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.
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
The following procedures assumes that all of the OS-level configuration has been completed. They are:
- AWS Command Line Interface
- Node.js 12.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 v12.x.
Clone the aws-data-lake-solution GitHub repository:
git clone https://github.com/awslabs/aws-data-lake-solution.git
export AWS_REGION=<aws-region-code>
export SOLUTION_NAME=<your-solution-name>
export VERSION_CODE=<version-code>
export DEPLOY_BUCKET=<source-bucket-base-name>
export CLOUDFORMATION_TEMPLATE_BUCKET=<cloudformation-template-bucket-name>
- aws-region-code: AWS region code. e.g.:
us-east-1,us-west-2... - your-solution-name: Your customized solution name. e.g.
aws-data-lake-solution - version-code: Version of the package. e.g.
v1.0.0 - 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 aws-data-lake-solution v2.0.0 solutions, the template will then expect the source code to be located in thesolutions-[aws-region-code]bucket. - cloudformation-template-bucket-name: Name for the S3 bucket where the CloudFormation templates are going to be.
cd ./aws-data-lake-solution/deployment
chmod +x run-unit-tests.sh
./run-unit-tests.sh
chmod +x build-s3-dist.sh
./build-s3-dist.sh $DEPLOY_BUCKET $SOLUTION_NAME $VERSION_CODE $CLOUDFORMATION_TEMPLATE_BUCKET
aws s3 cp ./global-s3-assets s3://$CLOUDFORMATION_TEMPLATE_BUCKET/$SOLUTION_NAME/$VERSION_CODE --recursive --acl bucket-owner-full-control
aws s3 cp ./regional-s3-assets s3://$DEPLOY_BUCKET-$AWS_REGION/$SOLUTION_NAME/$VERSION_CODE --recursive --acl bucket-owner-full-control
- 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 ]
This solution collects anonymous operational metrics to help AWS improve the quality and features of the solution. For more information, including how to disable this capability, please see the implementation guide.
Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.