Overview
DataLake is a software component of ONAP that can systematically persist the events in DMaaP into supported Big Data storage systems. It has a Admin UI, where a system administrator configures which Topics to be monitored, and to which data storage to store the data. It is also used to manage the settings of the storage and associated data analytics tool. The second part is the Feeder, which does the data transfer work and is horizontal scalable. In the next release, R7, we will add the third component, Data Exposure Service (EDS), which will expose the data in the data storage via REST API for other ONAP components and external systems to consume. Each data exposure only requires simple configurations.
Architecture Diagram
Data Exposure Service will be available in R7.
Artefacts
Βlueprint (deployment artifact) : k8s-datalake-feeder.yaml, k8s-datalake-admin-ui.yaml
Docker image
Deployment Prerequisite/dependencies
Since datalake can log the message from the DMaap to several different external databases, such as Elasticsearch, Couch Base, MongoDB, Relational databases...etc. Once Datalake is successfully deployed, you can start to deploy the external databases and configure the sink databases through our admin UI. The following sections will guide you to deploy datalake microservice, including cloudify blueprint upload, deployment, and un-deployment.
Deployment Steps
DL-handler consists of two pods- the feeder and admin UI. It can be deployed by using cloudify blueprint. Datalake can be easily deployed through DCAE cloudify manager. The following steps guides you launch Datalake though cloudify manager.
Log-in to the DCAE bootstrap POD's main container
Login to the DCAE bootstrap pod through the following command.
kubectl exec -it <DCAE bootstrap pod> /bin/bash -n onap
Validate blueprint
cfy blueprints validate /blueprints/k8s-dl-handler.yaml
Upload the blueprint to cloudify manager.
cfy blueprint upload -b datalake-feeder /bluerints/k8s-datalake-feeder.yaml cfy blueprint upload -b datalake-admin-ui /blueprints/k8s-datalake-admin-ui.yaml
Verify Blueprint Upload
cfy blueprint list
You can see the following returned message to show the blueprints have been correctly uploaded.
Verify Plugin versions in target Cloudify instance match to blueprint imports
If the version of the plugin used is different, update the blueprint import to match.
cfy plugins list
Create Deployment
Here we are going to create deployments for both feeder and admin UI.
cfy deployments create -b datalake-feeder feeder-deploy cfy deployments create -b datalake-admin-ui admin-ui-deploy
Launch Service
Next, we are going to launch the datalake.
cfy executions start -d feeder-deploy install cfy executions start -d admin-ui-deploy install
To Un-deploy
Uninstall running component and delete deployment
cfy uninstall feeder-deploy cfy uninstall admin-ui-deploy
Delete blueprint
cfy blueprints delete datalake-feeder cfy blueprints deltet datalake-admin-ui