The document discusses best practices for migrating databases to AWS using AWS Database Migration Service (DMS) and AWS Schema Conversion Tool (SCT). It describes how the traditional approach to database migration involved complex steps like shutting down the database, replicating data, and long application downtimes. AWS DMS and SCT enable automated migration between on-premises and AWS databases with zero downtime and automated schema conversion. The document provides an overview of AWS database services, the database migration process, features of DMS and SCT, lessons learned, examples, and best practices for using DMS.

1. S U M M I T
SYDNEY

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Best practices for migrating
databases to the cloud
Masudur Rahaman Sayem
Solutions Architect
Amazon Web Services

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AWS database portfolio
Amazon RDS
MySQL, PostgreSQL, MariaDB, Oracle,
SQL Server
Amazon Aurora
MySQL, PostgreSQL
Amazon DynamoDB
Key value
Amazon ElastiCache
Redis, Memcached
Amazon Neptune
Graph
Amazon Timestream
Time Series
Amazon QLDB
Ledger Database
Amazon RDS on VMware
N E W
N E W
Amazon DocumentDB
Document
N E W

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Traditional migration approach
Required DB-specific
application code
1001001
0101001
1000100
Was complex to set
up and manage
Required commercial
migration and
replication software
Caused long application
downtime

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Traditional approach to migrate to AWS
Create your AWS account
Setup your Virtual Private Cloud (VPC) in AWS
Connect to AWS with a VPN or Direct Connect
Shutdown and backup your database
Transmit the backup to S3
Configure an EC2 instance with the DB software
Restore the backup
Configure EC2 instances for the application
Switch the users to use AWS

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Create your AWS account
Setup your Virtual Private Cloud (VPC) in AWS
Connect to AWS with a VPN or Direct Connect
Shutdown and backup your database
Transmit the backup to S3
Configure an EC2 instance with the DB software
Restore the backup
Configure EC2 instances for the application
Switch the users to use AWS
Traditional approach to migrate to AWS
Could take a week or more!

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AWS DMS and AWS SCT
AWS Database Migration Service (DMS)
Easy and secure cloud database migration
AWS Schema Conversion Tool (SCT)
Automate database schema and code
conversion
Migrate between on
premises and AWS
Automated schema conversion
Data replication for zero
downtime migration
>100,000 Databases migrated with DMS
Migrate between databases

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Database migration process

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AWS Schema onversion ool (SCT)

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AWS Schema Conversion Tool (SCT)
Features
Modernise database schema
warehouse schema
application SQL
Code browser
Secure
ETL

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AWS SCT data extractors
Extract data from your data warehouse and migrate to Amazon Redshift
Extracts data through local migration agents
Data is optimised for Redshift and saved in local files
Files are loaded to an Amazon S3 bucket (through network or
Amazon Snowball) and then to Amazon Redshift
AWS SCT Amazon S3

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AWS SCT can tell you how hard the migration will be
Connect SCT to Source
and Target databases
Run Assessment Report
Read Executive Summary
Follow detailed
instructions

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AWS SCT helps with converting tables, views, and
code

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AWS SCT lessons learned
Memory management
Large database schema conversion
DB agnostic code
Data type conversion
Migrating large
databases

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Oracle RAC to PostgreSQL replication
Replicate Oracle RAC to RDS for PostgreSQL
Replicate PostgreSQL to Amazon Redshift
• Higher performance without the Oracle cost
• Ability to split the data and keep master tables in sync
• Use SCT to begin the modernisation journey
“Amazon DMS is a great product. From looking at the product to getting it in production takes no time at all. It’s simple
to use and reliable. The flexibility of creating new tasks is not very time consuming and just works.”

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AWS Database Migration Service (DMS)
features and best practices

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Customer
premise
Application users
AWS
Internet
VPN
Keep your apps running during the migration
Start a replication instance
Connect to source and target
databases
Select tables, schemas, or databases
Let AWS DMS create tables, load
data, and keep them in sync
Switch applications over to the
target at your convenience
AWS DMS

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AWS DMS features
Migrate table by table Source
Amazon Aurora
(MySQL, PostgreSQL)
Amazon DynamoDB
Amazon Redshift
Amazon RDS
Amazon S3
Customers don’t have to take everything
Change Data Capture (CDC)
Multiple targets, multiple sources
Homogenous or heterogeneous

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Split migration
35 million members on its site
Migration from legacy cloud service to AWS
Combination of migration to MySQL on EC2 and
Amazon Aurora
DMS reduced the time required to migrate their
databases by 40 percent
Realised 55 percent cost savings by moving some
DBs to Amazon Aurora

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DMS Kinesis Target
Amazon Kinesis
Data Stream
Amazon EMR
Spark
Amazon Kinesis
Data Stream
Stream data change to Amazon Kinesis
Amazon
DynamoDB
Amazon RDS
MySQL, PostgreSQL,
MariaDB, Oracle, SQL
Server
DB2 LUW
Amazon DynamoDB
Amazon Redshift
Amazon QuickSight
Amazon CloudSearch
Amazon Athena
Amazon S3
Amazon Kinesis Firehose Amazon Kinesis Firehose
Amazon S3 Bucket Amazon S3 Bucket

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Best practices using AWS DMS
Parallel load (large table)
Check indexes, triggers and referential integrity constraints
Disable backups and transaction logging
Use standby source
Improve performance

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Best practices using AWS DMS
Correct sizing your replication instance
Monitor source DB load
Troubleshoot using task log
Reconsider storing LOB on DB
Dry runs
Things to consider

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Recap
Assessment
Schema
Migration
Data
Migration
App
Migration
Data
Validation
Functional
Testing
Performance
Testing
AWS SCT AWS DMS Amazon Marketplace tool

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The SQL 2008 end of support countdown is on
9 July 2019
SQL Server 2008 and 2008 R2 end of support
We are ready!
to help customers
Step beyond SQL ’08

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Next steps
• Ask us about funding for POCs and commercial DB migrations
(eg Oracle Database to Aurora)
• https://aws.amazon.com/solutions/databasemigrations/database-freedom/
• DMS & SCT: https://aws.amazon.com/dms/
• Getting Started Guides and Playbooks:
https://aws.amazon.com/dms/getting-started/
• Free DMS: https://aws.amazon.com/dms/free-dms/

27. Thank you!
S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Masudur Rahaman Sayem
masudurs@amazon.com