Skip to content

Latest commit

 

History

History
302 lines (225 loc) · 9.26 KB

lab_pivotal_bank_analytics.md

File metadata and controls

302 lines (225 loc) · 9.26 KB

Pivotal Bank Analytics

Pivotal Bank Analytics is an extension to pivotal bank that incorporates elasticsearch deployed to Pivotal Container Service and Spring Cloud Data Flow for PCF. It offloads potentially expensive queries from the transactional database source and to elasticsearch.

The demo includes the following:

  • Enterprise Microservices. The venerable Pivotal Bank demo highlights the use of Spring Cloud and Spring Cloud Services deliver enterprise class micro-services capabilities.

  • Stateful Data Services on PKS. Deploy Elasticsearch on PKS leveraging persistent storage and privileged containers.

  • ETL leveraging Spring Cloud Data Flow. Spring Cloud Data Flow for PCF replicates data from MySQL to Elasticsearch using jdbc source and custom Elasticsearch sink.

  • New microservice. Extends Pivotal Bank, through creation of new microservice and updated UI.

Have a look at the updated architecture.

architecture

Requires that you have access to Pivotal Container Service.

Demo Setup Background

The instructions below should be followed as preparation for light weight demo.
Or if you want to learn the specifics from soup to nuts. Once completed, you can access these instructions for a shorter demo that relies on these prerequistes.

Demo Setup Steps

Assumes you have already logged in to pks and cf via the command line and pivotal-bank is already deployed

  1. Setup elasticsearch (must be 5.6.4)

Create elasticsearch cluster

kubectl apply -f vsphere-volume-sc-fast.yaml
kubectl create namespace es-demo
kubectl config set-context my-cluster --namespace=es-demo
kubectl apply -f es-statefulset.yaml
kubectl apply -f es-svc.yaml
  1. Get service details
kubectl get nodes -o wide
kubectl get svc

If your PKS instance is not setup with NSX-T you will need to use the NodePort to access the service.

export ES_HOST=$(kubectl get node  -o 'jsonpath={.items[0].status.addresses[0].address}')
export ES_PORT=$(kubectl get svc elasticsearch -o 'jsonpath={.spec.ports[?(@.port==9300)].nodePort}')
export ES_HTTP_PORT=$(kubectl get svc elasticsearch -o 'jsonpath={.spec.ports[?(@.port==9200)].nodePort}')

Otherwise, the LoadBalancer service should be given and external ip and you can follow these commands.

export ES_HOST=$(kubectl get svc elasticsearch -o 'jsonpath={.status.loadBalancer.ingress[0].ip}')
export ES_PORT=9300
export ES_HTTP_PORT=9200
  1. Test elasticsearch cluster
http $ES_HOST:$ES_HTTP_PORT
http POST $ES_HOST:$ES_HTTP_PORT/trader/trades symbol=PVTL
http $ES_HOST:$ES_HTTP_PORT/trader/_search
  1. Create CUPS for use by analytics-service
cf create-user-provided-service es -p "'{\"cluster-name\":\"elasticsearch\",\"host\":\"$ES_HOST\",\"port\":\"$ES_PORT\"}'"
  1. Build and push the analytics-service

You need to pass in the elasticsearch host and port or the tests will fail.

VCAP_SERVICES_ES_CREDENTIALS_HOST=$ES_HOST \
VCAP_SERVICES_ES_CREDENTIALS_PORT=$ES_PORT \
./gradlew build

cf push
  1. Build and deploy analytics-scdf-sink to bintray or alternative maven repository

You need to pass in the elasticsearch host and port or the tests will fail. Also specify the properties for maven distribution management repository id and url. For example, ...release.id=bintray and ....release.url=https://api.bintray.com/maven/dpfeffer/maven-repo/analytics-scdf-sink

ES_SINK_HOST=$ES_HOST \
ES_SINK_PORT=$ES_PORT \
mvn clean deploy -Ddistribution.management.release.id=<repository_id> -Ddistribution.management.release.url=<repository url>

Ensure that you publish the version that is deployed so that it is publicly accessible

  1. SCDF Command Prep

Get the traderdb connection information

cf env user

Set environment variables

export DB_HOST=10.193.213.234
export DB_USERNAME=9e0aaf43b46d47a1ab0eb56ab4ce2f0b
export DB_PASSWORD=8cuxtpq6bwmzw1k

Export your bintray credentials

export BINTRAY_USERNAME=<your_bintray_username>

Export analytics-scdf-sink version from your analytics-scdf-sink pom file. Something like 1.1.4

export ANALYTICS_SCDF_SINK_VERSION=<your_version>

Resolve data flow shell commands.

echo "app register --name analytics-scdf-sink --type sink --uri maven://io.pivotal.analytics:analytics-scdf-sink:$ANALYTICS_SCDF_SINK_VERSION"

Copy the output and put in a scratch pad for use later.

echo "stream create --name trader --definition \"jdbc --query='select * from orders where tag is NULL' --update='update orders set tag=''1'' where orderid in (:orderid)' --password=$DB_PASSWORD --username=$DB_USERNAME --url='jdbc:mysql://$DB_HOST:3306/service_instance_db' --spring.datasource.driver-class-name=org.mariadb.jdbc.Driver | analytics-scdf-sink --es-sink.cluster-name=elasticsearch --es-sink.host=$ES_HOST --es-sink.port=$ES_PORT\""

Copy the output and put in a scratch pad for use later.

echo "cf create-service p-dataflow standard data-flow -c '{\"maven.remote-repositories.repo1.url\": \"https://dl.bintray.com/$BINTRAY_USERNAME/maven-repo\"}'"

Copy the output and put in a scratch pad for use later.

  1. Setup SCDF

Use the resolved cf create-service command from above

This step may take several minutes. Use watch cf services to monitor the status of the creation

  1. Access the dataflow shell
cf dataflow-shell data-flow
  1. Import the starters
app import http://bit.ly/Darwin-SR1-stream-applications-rabbit-maven
  1. Register the analytics-scdf-sink

Use the resolved app register command from above

Test out that the registration was successful.

app info sink:analytics-scdf-sink
  1. Create the trader stream

Use the resolved stream create command from above

  1. Deploy stream
stream deploy trader

  1. Run your test Make a trade, then view the analytics

  2. Un-deploy and un-register SCDF

Within the dataflow shell

stream undeploy trader
stream destroy trader
  1. Tear Down elasticsearch
kubectl delete -f es-statefulset.yaml
kubectl delete -f es-svc.yaml

Demo Time

Now with the above in place you are ready for the demo. The following is a shortened version that already assumes that you have

  • Created the SCDF service
  • analytics-scdf-sink is already deployed to bintray
  • starter apps are already registered in data-flow service
  • analytics-scdf-sink is already registered in data-flow service
  • analytics-service is already deployed
  • es user-provided service already created
  • vsphere storage class already exists in cluster
  • Following environment variables are already setup
    • DB_HOST
    • DB_USERNAME
    • DB_PASSWORD
    • BINTRAY_USERNAME
    • ANALYTICS_SCDF_SINK_VERSION

Assumes you have already logged in to pks and cf via the command line and pivotal-bank is already deployed

  1. Setup elasticsearch (must be 5.6.4)

Create elasticsearch cluster

kubectl config set-context my-cluster --namespace=es-demo
kubectl apply -f es-statefulset.yaml
kubectl apply -f es-svc.yaml
  1. Get service details
kubectl get nodes -o wide
kubectl get svc

If your PKS instance is not setup with NSX-T you will need to use the NodePort to access the service.

export ES_HOST=$(kubectl get node  -o 'jsonpath={.items[0].status.addresses[0].address}')
export ES_PORT=$(kubectl get svc elasticsearch -o 'jsonpath={.spec.ports[?(@.port==9300)].nodePort}')
export ES_HTTP_PORT=$(kubectl get svc elasticsearch -o 'jsonpath={.spec.ports[?(@.port==9200)].nodePort}')

Otherwise, the LoadBalancer service should be given and external ip and you can follow these commands.

export ES_HOST=$(kubectl get svc elasticsearch -o 'jsonpath={.status.loadBalancer.ingress[0].ip}')
export ES_PORT=9300
export ES_HTTP_PORT=9200
  1. Test elasticsearch cluster
http $ES_HOST:$ES_HTTP_PORT
http POST $ES_HOST:$ES_HTTP_PORT/trader/trades symbol=PVTL
http $ES_HOST:$ES_HTTP_PORT/trader/_search
  1. Update CUPS for use by analytics-service
cf update-user-provided-service es -p "'{\"cluster-name\":\"elasticsearch\",\"host\":\"$ES_HOST\",\"port\":\"$ES_PORT\"}'"
  1. Restage the analytics-service

You need to pass in the elasticsearch host and port or the tests will fail.

cf restage analytics
  1. SCDF Command Prep

Copy the output and put in a scratch pad for use later.

echo "stream create --name trader --definition \"jdbc --query='select * from orders where tag is NULL' --update='update orders set tag=''1'' where orderid in (:orderid)' --password=$DB_PASSWORD --username=$DB_USERNAME --url='jdbc:mysql://$DB_HOST:3306/service_instance_db' --spring.datasource.driver-class-name=org.mariadb.jdbc.Driver | analytics-scdf-sink --es-sink.cluster-name=elasticsearch --es-sink.host=$ES_HOST --es-sink.port=$ES_PORT\""
  1. Access the dataflow shell
cf dataflow-shell data-flow
  1. Create the trader stream

Use the resolved stream create command from above

  1. Deploy stream
stream deploy trader
  1. Run your test Make a trade, then view the analytics

Demo Soft Clean Up so It can be Re-run

  1. Un-deploy and un-register SCDF

Within the dataflow shell

stream undeploy trader
stream destroy trader
  1. Tear Down elasticsearch
kubectl delete -f es-statefulset.yaml
kubectl delete -f es-svc.yaml