b) Logging and Visualization for Helm Chart oud-ds-rs Deployment

  1. Introduction
  2. Installation
    1. Create a Kubernetes secret
    2. Enable Elasticsearch, Logstash, and Kibana
    3. Upgrade OUD deployment with ELK configuration
    4. Verify the pods
  3. Verify using the Kibana application

Introduction

This section describes how to install and configure logging and visualization for the oud-ds-rs Helm chart deployment.

The ELK stack consists of Elasticsearch, Logstash, and Kibana. Using ELK you can gain insights in real-time from the log data from your applications.

  • Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data so you can discover the expected and uncover the unexpected.
  • Logstash is an open source, server-side data processing pipeline that ingests data from a multitude of sources simultaneously, transforms it, and then sends it to your favorite “stash.”
  • Kibana lets you visualize your Elasticsearch data and navigate the Elastic Stack. It gives you the freedom to select the way you give shape to your data. And you don’t always have to know what you’re looking for.

Installation

ELK can be enabled for environments created using the Helm charts provided. The example below will demonstrate installation and configuration of ELK for the oud-ds-rs chart.

Create a Kubernetes secret

A Kubernetes secret to access the required images on hub.docker.com should have been previously created in Create OUD instances.

If you have not yet created a Kubernetes secret refer back to Create OUD instances.

Enable Elasticsearch, Logstash, and Kibana

  1. Create a directory on the persistent volume to store the ELK log files:

    $ mkdir -p <persistent_volume>/oud_elk_data
    $ chmod 777 <persistent_volume>/oud_elk_data
    

    For example:

    $ mkdir -p /scratch/shared/oud_elk_data
    $ chmod 777 /scratch/shared/oud_elk_data
    
  2. Navigate to the $WORKDIR/kubernetes/helm directory and create a logging-override-values.yaml with the following:

    elk:
      enabled: true
      imagePullSecrets:
        - name: dockercred
    
    elkVolume:
      # If enabled, it will use the persistent volume.
      # if value is false, PV and PVC would not be used and there would not be any mount point available for config
      enabled: true
      type: filesystem
      filesystem:
        hostPath:
          path: <persistent_volume>/oud_elk_data
    

    For example:

    elk:
      enabled: true
      imagePullSecrets:
        - name: dockercred
    
    elkVolume:
      # If enabled, it will use the persistent volume.
      # if value is false, PV and PVC would not be used and there would not be any mount point available for config
      enabled: true
      type: filesystem
      filesystem:
        hostPath:
          path: /scratch/shared/oud_elk_data
    

    If using NFS for the persistent volume change the elkVolume section as follows:

    elkVolume:
      # If enabled, it will use the persistent volume.
      # if value is false, PV and PVC would not be used and there would not be any mount point available for config
      enabled: true
      type: networkstorage
      networkstorage:
        nfs:
          server: myserver
          path: <persistent_volume>/oud_elk_data
    

Upgrade OUD deployment with ELK configuration

  1. Run the following command to upgrade the OUD deployment with the ELK configuration:

    $ helm upgrade --namespace <namespace> --values <valuesfile.yaml> <releasename> oud-ds-rs --reuse-values
    

    For example:

    $ helm upgrade --namespace oudns --values logging-override-values.yaml oud-ds-rs oud-ds-rs --reuse-values
    

Verify the pods

  1. Run the following command to verify the elasticsearch, logstash and kibana pods are running:

    $ kubectl get pods -o wide -n <namespace> | grep 'es\|kibana\|logstash'
    

    For example:

    $ kubectl get pods -o wide -n oudns | grep 'es\|kibana\|logstash'
    

    The output will look similar to the following:

    oud-ds-rs-es-cluster-0                1/1     Running   0          6m28s
    oud-ds-rs-kibana-7b7769485f-b9mr4     1/1     Running   0          6m28s
    oud-ds-rs-logstash-5995948d7f-nqlh6   1/1     Running   0          6m28s   
    

    From the above identify the elasticsearch pod, for example: oud-ds-rs-es-cluster-0.

  2. Run the port-forward command to allow elasticsearch to listen on port 9200:

    $ kubectl port-forward oud-ds-rs-es-cluster-0 9200:9200 --namespace=<namespace> &
    

    For example:

    $ kubectl port-forward oud-ds-rs-es-cluster-0 9200:9200 --namespace=oudns &
    

    The output will look similar to the following:

    [1] 98458
    bash-4.2$ Forwarding from 127.0.0.1:9200 -> 9200
    Forwarding from [::1]:9200 -> 9200
    
  3. Verify that elasticsearch is running by interrogating port 9200:

    $ curl http://localhost:9200
    

    The output will look similar to the following:

    {
      "name" : "oud-ds-rs-es-cluster-0",
      "cluster_name" : "OUD-elk",
      "cluster_uuid" : "J42fuv_XSHGy-uolRyNEtA",
      "version" : {
        "number" : "6.8.0",
        "build_flavor" : "default",
        "build_type" : "docker",
        "build_hash" : "65b6179",
        "build_date" : "2019-05-15T20:06:13.172855Z",
        "build_snapshot" : false,
        "lucene_version" : "7.7.0",
        "minimum_wire_compatibility_version" : "5.6.0",
        "minimum_index_compatibility_version" : "5.0.0"
      },
      "tagline" : "You Know, for Search"
    }
    

Verify using the Kibana application

  1. List the Kibana application service using the following command:

    $ kubectl get svc -o wide -n <namespace> | grep kibana
    

    For example:

    $ kubectl get svc -o wide -n oudns | grep kibana
    

    The output will look similar to the following:

    oud-ds-rs-kibana             NodePort    10.103.169.218   <none>        5601:31199/TCP               13m   app=kibana
    

    In this example, the port to access the Kibana application is 31199.

  2. Access the Kibana console in a browser with: http://${MASTERNODE-HOSTNAME}:${KIBANA-PORT}/app/kibana.

  3. From the Kibana portal navigate to Management> Kibana > Index Patterns.

  4. In the Create Index Pattern page enter * for the Index pattern and click Next Step.

  5. In the Configure settings page, from the Time Filter field name drop down menu select @timestamp and click Create index pattern.

  6. Once the index pattern is created click on Discover in the navigation menu to view the OUD logs.