Build multi region data warehouse on AWS - AWSVNUG
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The solution for building the Data Warehouse on AWS with the scalable-data across AWS regions. The benefits of this solution: it enables users to access, analyze and visualize any data to get the insight faster in order to make better decisions for the business. The solution is secure, scalable, comprehensive, and cost-effective.
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Build multi region data warehouse on AWS - AWSVNUG
- 1. Build multi-region Data Warehouse on AWS Mr. Vuong Tran Cloud Solution Architect OSAM #1 Mr. Thai Ngo Cloud Solution Architect OSAM AWS User Group Vietnam
- 3. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT Agenda 1. What is Data Warehouse? 2. Benefit of using AWS for Data Warehousing 3. Why Multi-region Data Warehouse? 4. AWS Architecture
- 4. What is the Data Warehouse?
- 5. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT What is the Data Warehouse • DWs are central repositories of integrated data from one or more disparate sources so it can be compared and analyzed for greater business intelligence. • DWs is known as a blend of technologies and components which allows the strategic use of data.
- 6. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT Data Warehouse using for? • Reporting • Data Analysis • Core component of business intelligence
- 7. Benefits of using AWS for Data Warehouse
- 8. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Global Infrastructure 19 regions in the world Expanding more and more: Bahrain, Cape Town, Hong Kong SAR and Milan
- 9. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT What are the main components of data warehouse on AWS?
- 10. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT Benefits of using AWS for Data Warehouse • Better decision making • Consolidates data from many sources • Data quality, consistency, and accuracy • Historical intelligence • Separates analytics processing from transactional databases, improving performance of both systems
- 11. Why Multi-region Data Warehouse ?
- 12. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT Global business
- 13. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Data Location ● Stores in different regions ● Different networks
- 14. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT Data Process Be processed separately in different ways in different regions
- 15. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT Data Aggregation Be aggregated across regions for data mining and business analytic
- 16. AWS Architecture
- 17. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT From the beginning Single Region
- 18. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS Redshift Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers
- 19. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT Amazon RedShift • Scale from 160GB to 2PB online • Automatic streaming backup/restore to S3 • Automatic failover and recovery • ANSI SQL interface • Load data from S3, DynamoDB and EMR
- 20. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS Glue Automatically discover and categorize your data making it immediately searchable and queryable across data sources Generate code to clean, enrich, and reliably move data between various data sources; you can also use their favorite tools to build ETL jobs Run your jobs on a serverless, fully managed, scale-out environment. No compute resources to provision or manage. Discovery Develop Deploy
- 21. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS S3 Secure, durable, highly-scalable object storage Accessible via a simple web services interface Store & retrieve any amount of data Integrate with many AWS services
- 22. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon S3 Backup & Archiving Content Storage & Distribution Big Data Analytics Static Website Hosting Cloud-native Application Data Disaster Recovery
- 23. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT Then expanding
- 24. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Multi Regions Architecture - Route 53: Geolocation Routing - DW Redshift separately - Glue jobs differences between regions - Data is placed separately among regions
- 25. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT Multi Regions Architecture What about the Data from other regions? How can we manage and access data from other regions in secure way?
- 26. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT We can do like this Rely on BI tools features - Support multiple sources - Support aggregation from multiple sources Challenge - Latency from sources - Customize data from other regions
- 27. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.SUMMIT Or like this Glue - Send data to multiple DW endpoints per job Challenge - Managed glue jobs across region - Complex private networks with VPC peering when using Glue in VPC
- 28. Better solution
- 29. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Architecture Diagram
- 30. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Pros - Replicate by AWS - Choose partial data to replicate by S3 prefix - Simplify the replication configure multi regions by using Cloud Formation S3 with cross-regions replication
- 31. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Pros - Maximize the ability to process and mine data from other regions - Focus only processing data, not sending data to many endpoints
- 32. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Pros - No complex network, no VPCs peering - Isolate ETL process between regions, different teams
- 33. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Pros - Data is prepared completely on each Redshift per region - Reduce latency from BI tools to Redshift
- 34. SUMMIT © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Cons Redundant data - Replicate only what we need - Apply S3 object life cycle - Leverage Lambda to clean up Redshift data
- 35. NGO QUOC THAI Cloud Solution Architect OSAM TRAN LE VUONG Cloud Solution Architect OSAM Thank you