20 AWS Database Migration Service Interview Questions and Answers

Database migration is a complex process that requires careful planning and execution. When you’re interviewing for a position that involves database migration, you can expect to be asked questions about your experience and knowledge of the AWS Database Migration Service (DMS). Answering these questions confidently can help you demonstrate your qualifications and land the job. In this article, we’ll review some of the most common DMS interview questions and provide tips on how to answer them.

AWS Database Migration Service Interview Questions and Answers

Here are 20 commonly asked AWS Database Migration Service interview questions and answers to prepare you for your interview:

1. What is AWS Database Migration Service?

AWS Database Migration Service is a web service that helps you migrate your databases to AWS. It does this by providing a simple interface that you can use to copy your data from your current database to a new database in AWS.

2. What are the different types of data stores supported by AWS DMS?

AWS DMS supports a variety of different data stores, including relational databases (such as Amazon Aurora, MySQL, MariaDB, Microsoft SQL Server, Oracle, and PostgreSQL), as well as non-relational databases (such as MongoDB and Amazon DynamoDB).

3. Can you explain what homogenous migrations and heterogeneous migrations are in the context of AWS DMS?

A homogenous migration is one in which you are migrating your database from one platform to another that is the same or very similar. This might be, for example, moving your database from MySQL to MariaDB. A heterogeneous migration, on the other hand, is one in which you are moving your database to a platform that is significantly different, such as moving from MySQL to Oracle.

4. What is the difference between a full load and CDC (change data capture) in AWS DMS?

A full load is the process of migrating all of the data from your source database to your target database. This is typically done when you are first setting up your target database, or when you are performing a major update to your target database. CDC is the process of migrating only the data that has changed since the last full load. This is typically done on a regular basis to keep your target database up to date.

5. Why would I need to use AWS DMS?

AWS DMS can be used when you need to migrate your database from one platform to another. This can be useful when you are changing database providers, or if you need to move your database to a new server. DMS can also be used to replicate your database across multiple servers for high availability.

6. How does AWS DMS handle schema changes during migration?

AWS DMS uses a process called “online schema migration” to handle schema changes during migration. This process allows for the target database to be updated with the new schema while the migration is still in progress, which minimizes downtime and disruption.

7. Does AWS DMS support change data capture for Oracle source databases?

Yes, AWS DMS does support change data capture for Oracle source databases. This means that it can track changes to the data in the source database and replicate those changes to the target database.

8. What happens if an error occurs while migrating data using AWS DMS? Will it stop or can you configure it to continue?

If an error occurs while migrating data using AWS DMS, it will stop. You can configure it to continue, but it will skip any records that caused an error.

9. Is there a way to migrate multiple tables from one database to another using AWS DMS? If yes, then how can this be done?

Yes, it is possible to migrate multiple tables from one database to another using AWS DMS. This can be done by creating a separate migration task for each table that you wish to migrate.

10. Can you explain the process used by AWS DMS to copy data from a source database to a target database?

AWS DMS uses a process called Change Data Capture (CDC) to copy data from a source database to a target database. CDC involves reading the source database’s transaction logs to identify changes that have been made to the data. These changes are then applied to the target database, so that it contains an up-to-date copy of the data from the source database.

11. What do you understand about Amazon S3 buckets in relation to AWS DMS?

Amazon S3 buckets are used to store data that is to be migrated using AWS DMS. The data is first transferred to an S3 bucket, and then from there it is transferred to the target database.

12. What’s the maximum size of a table that can be migrated with AWS DMS?

The maximum size of a table that can be migrated with AWS DMS is 4 TB.

13. What is your understanding of custom endpoints in AWS DMS?

Custom endpoints are used when you want to connect to a database that is not currently supported by AWS DMS. In order to do this, you will need to create a custom endpoint using the AWS Management Console. This will allow you to specify the connection information for your database, as well as any other necessary settings.

14. Can you explain what Target Table Preparation Mode is? Which mode should I choose to ensure no errors occur when migrating data using AWS DMS?

Target Table Preparation Mode is a setting in AWS DMS that allows you to choose how you want to prepare the target table for data migration. There are two modes: Do Nothing and Truncate. In Do Nothing mode, AWS DMS will not make any changes to the target table. This means that if there are any existing data in the table, it will remain there after the migration. In Truncate mode, AWS DMS will delete all data from the target table before migrating the data from the source. This ensures that there are no errors during the migration, but it also means that any data that was in the target table will be lost.

15. What is the default provisioned throughput for replication instances in AWS DMS?

The default provisioned throughput for replication instances in AWS DMS is 1,000 reads and 1,000 writes per second.

16. What steps are required to set up an AWS DMS migration task?

In order to set up an AWS DMS migration task, you will need to first create an IAM role that will allow DMS to access your source and target databases. Next, you will need to create a replication instance. Once the replication instance is created, you will need to create a migration task. This task will require you to specify the source and target databases, as well as the IAM role that you created earlier. Finally, you will need to start the replication task.

17. What are some best practices you think should be followed when designing an AWS DMS architecture?

Some best practices for designing an AWS DMS architecture include using multiple replication instances for high availability, using a VPC for security, and using a CloudWatch alarm to monitor replication.

18. What’s the best way to analyze progress and monitor ongoing activity during a migration task with AWS DMS?

The AWS Database Migration Service (DMS) offers a few different ways to monitor progress and activity during a migration task. The AWS Management Console provides a visual representation of the task’s progress, and you can also use the AWS DMS APIs to programmatically track progress and activity. Additionally, the AWS DMS event notification feature can be used to send email or Amazon Simple Notification Service (SNS) notifications when certain events occur during a migration task.

19. What are the limitations of AWS DMS?

AWS DMS is limited to databases that are compatible with the AWS Database Migration Service. Additionally, it can only migrate data from databases that are within the AWS DMS supported data types.

20. How much time will it take to migrate 100 GB of data from one database to another using AWS DMS?

The time it takes to migrate 100 GB of data using AWS DMS will vary depending on a number of factors, including the size and type of the data, the number of concurrent tasks, the amount of available network bandwidth, and the number of changes being made to the data. Generally speaking, it will take longer to migrate larger amounts of data or data with a lot of changes.