Best Practices for Using AWS Data Migration Services for Your Cloud Migration

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Following these best practices can ensure a smooth data migration to the cloud

Key Takeaways:

  • Data migration is the most important element in a cloud-based digital transformation
  • A well-planned data migration should follow established best practices
  • Devise a thorough data migration plan after a complete analysis of your data
  • Running a small-scale migration test before executing the actual migration is highly recommended
  • Knowing the factors that can improve the reliability of an AWS migration and complying with them is the right way to go 
  • Data validation, metrics monitoring, and troubleshooting are all essential functions for an error-free data migration

If your business is ready to transition to the cloud, it’s time to get your data magnifying glass out to ensure a smooth data migration. If you can get your data shifted into the cloud accurately and securely, more than half of your cloud-migration headaches will be behind you. 

Here are some AWS data migration best practices that will help you complete this essential step with minimum risk and disruption. 

Have a thorough data migration plan based on analysis of your actual data

Migrations are always high-stress situations, regardless of whether they are happening in the Serengeti or in an organization making its move to the cloud. To make sure your cloud migration process is a smooth one, your IT team should chalk out a migration plan that covers every element of the migration project. 

First and foremost, there needs to be a thorough analysis of the data to be moved. The nature, importance, and access requirements of all the data to be migrated should be mapped out, so your data migration team can get everything where it needs to be in the cloud in the right order with data relationships intact. 

Once the data analysis is done, look at the available AWS data repository options namely: Amazon S3, Amazon Glacier, and Amazon EBS.  

  • Amazon S3 is the pay-as-you-go option, and it is best suited for data that is only going to be accessed occasionally. 
  • Amazon Glacier is your go-to choice for archival storage at the lowest cost and is appropriate for data that will not be accessed for a considerable duration. 
  • Amazon EBS is high-performance storage for data you use frequently. 

You also need to decide whether you want to migrate the data all at once or step-by-step. This will help determine the most appropriate data transfer tools, such as Rsync, FTP, Jump Box, or AWS Snowball.

Here are a few other things you should know while planning a database migration using AWS DMS:

  • You will have to configure a network to connect your source and target databases to the AWS DMS replication instance. Click here for more information on network configuration.
  • Depending on the engine of your source and target database, you may have to set up supplemental logging or adjust other settings. For further information on this, see data migration sources and data migration targets.
  • You can’t use AWS DMS for schema conversion for different database engines. However, you can use the AWS Schema Conversion Tool to create a target schema and generate tables, indexes, etc. 
  • Make sure you are able to convert the source data types into equivalent data types for the target database.
  • It is highly recommended to run diagnostic support scripts and premigration assessments before going for the migration. Running these scripts and assessments will give you insights into where potential migration failures could happen. 
  • Review the AWS DMS public documentation for the source and target endpoint before finalizing your migration plan. 

Run a test migration

Testing your migration plan by running a small test migration can help discover issues, if any, and aid in setting a realistic data migration timeline. You may also need to run a full-scale test migration to measure if the AWS DMS can deal with the throughput of your database over your network. 

The test migration phase will also help you identify your data profile more clearly.

Factors that affect AWS DMS migration performance

Various factors can affect the performance of a data migration carried out via AWS DMS:

  • The available network throughput
  • Resource availability on the source
  • The target’s ability to ingest changes
  • The replication server’s resource capacity
  • The quantity of the objects to be migrated
  • The distribution and type of source data

Understanding these factors can improve data migration performance by helping your migration team make the right arrangements, such as provisioning an appropriate replication server. 

Reducing load and bottlenecks on source and target database during migration

If you observe overburdening of the source database during the migration process, reduce the number of tasks or tables for each migration task. Individual tasks get source changes independently of others, so a decrease in change capture workload can be achieved by consolidating tasks.

Try to halt any processes that are competing for target database write resources. This will help clear bottlenecks on your target database.

Data validation 

Once the migration is completed, you can turn data validation on, which makes the AWS DMS compare the source and target data to identify any discrepancies. For more information about data validation, see AWS DMS data validation.

Task monitoring metrics

The AWS DMS console has several options for task metric monitoring, which can help you maintain the availability, reliability, and performance of AWS DMS.

  • Host metrics can be used to monitor whether your replication instance is sized correctly. 
  • Replication task metrics gauge incoming and committed changes, as well as latency between replication host and source/target databases. 
  • Table metrics for each individual task help monitor overall migration performance. 

For more information about monitoring metrics, see Monitoring AWS DMS tasks.

Troubleshooting migration issues and replication tasks

During the course of your migration, AWS DMS may encounter issues for which error messages or warnings can only be seen in the task log. These issues usually include row rejections due to foreign key violations and data truncation and are only written in the task log. So, always be sure to review the task log while migrating a database. For more information on this click here.

You can also use the time travel option to troubleshoot replication tasks. For more information about Time Travel go to Time Travel task settings.

Contact CloudHesive to make sure your cloud migration goes smoothly

CloudHesive is an Amazon Premier Partner company that provides expert assistance on the journey to AWS cloud. Contact the CloudHesive team today for all your cloud-based questions.

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