_v1alpha1_skydive_cr.yaml
  • To create Skydive as netflow collector resource run:
kubectl create -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/crds/charts.helm.k8s.io_v1alpha1_netflowcollector_cr.yaml

Note: By running on of the above commands, you instruct the skydive-operator to deploy the selected option of skydive with default configuration parameters. To customize the configuration parameters, copy the rellevant cr yaml file to your local environment, modify the values (see the Configuration section below) and run the create command on the modified file.

Uninstalling

To remove the custom resource:

$ kubectl delete -f https://github.com/skydive-project/skydive-operator/blob/master/deploy/crds/charts.helm.k8s.io_v1alpha1_skydive_cr.yaml

or

$ kubectl delete -f https://github.com/skydive-project/skydive-operator/blob/master/deploy/crds/charts.helm.k8s.io_v1alpha1_netflowcollector_cr.yaml

The command causes the skydive-operator to remove all the Kubernetes components associated with skydive custom resource/ netflow collector custom resource

then (optionally) you can remove the operator:

$. kubectl delete -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/operator.yaml

and the custom resource definitions and rbac definitions:

$ kubectl delete -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/crds/charts.helm.k8s.io_skydives_crd.yaml
$ kubectl delete -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/crds/charts.helm.k8s.io_netflowcollectors_crd.yaml
$ kubectl delete -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/role_binding.yaml
$ kubectl delete -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/role.yaml
$ kubectl delete -f https://raw.githubusercontent.com/skydive-project/skydive-operator/master/deploy/service_account.yaml

Configuration

The netflowcollector custom resource can be customized using the following configuration parameters:

Parameter Description Default
exporter.write.s3.endpoint Endpoint of the Object Storage to be used http://127.0.0.1:9000
exporter.write.s3.installLocalMinio Install default Minio Object Storage locally true
exporter.write.s3.region Object Store region default
exporter.write.s3.use_api_key Use an api key for Object Store autentication false
exporter.write.s3.api_key api key for Object Store autentication Empty
exporter.write.s3.access_key access key for Object Store autentication admin
exporter.write.s3.secret_key secret key for Object Store autentication admin1234
exporter.store.bucket bucket name to be used in Object Store default
exporter.store.objectPrefix prefix of stroed objects default
exporter.classify.cluster_net_masks masks of inner cluster ips (space sepparated), used for classification of netflows to ingress/egress/internal/other 10.0.0.0/8 172.16.0.0/12 192.168.0.0/16

For testing purpuses the default values can be kept, for production environment

  • exporter.write.s3.installLocalMinio should be set to false
  • endpoint should be set to an S3 compatible Object Storage
  • the api_key or access_key and secret_key sould be set (set use_api_key to true, if you provide the api_key)
  • set exporter.store.bucket
  • exporter.store.objectPrefix can be set to simulate a 'directory' location of the collected data inside the bucket.

The Skydive custom resource can be castomized using the following configuration parameters (and generally using any of the helm configuration parameters definedhttps://github.com/skydive-project/skydive-helm.):

Parameter Description Default
image.repository Skydive image repository skydive/skydive
image.tag Image tag 0.24.0
image.secretName Image secret for private repository Empty
image.imagePullPolicy Image pull policy IfNotPresent
resources CPU/Memory resource requests/limits Memory: 8192Mi, CPU: 2000m
service.name service name skydive
service.type k8s service type (e.g. NodePort, LoadBalancer) NodePort
service.port TCP port 8082
etcd.port TCP port 12379
analyzer.topology.fabric Fabric connecting k8s nodes TOR1->*[Type=host]/eth0
env Extended environment variables Empty
storage.elasticsearch.host ElasticSearch host 127.0.0.1
storage.elasticsearch.port ElasticSearch port 9200
storage.flows.indicesToKeep Number of flow indices to keep in storage 10
storage.flows.indexEntriesLimit Number of flow records to keep per index 10000
storage.topology.indicesToKeep Number of topology indices to keep in storage 10
storage.topology.indexEntriesLimit Number of topology records to keep per index 10000
persistence.enabled Use a PVC to persist data false
persistence.useDynamicProvisioning Specify a storageclass or leave empty false
dataVolume.name Name of the PVC to be created datavolume
dataVolume.existingClaimName Provide an existing PersistentVolumeClaim nil
dataVolume.storageClassName Storage class of backing PVC nil
dataVolume.size Size of data volume 10Gi

Documentation

Skydive documentation can be found here:

Contact and Support

Invite : https://slack.skydive.network Workspace : https://skydive-project.slack.com

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