Its an era of Cloud computing and anywhere you go, people talk about cloud computing and its usages, migration and benefits etc.So, I thought of taking an initiative on understanding how SQL Server is versed with Cloud. I would like to admit the fact that it was a “walk away” for me initially, but its quite interesting and fascinated knowing more about. Not just because its success stories,but also I loved the challenges while assessing different scenarios SQL Server with Cloud computing and its support.

This blog post concentrates on AWS and SQL Server.

Let us quickly understand what is AWS first?

AWS is a cloud computing platform provided by Amazon. It includes Infrastructure as a Service (IaaS), Platform as a service (PaaS) and Software As a Service (SaaS). Its a “pay-as-you-go” computing model that means you can scale your depending on your needs and pay for the service. Again, I do not want to go in detail about AWS since lots of resources available in internet and its just a google search away.

AWS offers a great flexibility to run SQL server with two major options:

1. Amazon Elastic Compute Cloud (EC2)
EC2 is a version of VM in Amazon cloud platform. It provides us a complete control for settings/configuration etc.
2. Amazon Relational Database Service (RDS)
RDS is a fully managed service without much control to the user. Service would take care of maintenance and manageability of service instances. Amazon RDS supports various relational database engines like MySQL, PostgresSQL, MS SQL, Oracle , MongoDB, Maria DB and Amazon Aurora etc.
Amazon Relational Database Service provides many more managed services compared to EC2 as shown in the below picture. Hence, its is more of business drivers that the customer can spend more effort on their data rather than maintenance and manageability of their database or instance.

Features supported by RDS & EC2

Now, its very important for SQL Server Professionals that to understand the supporting features for Amazon RDS and Amazon EC2. A quick reference table is prepared as below (as on 25th Apr 2020). We need to understand this reference may or may not needs changes as Amazon increases its capabilities in future and we may need to compare with the latest at the time.

The above are the major comparison chart, more detailed information, please refer See Also section.

Assessment & Planning

Since we had seen some of the differences between Amazon RDS & Amazon EC2 services, it is time for us to evaluate which one would be best suited for our application if there is a migration plan exists. We all should be aware the fact that it is NOT definitely a LIFT and SHIFT technique, but needs lots of understanding of your system and careful evaluation of certain things. This is the most time taken phase. I would like to list out few parameters to help in this decision making as below. Please note, it is a very wide topic and we should do a careful evaluation depending on your application/project workloads and other characteristics. I would also suggest to have an evaluation done by an Amazon professional for smooth transition.

1. Conduct an inventory of your SQL Server instances
2. Conduct an inventory of your SQL Server databases
3. Know your current Licensing option
One of the main reasons for cloud migration is cost saving. It can be in terms of Infrastructure cost or human resource cost or maintenance cost etc. License Cost can also be reviewed here as AWS comes with License option by default, so it would be important to verify the current licensing option with your organization and Microsoft that can be further evaluated. “Amazon RDS for SQL Server supports the “License Included” licensing model. You do not need separately purchased Microsoft SQL Server licenses. “License Included” pricing is inclusive of software, underlying hardware resources, and Amazon RDS management capabilities.” Please refer for more details.
4. Understand your HA/DR solutions
5. Performance benchmarks if any /Capacity Planning
(Resource utilization like CPU/Memory/IOPS etc)
6. Data Retention Policy if any
This assessment helps us to reduce the Disk cost and utilization. Say, If we have a database with 10 years of data and as per business rules, we just need ONLY last 5 years data , then it is good to purge or archive the older data before we migrate to AWS. This would reduce the space usage and enables an easy migration from On-Premise to Cloud. This is one of the area where Micorsoft Azure has flexibility using Stretch database feature; Amazon RDS does not support Stretch Databases yet (as on published date of this blog post).
7. Various Migration options

We will cover lot more interesting things in upcoming posts, until then stay tuned, stay safe!

See Also:

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_SQLServer.html

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