charts/bitnami/dataplatform-bp2

Data Platform Blueprint 2 with Kafka-Spark-Elasticsearch

Enterprise applications increasingly rely on large amounts of data, that needs be distributed, processed, and stored. Open source and commercial supported software stacks are available to implement a data platform, that can offer common data management services, accelerating the development and deployment of data hungry business applications.

This Helm chart enables the fully automated Kubernetes deployment of such multi-stack data platform, covering the following software components:

• Apache Kafka – Data distribution bus with buffering capabilities
• Apache Spark – In-memory data analytics
• Elasticsearch with Kibana – Data persistence and search
• Logstash - Data Processing Pipeline

These containerized stateful software stacks are deployed in multi-node cluster configurations, which is defined by the Helm Chart blueprint for this data platform deployment, covering:

• Pod placement rules – Affinity rules to ensure placement diversity to prevent single point of failures and optimize load distribution
• Pod resource sizing rules – Optimized Pod and JVM sizing settings for optimal performance and efficient resource usage
• Default settings to ensure Pod access security
• Optional Tanzu Observability framework configuration

In addition to the Pod resource optimizations, this blueprint is validated and tested to provide Kubernetes node count and sizing recommendations (see Kubernetes Cluster Requirements) to facilitate cloud platform capacity planning. The goal is optimize the number of required Kubernetes nodes in order to optimize server resource usage and, at the same time, ensuring runtime and resource diversity.

The first release of this blueprint defines a small size data platform deployment, deployed on 3 Kubernetes application nodes with physical diverse underlying server infrastructure.

Use cases for this small size data platform setup include: data and application evaluation, development, and functional testing.

TL;DR

$ helm repo add bitnami https://charts.bitnami.com/bitnami
$ helm install my-release bitnami/dataplatform-bp2

Introduction

This chart bootstraps Data Platform Blueprint-2 deployment on a Kubernetes cluster using the Helm package manager.

The "Small" size data platform in default configuration deploys the following:

1. Zookeeper with 3 nodes to be used for both Kafka
2. Kafka with 3 nodes using the zookeeper deployed above
3. Elasticsearch with 3 master nodes, 2 data nodes, 2 coordinating nodes and 1 kibana node
4. Logstash with 2 nodes
5. Spark with 1 Master and 2 worker nodes

The data platform can be optionally deployed with the Tanzu observability framework. In that case, the wavefront collectors will be set up as a DaemonSet to collect the Kubernetes cluster metrics to enable runtime feed into the Tanzu Observability service. It will also be pre-configured to scrape the metrics from the Prometheus endpoint that each application (Kafka/Spark/Elasticsearch/Logstash) emits the metrics to.

Bitnami charts can be used with Kubeapps for deployment and management of Helm Charts in clusters. This Helm chart has been tested on top of Bitnami Kubernetes Production Runtime (BKPR). Deploy BKPR to get automated TLS certificates, logging and monitoring for your applications.

Prerequisites

• Kubernetes 1.12+
• Helm 3.1.0
• PV provisioner support in the underlying infrastructure

Kubernetes Cluster requirements

Below are the minimum Kubernetes Cluster requirements for "Small" size data platform:

Data Platform Size	Kubernetes Cluster Size	Usage
Small	1 Master Node (2 CPU, 4Gi Memory) 3 Worker Nodes (4 CPU, 32Gi Memory)	Data and application evaluation, development, and functional testing

Installing the Chart

To install the chart with the release name my-release:

$ helm repo add bitnami https://charts.bitnami.com/bitnami
$ helm install my-release bitnami/dataplatform-bp2

These commands deploy Data Platform on the Kubernetes cluster in the default configuration. The Parameters section lists recommended configurations of the parameters to bring up an optimal and resilient data platform. Please refer the individual charts for the remaining set of configurable parameters.

Tip

: List all releases using helm list

Uninstalling the Chart

To uninstall/delete the my-release deployment:

$ helm delete my-release

The command removes all the Kubernetes components associated with the chart and deletes the release.

Parameters

Global parameters

Name	Description	Value
global.imageRegistry	Global Docker image registry	""
global.imagePullSecrets	Global Docker registry secret names as an array	[]
global.storageClass	Global StorageClass for Persistent Volume(s)	""

Kafka parameters

Name	Description	Value
kafka.enabled	Enable Kafka subchart	true
kafka.replicaCount	Number of Kafka brokers	3
kafka.heapOpts	Kafka Java Heap size	-Xmx4096m -Xms4096m
kafka.resources.limits	Resource limits for Kafka	{}
kafka.resources.requests.cpu	CPU capacity request for Kafka nodes	250m
kafka.resources.requests.memory	Memory capacity request for Kafka nodes	5120Mi
kafka.affinity.podAntiAffinity	Kafka anti affinity rules	{}
kafka.affinity.podAffinity	Kafka affinity rules	{}
kafka.metrics.kafka.enabled	Enable prometheus exporter for Kafka	false
kafka.metrics.kafka.resources.limits	Resource limits for kafka prometheus exporter	{}
kafka.metrics.kafka.resources.requests.cpu	CPU capacity request for Kafka prometheus nodes	100m
kafka.metrics.kafka.resources.requests.memory	Memory capacity request for Kafka prometheus nodes	128Mi
kafka.metrics.kafka.service.port	Kafka Exporter Prometheus port to be used in wavefront configuration	9308
kafka.metrics.jmx.enabled	Enable JMX exporter for Kafka	false
kafka.metrics.jmx.resources.limits	Resource limits for kafka prometheus exporter	{}
kafka.metrics.jmx.resources.requests.cpu	CPU capacity request for Kafka prometheus nodes	100m
kafka.metrics.jmx.resources.requests.memory	Memory capacity request for Kafka prometheus nodes	128Mi
kafka.metrics.jmx.service.port	JMX Prometheus exporter service port	5556
kafka.zookeeper.enabled	Enable the Kafka subchart's Zookeeper	true
kafka.zookeeper.replicaCount	Number of Zookeeper nodes	3
kafka.zookeeper.heapSize	Size in MB for the Java Heap options (Xmx and XMs) in Zookeeper. This env var is ignored if Xmx an Xms are configured via JVMFLAGS	4096
kafka.zookeeper.resources.limits	Resource limits for zookeeper	{}
kafka.zookeeper.resources.requests.cpu	CPU capacity request for zookeeper	250m
kafka.zookeeper.resources.requests.memory	Memory capacity request for zookeeper	5Gi
kafka.zookeeper.affinity.podAntiAffinity	Zookeeper pod anti affinity rules	{}
kafka.externalZookeeper.servers	Array of external Zookeeper servers	[]

Spark parameters

Name	Description	Value
spark.enabled	Enable Spark subchart	true
spark.master.webPort	Web port for spark master	8080
spark.master.resources.limits	Spark master resource limits	{}
spark.master.resources.requests.cpu	Spark master CPUs	250m
spark.master.resources.requests.memory	Spark master requested memory	5Gi
spark.master.affinity.podAntiAffinity	Anti affinity rules set for resiliency	{}
spark.worker.replicaCount	Number of spark workers	2
spark.worker.webPort	Web port for spark master	8081
spark.worker.resources.limits	Spark master resource limits	{}
spark.worker.resources.requests.cpu	Spark master CPUs	250m
spark.worker.resources.requests.memory	Spark master requested memory	5Gi
spark.worker.affinity.podAntiAffinity	Anti affinity rules set for resiliency	{}
spark.metrics.enabled	Enable Prometheus exporter for Spark	false
spark.metrics.masterAnnotations	Annotations for Spark master exporter	{}
spark.metrics.workerAnnotations	Annotations for Spark worker exporter	{}

Elasticsearch parameters

Name	Description	Value
elasticsearch.enabled	Enable Elasticsearch	true
elasticsearch.global.kibanaEnabled	Enable Kibana	true
elasticsearch.master.replicas	Number of Elasticsearch replicas	3
elasticsearch.master.heapSize	Heap Size for Elasticsearch master	768m
elasticsearch.master.affinity.podAntiAffinity	Elasticsearch pod anti affinity	{}
elasticsearch.master.resources.limits	Elasticsearch master resource limits	{}
elasticsearch.master.resources.requests.cpu	Elasticsearch master CPUs	250m
elasticsearch.master.resources.requests.memory	Elasticsearch master requested memory	1Gi
elasticsearch.master.affinity.podAntiAffinity	Anti affinity rules set for resiliency	{}
elasticsearch.data.name	Elasticsearch data node name	data
elasticsearch.data.replicas	Number of Elasticsearch replicas	2
elasticsearch.data.heapSize	Heap Size for Elasticsearch data node	4096m
elasticsearch.data.affinity.podAntiAffinity	Anti affinity rules set for resiliency	{}
elasticsearch.data.resources.limits	Elasticsearch data node resource limits	{}
elasticsearch.data.resources.requests.cpu	Elasticsearch data node CPUs	250m
elasticsearch.data.resources.requests.memory	Elasticsearch data node requested memory	5Gi
elasticsearch.coordinating.replicas	Number of Elasticsearch replicas	2
elasticsearch.coordinating.heapSize	Heap Size for Elasticsearch coordinating	768m
elasticsearch.coordinating.affinity.podAntiAffinity	Anti affinity rules set for resiliency	{}
elasticsearch.coordinating.resources.limits	Elasticsearch coordinating resource limits	{}
elasticsearch.coordinating.resources.requests.cpu	Elasticsearch coordinating CPUs	250m
elasticsearch.coordinating.resources.requests.memory	Elasticsearch coordinating requested memory	1Gi
elasticsearch.metrics.enabled	Enable Prometheus exporter for Elasticsearch	false
elasticsearch.metrics.resources.limits	Elasticsearch metrics resource limits	{}
elasticsearch.metrics.resources.requests.cpu	Elasticsearch metrics CPUs	100m
elasticsearch.metrics.resources.requests.memory	Elasticsearch metrics requested memory	128Mi
elasticsearch.metrics.service.annotations	Elasticsearch metrics service annotations	{}

Logstash parameters

Name	Description	Value
logstash.enabled	Enable Logstash	true
logstash.replicaCount	Number of Logstash replicas	2
logstash.affinity.podAntiAffinity	Logstash pod anti affinity	{}
logstash.extraEnvVars	Array containing extra env vars to configure Logstash	[]
logstash.resources.limits	Elasticsearch metrics resource limits	{}
logstash.resources.requests.cpu	Elasticsearch metrics CPUs	250m
logstash.resources.requests.memory	Elasticsearch metrics requested memory	1500Mi
logstash.metrics.enabled	Enable metrics for logstash	false
logstash.metrics.resources.limits	Elasticsearch metrics resource limits	{}
logstash.metrics.resources.requests.cpu	Elasticsearch metrics CPUs	100m
logstash.metrics.resources.requests.memory	Elasticsearch metrics requested memory	128Mi
logstash.metrics.service.port	Logstash Prometheus port	9198
logstash.metrics.service.annotations	Annotations for the Prometheus metrics service	{}

Tanzu Observability (Wavefront) parameters

Name	Description	Value
wavefront.enabled	Enable Tanzu Observability Framework	false
wavefront.clusterName	Cluster name	KUBERNETES_CLUSTER_NAME
wavefront.wavefront.url	Tanzu Observability cluster URL	https://YOUR_CLUSTER.wavefront.com
wavefront.wavefront.token	Tanzu Observability access token	YOUR_API_TOKEN
wavefront.wavefront.existingSecret	Tanzu Observability existing secret	""
wavefront.collector.resources.limits	Wavefront collector metrics resource limits	{}
wavefront.collector.resources.requests.cpu	Wavefront collector metrics CPUs	200m
wavefront.collector.resources.requests.memory	Wavefront collector metrics requested memory	10Mi
wavefront.collector.discovery.enabled	Enable wavefront discovery	true
wavefront.collector.discovery.enableRuntimeConfigs	Enable runtime configs for wavefront discovery	true
wavefront.collector.discovery.config	Wavefront discovery config	[]
wavefront.proxy.resources.limits	Wavefront Proxy metrics resource limits	{}
wavefront.proxy.resources.requests.cpu	Wavefront Proxy metrics CPUs	100m
wavefront.proxy.resources.requests.memory	Wavefront Proxy metrics requested memory	5Gi

Specify each parameter using the --set key=value[,key=value] argument to helm install. For example,

$ helm install my-release \
  --set kafka.replicaCount=3 \
  bitnami/dataplatform-bp2

The above command deploys the data platform with Kafka with 3 nodes (replicas).

Alternatively, a YAML file that specifies the values for the above parameters can be provided while installing the chart. For example

$ helm install my-release -f values.yaml bitnami/dataplatform-bp2

Tip

: You can use the default values.yaml

Data Platform Deployment with Observability Framework

In case you need to deploy the data platform with Tanzu Observability Framework for all the applications (Kafka/Spark/Elasticsearch/Logstash) in the data platform, you can specify the 'enabled' parameter using the --set <component>.metrics.enabled=true argument to helm install. For Example,

$ helm install my-release bitnami/dataplatform-bp2 \
    --set kafka.metrics.kafka.enabled=true \
    --set kafka.metrics.jmx.enabled=true \
    --set spark.metrics.enabled=true \
    --set elasticsearch.metrics.enabled=true \
    --set logstash.metrics.enabled=true \
    --set wavefront.enabled=true \
    --set wavefront.clusterName=<K8s-CLUSTER-NAME> \
    --set wavefront.wavefront.url=https://<YOUR_CLUSTER>.wavefront.com \
    --set wavefront.wavefront.token=<YOUR_API_TOKEN>

If you want to use an existing Wavefront deployment, edit the Wavefront Collector ConfigMap and add the following snippet under discovery plugins. Once done, restart the wavefront collectors DaemonSet.

$ kubectl edit configmap wavefront-collector-config -n wavefront

Add the below config:

      discovery:
        enable_runtime_plugins: true
        plugins:
        ## auto-discover kafka-exporter
        - name: kafka-discovery
          type: prometheus
          selectors:
            images:
              - '*bitnami/kafka-exporter*'
          port: 9308
          path: /metrics
          scheme: http
          prefix: kafka.

        ## auto-discover jmx exporter
        - name: kafka-jmx-discovery
          type: prometheus
          selectors:
            images:
              - '*bitnami/jmx-exporter*'
          port: 5556
          path: /metrics
          scheme: http
          prefix: kafkajmx.

        ## auto-discover elasticsearch
        - name: elasticsearch-discovery
          type: prometheus
          selectors:
            images:
              - '*bitnami/elasticsearch-exporter*'
          port: 9114
          path: /metrics
          scheme: http

        ## auto-discover logstash
        - name: logstash-discovery
          type: prometheus
          selectors:
            images:
              - '*bitnami/logstash-exporter*'
          port: 9198
          path: /metrics
          scheme: http

        ## auto-discover spark
        - name: spark-worker-discovery
          type: prometheus
          selectors:
            images:
              - '*bitnami/spark*'
          port: 8081
          path: /metrics/
          scheme: http
          prefix: spark.

        ## auto-discover spark
        - name: spark-master-discovery
          type: prometheus
          selectors:
            images:
              - '*bitnami/spark*'
          port: 8080
          path: /metrics/
          scheme: http
          prefix: spark.

Below is the command to restart the DaemonSets

$ kubectl rollout restart daemonsets wavefront-collector -n wavefront

Configuration and installation details

Rolling VS Immutable tags

It is strongly recommended to use immutable tags in a production environment. This ensures your deployment does not change automatically if the same tag is updated with a different image.

Bitnami will release a new chart updating its containers if a new version of the main container, significant changes, or critical vulnerabilities exist.

Troubleshooting

Find more information about how to deal with common errors related to Bitnami’s Helm charts in this troubleshooting guide.

In order to render complete information about the deployment including all the sub-charts, please use --render-subchart-notes flag while installing the chart.

Notable changes

0.3.0

Elasticsearch dependency version was bumped to a new major version changing the license of some of its components to the Elastic License that is not currently accepted as an Open Source license by the Open Source Initiative (OSI). Check Elasticsearch Upgrading Notes for more information.

Regular upgrade is compatible from previous versions.

Upgrading

To 6.0.0

This major version updates resources for elasticsearch and logstash values. Also updates the README file with instructions on how to enable existing Wavefront deployment for the data platform blueprint.

To 5.0.0

This major updates the Kafka subchart its newest major, 14.0.0. Here you can find more information about the changes introduced in this version.

To 4.0.0

This major updates the Kafka subchart to its newest major 13.0.0. For more information on this subchart's major, please refer to kafka upgrade notes.

To 3.0.0

This major version updates the prefixes of individual applications metrics in Wavefront Collectors which are fed to Tanzu observability in order to light up the individual dashboards of Kafka, Spark ElasticSearch and Logstash on Tanzu Observability platform.

To 2.0.0

This major updates the wavefront subchart to it newest major, 3.0.0, which contains a new major for kube-state-metrics. For more information on this subchart's major, please refer to wavefront upgrade notes.

To 1.0.0

The affinity rules have been updated to allow deploying this chart and the dataplatform-bp1 chart in the same cluster.