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AWS DMS
Database Migration Service
Objective(s)
 Have a ready-made solution available for Database Migrations
from OnPrem to OnPrem and Cloud; also from Cloud to Cloud and
OnPrem.
 Use the industry leading tools for this solution using the open-
source and have a ready PoC available to take it to multiple client
Deluxe Support.
 Share the information to the sales team to check for the business
opportunity with existing and new clients.
 Enable the technical team of the client with the available solution
to use it effectively to provide the value to the client.
 Provide the opportunity for SMEs to come up with the such
solutions to enhance the technical capabilities within.
Industry
Challenges
 Migrating DB can be a complex process, and it's important to plan
and prepare for potential challenges to ensure a smooth
migration.
 Working with experienced migration experts, using the right tools,
and testing thoroughly can help minimize the risks and ensure a
successful migration.
 Downtime
 Data integrity
 Application compatibility
 Security
 Data loss
Demo
Automation of DB Migration using AWS DMS usingTerraform
Terraform Script
triggered
Source & Target
validation
Source Database
backup
Create Relevant
Security Aspects
Map, Conversion,
Transformation
Test Functionality,
initiate migration
Monitor Migration
and complete it.
Verify Migrated data
Update Config to
Target
Migration Flow
AWS DMS
(Database Migration Service)
 AWS DMS, a managed migration and replication service that helps move
database and analytics workloads to AWS quickly, securely, and with
minimal downtime and zero data loss.
 AWS DMS supports migration between 20-plus DB and analytics engines.
 Discover, assess, convert, and migrate your database and analytics
workloads to AWS with automated migration.
 Maintain high availability and minimal downtime during migration process
with Multi-AZ and ongoing data replication and monitoring.
 Supports homogeneous & heterogeneous database migrations from
Oracle, SQL, Postgres, MySQL, MongoDB, MariaDB, and other DBs.
 Migrate aTB-Sized database at a low cost, paying only for the compute
resources and additional log storage used during migration process.
How it works
Heterogeneous
Homogeneous
Features
1. Simple to use:
2. Minimal downtime:
3. Cost effectiveness:
4. Reliable:
5. On-going replication:
6. Developer productivity:
7. Database Consolidation:
Supported
Source DBs
Source Databases
 Oracle
 MS SQL
 MySQL
 MariaDB
 Postgres
 MongoDB
 SAP Adaptive
 IBM DB2(LUW)
Managed DBs
 Azure SQL DB
 Google Cloud MySQL
 AWS RDS
 Oracle 11G Onwards
 MS SQL 5.5 to 8.0
 MariaDB 10.0.24 to 10.4
 Postgres 10.x to 14.x
 Aurora MySQL
 Aurora PostgreSQL
 AWS S3
 AWS Document DB
Supported
Target DBs
Target DBs
 Oracle
 Microsoft SQL
 MySQL
 MariaDB
 PostgreSQL
 SAP Adaptive Server
 Redis versions 6.x.
Managed DBs
 Amazon Redshift
 DynamoDB
 AWS S3
 DocumentDB
 Neptune
 Oracle versions
 MS SQL Server
 MySQL
 MariaDB
Managed DBs
 PostgreSQL
 Aurora MySQL
 Aurora PostgreSQL
 Aurora Serverless
 OpenSearch Service
 ElastiCache for Redis
 Kinesis Data Streams
 Apache Kafka
 Babelfish
Partial / Limited
Migration
 SAP Adaptive Server toAmazon Redshift:
 MongoDB to Amazon DynamoDB:
 MariaDB to Oracle:
 AWS DocumentDB (MongoDB compatibility) to MongoDB:
 AmazonOpenSearch Service to Elasticsearch:
 Babelfish to Microsoft SQL Server:
Limitations
 Unsupported source or target databases:
 IBM DB2, Sybase, and Informix
 Limited data conversion:
 Functions, and stored procedures
 Replication lag:
 Depending on the workload, network latency, and other factors.
 High network bandwidth requirement:
 Dedicated network connection or use Amazon Direct Connect
 No support for certain features:
 spatial data types, geospatial indexing, and full-text search.
AWSSchema
Conversion
Tool
 Convert your existing DB schema from one DB engine to another.
 Key benefits of leveraging DMS Schema Conversion tool are:
 Simplify database migrations by automating schema analysis,
recommendations, and conversion at scale.
 Compatible with popular DBs and analytics services as source and
target engines, including Oracle, SQL, Postgres, and MySQL.
 Save weeks or months of manual time and resources.
 Free tool
 Download and install on your infrastructure
Terraform for
DMS
 Terraform is a handy IaC tool to think ofAutomation and adopt for
this purpose.
 Idempotent in nature
 Avoid vendor lock-in
 Supports multiple cloud environment
 Define once and use it for multiple clients/iterations
Thank you
For any queries, reach out to
sshettar@msystechnologies.com
sdurai@msystechnologies.com

More Related Content

AWS-DMS-2023.pptx

  • 2. Objective(s)  Have a ready-made solution available for Database Migrations from OnPrem to OnPrem and Cloud; also from Cloud to Cloud and OnPrem.  Use the industry leading tools for this solution using the open- source and have a ready PoC available to take it to multiple client Deluxe Support.  Share the information to the sales team to check for the business opportunity with existing and new clients.  Enable the technical team of the client with the available solution to use it effectively to provide the value to the client.  Provide the opportunity for SMEs to come up with the such solutions to enhance the technical capabilities within.
  • 3. Industry Challenges  Migrating DB can be a complex process, and it's important to plan and prepare for potential challenges to ensure a smooth migration.  Working with experienced migration experts, using the right tools, and testing thoroughly can help minimize the risks and ensure a successful migration.  Downtime  Data integrity  Application compatibility  Security  Data loss
  • 4. Demo Automation of DB Migration using AWS DMS usingTerraform
  • 5. Terraform Script triggered Source & Target validation Source Database backup Create Relevant Security Aspects Map, Conversion, Transformation Test Functionality, initiate migration Monitor Migration and complete it. Verify Migrated data Update Config to Target Migration Flow
  • 6. AWS DMS (Database Migration Service)  AWS DMS, a managed migration and replication service that helps move database and analytics workloads to AWS quickly, securely, and with minimal downtime and zero data loss.  AWS DMS supports migration between 20-plus DB and analytics engines.  Discover, assess, convert, and migrate your database and analytics workloads to AWS with automated migration.  Maintain high availability and minimal downtime during migration process with Multi-AZ and ongoing data replication and monitoring.  Supports homogeneous & heterogeneous database migrations from Oracle, SQL, Postgres, MySQL, MongoDB, MariaDB, and other DBs.  Migrate aTB-Sized database at a low cost, paying only for the compute resources and additional log storage used during migration process.
  • 8. Features 1. Simple to use: 2. Minimal downtime: 3. Cost effectiveness: 4. Reliable: 5. On-going replication: 6. Developer productivity: 7. Database Consolidation:
  • 9. Supported Source DBs Source Databases  Oracle  MS SQL  MySQL  MariaDB  Postgres  MongoDB  SAP Adaptive  IBM DB2(LUW) Managed DBs  Azure SQL DB  Google Cloud MySQL  AWS RDS  Oracle 11G Onwards  MS SQL 5.5 to 8.0  MariaDB 10.0.24 to 10.4  Postgres 10.x to 14.x  Aurora MySQL  Aurora PostgreSQL  AWS S3  AWS Document DB
  • 10. Supported Target DBs Target DBs  Oracle  Microsoft SQL  MySQL  MariaDB  PostgreSQL  SAP Adaptive Server  Redis versions 6.x. Managed DBs  Amazon Redshift  DynamoDB  AWS S3  DocumentDB  Neptune  Oracle versions  MS SQL Server  MySQL  MariaDB Managed DBs  PostgreSQL  Aurora MySQL  Aurora PostgreSQL  Aurora Serverless  OpenSearch Service  ElastiCache for Redis  Kinesis Data Streams  Apache Kafka  Babelfish
  • 11. Partial / Limited Migration  SAP Adaptive Server toAmazon Redshift:  MongoDB to Amazon DynamoDB:  MariaDB to Oracle:  AWS DocumentDB (MongoDB compatibility) to MongoDB:  AmazonOpenSearch Service to Elasticsearch:  Babelfish to Microsoft SQL Server:
  • 12. Limitations  Unsupported source or target databases:  IBM DB2, Sybase, and Informix  Limited data conversion:  Functions, and stored procedures  Replication lag:  Depending on the workload, network latency, and other factors.  High network bandwidth requirement:  Dedicated network connection or use Amazon Direct Connect  No support for certain features:  spatial data types, geospatial indexing, and full-text search.
  • 13. AWSSchema Conversion Tool  Convert your existing DB schema from one DB engine to another.  Key benefits of leveraging DMS Schema Conversion tool are:  Simplify database migrations by automating schema analysis, recommendations, and conversion at scale.  Compatible with popular DBs and analytics services as source and target engines, including Oracle, SQL, Postgres, and MySQL.  Save weeks or months of manual time and resources.  Free tool  Download and install on your infrastructure
  • 14. Terraform for DMS  Terraform is a handy IaC tool to think ofAutomation and adopt for this purpose.  Idempotent in nature  Avoid vendor lock-in  Supports multiple cloud environment  Define once and use it for multiple clients/iterations
  • 15. Thank you For any queries, reach out to sshettar@msystechnologies.com sdurai@msystechnologies.com

Editor's Notes

  1. Pre-Reqs Efforts required Limitations Flow diagram while terraform triggers the DMS, service/resource wise Template Table for possible migrations and challenges Cover version related info if feasible