Data Lake Solution

Many Amazon Web Services (AWS) customers require a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an increasingly popular way to store and analyze data because it allows businesses to store all of their data, structured and unstructured, in a centralized repository. The AWS Cloud provides many of the building blocks required to help businesses implement a secure, flexible, and cost-effective data lake.

The data lake solution is an automated reference implementation that deploys a highly available, cost-effective data lake architecture on the AWS Cloud. The solution is intended to address common customer pain points around conceptualizing data lake architectures, and automatically configures the core AWS services necessary to easily tag, search, share, and govern specific subsets of data across a business or with other external businesses. This solution allows users to catalog new datasets, and to create data profiles for existing datasets in Amazon Simple Storage Service (Amazon S3) and integrate with integrate with solutions like AWS Glue and Amazon Athena with minimal effort.

For the full solution overview visit Data Lake on AWS.

For help when using the data lake solution, visit the online help guide.

File Structure

The data lake project consists of microservices that facilitate the functional areas of the solution. These microservices are deployed to a serverless environment in AWS Lambda.

|-deployment/ [folder containing templates and build scripts]
|-source/
  |-api/
    |-authorizer/ [custom authorizer for api gateway]
    |-services/
      |-admin/ [microservice for data lake administrative functionality]
      |-cart/ [microservice for data lake cart functionality]
      |-logging/ [microservice for data lake audit logging]
      |-manifest/ [microservice for data lake manifest processing]
      |-package/ [microservice for data lake package functionality]
      |-profile/ [microservice for data lake user profile functionality]
      |-search/ [microservice for data lake search functionality]
  |-cli/ [data lake command line interface]
  |-console/ [data lake angularjs management console]
  |-resource/
    |-access-validator/ [auxiliar module used to validate granular permissions]
    |-helper/ [custom helper for CloudFormation deployment template]

Each microservice follows the structure of:

|-service-name/
  |-lib/
    |-[service module libraries and unit tests]
  |-index.js [injection point for microservice]
  |-package.json

Getting Started

01. Prerequisites

The following procedures assumes that all of the OS-level configuration has been completed. They are:

• AWS Command Line Interface
• Node.js 8.x

The data lake solution is developed with Node.js for the microservices that run in AWS Lambda and Angular 1.x for the console user interface. The latest version of the data lake solution has been tested with Node.js v8.10.

02. Build the data lake solution

Clone the aws-data-lake-solution GitHub repository:

git clone https://github.com/mariandumitrascu/aws-data-lake-solution.git

03. Declare enviroment variables:

export AWS_REGION=<aws-region-code>
export VERSION_CODE=<version-code>
export DEPLOY_BUCKET=<source-bucket-base-name>

• aws-region-code: AWS region code. Ex: us-east-1, us-west-2 ...
• version-code: version of the package
• source-bucket-base-name: Name for the S3 bucket location where the template will source the Lambda code from. The template will append -[aws-region-code] to this bucket name. For example: ./build-s3-dist.sh solutions v2.0.0, the template will then expect the source code to be located in the solutions-[aws-region-code] bucket.

You need to create this bucket manually: $DEPLOY_BUCKET-$AWS_REGION

04. Run the data lake solution unit tests:

cd ./aws-data-lake-solution/deployment
chmod +x run-unit-tests.sh
./run-unit-tests.sh

05. Build the data lake solution for deployment://$

chmod +x build.sh
./build.sh

06. Upload deployment assets to your Amazon S3 bucket:

*aws s3 cp ./dist s3://$DEPLOY_BUCKET/data-lake/latest --recursive --acl bucket-owner-full-control*

Correct syntax to upload to correct bucket is this:

aws s3 cp ./dist s3://$DEPLOY_BUCKET-$AWS_REGION/data-lake/$VERSION_CODE --recursive --acl bucket-owner-full-control

or execute

./upload-s3.sh

07. Deploy the data lake solution:

• From your designated Amazon S3 bucket where you uploaded the deployment assets, copy the link location for the data-lake-deploy.template or data-lake-deploy-federated.template.
• Using AWS CloudFormation, launch the data lake solution stack using the copied Amazon S3 link for the data-lake-deploy.template or data-lake-deploy-federated.template.

Currently, the data lake solution can be deployed in the following regions: [ us-east-1, us-east-2, us-west-2, eu-west-1, eu-west-2, eu-central-1, ap-northeast-1, ap-northeast-2, ap-southeast-2, ap-south-1 ]

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Licensed under the Amazon Software License (the "License"). You may not use this file except in compliance with the License. A copy of the License is located at

http://aws.amazon.com/asl/

or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, express or implied. See the License for the specific language governing permissions and limitations under the License.