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1. Enable thrift stats publishing with the DAS_HOSTNAME and DAS_TCP_PORT values in the thrift-client-config.xml file, which is in the <PRIVATE_PAAS_HOME>/repository/conf directory. If needed, you can set multiple DAS nodes for a High Availability (HA) setup.

   Code Block

   <!-- Apache thrift client configuration for publishing statistics to WSO2 CEP and WSO2 DAS--> <thriftClientConfiguration> . . . <das> <node id="node-01"> <statsPublisherEnabled>false</statsPublisherEnabled> <username>admin</username> <password>admin</password> <ip>[DAS_HOSTNAME]</ip> <port>[DAS_TCP_PORT]</port> </node> <!--<node id="node-02"> <statsPublisherEnabled>true</statsPublisherEnabled> <username>admin</username> <password>admin</password> <ip>localhost</ip> <port>7613</port> </node>--> </das> </config> </thriftClientConfiguration>

2. Configure the Private PaaS metering dashboard URL with the DAS_HOSTNAME and DAS_PORTAL_PORT values in the <PRIVATE_PAAS_HOME>/repository/conf/cartridge-config.properties file as follows:
   

   Code Block
   das.metering.dashboard.url=https://<DAS_HOSTNAME>:<DAS_PORTAL_PORT>/portal/dashboards/ppaas-metering-dashboard

    

3. Configure the PPaaS monitoring dashboard URL .
   To configure the DAS monitoring dashboard, add the following configuration in the with the DAS_HOSTNAME and DAS_PORTAL_PORT values in the <PRIVATE_PAAS_HOME>/repository/deployment/server/jaggeryapps/console/controllers/menu/menu.json file, after the applications menu. Configure monitoring dashboard URL by adding the DAS_HOSTNAME and DAS_PORTAL_PORT values in the link property. 

   Code Block{ "link": "https://<DAS_HOSTNAME>:<DAS_PORTAL_PORT>/portal/dashboards/ppaas-monitoring-dashboard", "linkexternal": true, "context": "/", "title": "Monitoring", "icon": "fa-laptop", "block-color":"#f1c40f", "permissionPaths": [ "/permission", "/permission/admin" ], "description": "Monitor health statistics of clusters and members." },

   conf/cartridge-config.properties file as follows:

   Code Block
   das.monitoring.dashboard.url=https://<DAS_HOSTNAME>:<DAS_PORTAL_PORT>/portal/dashboards/monitoring-dashboard

Step 2 - Configure DAS

1. Create the ANALYTICS_FS_DB, ANALYTICS_EVENT_STORE and ANALYTICS_PROCESSED_STORE databases in MySQL using the following MySQL scripts:

   Code Block
   CREATE DATABASE ANALYTICS_FS_DB; CREATE DATABASE ANALYTICS_EVENT_STORE; CREATE DATABASE ANALYTICS_PROCESSED_DATA_STORE;

2. Configure DAS analytics-datasources.xml file, which is in the <DAS_HOME>/repository/conf/datasources directory, as follows to create the ANALYTICS_FS_DB, ANALYTICS_EVENT_STORE and ANALYTICS_PROCESSED_STORE datasources.

   Code Block

   <datasources-configuration> <providers> <provider>org.wso2.carbon.ndatasource.rdbms.RDBMSDataSourceReader</provider> </providers> <datasources> <datasource> <name>WSO2_ANALYTICS_FS_DB</name> <description>The datasource used for analytics file system</description> <definition type="RDBMS"> <configuration> <url>jdbc:mysql://127.0.0.1:3306/ANALYTICS_FS_DB</url> <username>root</username> <password>root</password> <driverClassName>com.mysql.jdbc.Driver</driverClassName> <maxActive>50</maxActive> <maxWait>60000</maxWait> <testOnBorrow>true</testOnBorrow> <validationQuery>SELECT 1</validationQuery> <validationInterval>30000</validationInterval> <defaultAutoCommit>false</defaultAutoCommit> </configuration> </definition> </datasource> <datasource> <name>WSO2_ANALYTICS_EVENT_STORE_DB</name> <description>The datasource used for analytics record store</description> <definition type="RDBMS"> <configuration> <url>jdbc:mysql://127.0.0.1:3306/ANALYTICS_EVENT_STORE</url> <username>root</username> <password>root</password> <driverClassName>com.mysql.jdbc.Driver</driverClassName> <maxActive>50</maxActive> <maxWait>60000</maxWait> <testOnBorrow>true</testOnBorrow> <validationQuery>SELECT 1</validationQuery> <validationInterval>30000</validationInterval> <defaultAutoCommit>false</defaultAutoCommit> </configuration> </definition> </datasource> <datasource> <name>WSO2_ANALYTICS_PROCESSED_DATA_STORE_DB</name> <description>The datasource used for analytics record store</description> <definition type="RDBMS"> <configuration> <url>jdbc:mysql://127.0.0.1:3306/ANALYTICS_PROCESSED_DATA_STORE</url> <username>root</username> <password>root</password> <driverClassName>com.mysql.jdbc.Driver</driverClassName> <maxActive>50</maxActive> <maxWait>60000</maxWait> <testOnBorrow>true</testOnBorrow> <validationQuery>SELECT 1</validationQuery> <validationInterval>30000</validationInterval> <defaultAutoCommit>false</defaultAutoCommit> </configuration> </definition> </datasource> </datasources> </datasources-configuration>

3. Set the analytics datasources created in above step (WSO2_ANALYTICS_FS_DB, WSO2_ANALYTICS_EVENT_STORE_DB and WSO2_ANALYTICS_PROCESSED_STORE_DB) in the DAS analytics-config.xml file, which is in the <DAS_HOME>/repository/conf/analytics directory.
   

   Code Block

   <analytics-dataservice-configuration> <!-- The name of the primary record store --> <primaryRecordStore>EVENT_STORE</primaryRecordStore> <!-- The name of the index staging record store --> <indexStagingRecordStore>INDEX_STAGING_STORE</indexStagingRecordStore> <!-- Analytics File System - properties related to index storage implementation --> <analytics-file-system> <implementation>org.wso2.carbon.analytics.datasource.rdbms.RDBMSAnalyticsFileSystem</implementation> <properties> <!-- the data source name mentioned in data sources configuration --> <property name="datasource">WSO2_ANALYTICS_FS_DB</property> <property name="category">large_dataset_optimized</property> </properties> </analytics-file-system> <!-- Analytics Record Store - properties related to record storage implementation --> <analytics-record-store name="EVENT_STORE"> <implementation>org.wso2.carbon.analytics.datasource.rdbms.RDBMSAnalyticsRecordStore</implementation> <properties> <property name="datasource">WSO2_ANALYTICS_EVENT_STORE_DB</property> <property name="category">large_dataset_optimized</property> </properties> </analytics-record-store> <analytics-record-store name="INDEX_STAGING_STORE"> <implementation>org.wso2.carbon.analytics.datasource.rdbms.RDBMSAnalyticsRecordStore</implementation> <properties> <property name="datasource">WSO2_ANALYTICS_EVENT_STORE_DB</property> <property name="category">limited_dataset_optimized</property> </properties> </analytics-record-store> <analytics-record-store name = "PROCESSED_DATA_STORE"> <implementation>org.wso2.carbon.analytics.datasource.rdbms.RDBMSAnalyticsRecordStore</implementation> <properties> <property name="datasource">WSO2_ANALYTICS_PROCESSED_DATA_STORE_DB</property> <property name="category">large_dataset_optimized</property> </properties> </analytics-record-store> <!-- The data indexing analyzer implementation --> <analytics-lucene-analyzer> <implementation>org.apache.lucene.analysis.standard.StandardAnalyzer</implementation> </analytics-lucene-analyzer> <!-- The maximum number of threads used for indexing per node, -1 signals to aute detect the optimum value, where it would be equal to (number of CPU cores in the system - 1) --> <indexingThreadCount>-1</indexingThreadCount> <!-- The number of index shards, should be equal or higher to the number of indexing nodes that is going to be working, ideal count being 'number of indexing nodes * [CPU cores used for indexing per node]' --> <shardCount>6</shardCount> <!-- Data purging related configuration --> <analytics-data-purging> <!-- Below entry will indicate purging is enable or not. If user wants to enable data purging for cluster then this property need to be enable in all nodes --> <purging-enable>false</purging-enable> <cron-expression>0 0 0 * * ?</cron-expression> <!-- Tables that need include to purging. Use regex expression to specify the table name that need include to purging.--> <purge-include-tables> <table>.*</table> <!--<table>.*jmx.*</table>--> </purge-include-tables> <!-- All records that insert before the specified retention time will be eligible to purge --> <data-retention-days>365</data-retention-days> </analytics-data-purging> <!-- Receiver/Indexing flow-control configuration --> <analytics-receiver-indexing-flow-control enabled = "true"> <!-- maximum number of records that can be in index staging area before receiving is throttled --> <recordReceivingHighThreshold>10000</recordReceivingHighThreshold> <!-- the limit on number of records to be lower than, to reduce throttling --> <recordReceivingLowThreshold>5000</recordReceivingLowThreshold> </analytics-receiver-indexing-flow-control> </analytics-dataservice-configuration>

4. Add the MySQL Java connector 5.1.x JAR file, which is supported by MYSQL 5.6, in the <DAS_HOME>/repository/components/lib directory.

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Step 2.2 - Create PPaaS Metering Dashboard with DAS

1. Add the org.

   wso2

   apache.

   ppaas

   stratos.das.extension-

   <PPAAS_VERSION>

   4.1.5.jar file, which is in the <PPAAS_DAS_DISTRIBUTION>/lib directory, into the <DAS_HOME>/repository/components/lib directory.

2. Add the following Java class path into the spark-udf-config.xml file in the <DAS_HOME>/repository/conf/analytics/spark directory.

   Code Block
   <class-name>org.wso2apache.ppaasstratos.das.extension.TimeUDF</class-name>

3. Add Jaggery files, which are in the <PPAAS_DAS_DISTRIBUTION>/metering-dashboard/jaggery-files directory into the <DAS_HOME>/repository/deployment/server/jaggeryapps/portal/controllers/apis directory.

4. Manually create MySQL databases and tables using the queries, which are in the <PPAAS_DAS_DISTRIBUTION>/metering-dashboard/metering-mysqlscript.sql file. 
   

   Code Block

   CREATE DATABASE IF NOT EXISTS ANALYTICS_FS_DB; CREATE DATABASE IF NOT EXISTS ANALYTICS_EVENT_STORE; CREATE DATABASE IF NOT EXISTS ANALYTICS_PROCESSED_DATA_STORE; CREATE TABLE ANALYTICS_PROCESSED_DATA_STORE.MEMBER_STATUS(Time long, ApplicationId VARCHAR(150), ClusterAlias VARCHAR(150), MemberId VARCHAR(150), MemberStatus VARCHAR(50)); CREATE TABLE ANALYTICS_PROCESSED_DATA_STORE.MEMBER_COUNT(Time long, ApplicationId VARCHAR(150), ClusterAlias VARCHAR(150), CreatedInstanceCount int, InitializedInstanceCount int, ActiveInstanceCount int, TerminatedInstanceCount int); CREATE TABLE ANALYTICS_PROCESSED_DATA_STORE.MEMBER_INFORMATION(MemberId VARCHAR(150), InstanceType VARCHAR(150), ImageId VARCHAR(150), HostName VARCHAR(150), PrivateIPAddresses VARCHAR(150), PublicIPAddresses VARCHAR(150), Hypervisor VARCHAR(150), CPU VARCHAR(10) , RAM VARCHAR(10), OSName VARCHAR(150), OSVersion VARCHAR(150));

5. Apply a WSO2 User Engagement Server (UES) patch to the DAS dashboard.
   You need to do this to populate the metering dashboard.

   1. Copy the ues-dashboardgadgets.jsjs and the ues-pubsub.js files from the <PPAAS_DAS_DISTRIBUTION>/metering-dashboard/ues-patch directory into the <DAS_HOME>/repository/deployment/server/jaggeryapps/portal/js directory.

   2. Copy the dashboard.jag file from the <PPAAS_DAS_DISTRIBUTION>/metering-dashboard/ues-patch directory into the <DAS_HOME>/repository/deployment/server/jaggeryapps/portal/theme/templates directory.

6. Add the ppaas-metering-service.car file, which is in the <PPAAS_DAS_DISTRIBUTION>/metering-dashboard directory, into the <DAS_HOME>/repository/deployment/server/carbonapps directory to generate the metering dashboard.

   Note
   If the <DAS_HOME>/repository/deployment/server/carbonapps folder does not exist, initially create the folder before moving the CAR file.

   You can navigate to the metering dashboard from the Private PaaS application topology view at the application or cluster level as shown below.
   
   
   The following is a sample metering dashboard:
   

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