Overview

Amazon RDS is a managed, relational database offering from AWS. It allows developers to set up a production-ready database in minutes without having to worry about installations, provisioning infrastructure, or maintenance. It reduces operational overheads by automating backups and patching.Amazon RDS provides a high-performance database system that can scale vertically in minutes. It allows you to set up multiple read replicas for read-heavy workloads. With the underlying AWS infrastructure, HA (High Availability) can easily be achieved through multi-AZ deployments where data is replicated in another availability zone. It provides security features such as encryption at rest and in transit, deployment within a private subnet on Amazon VPC, and integration with IAM for access control.The pay-for-what-you-use pricing model, coupled with high-performance, production-ready features, and services such as AWS DMS and SCT, has made Amazon RDS a popular cost-effective choice.
Migration to Amazon RDS
One of the main reasons why customers want to migrate to the cloud is to reduce operational overhead and infrastructure costs. The limitations with the on-premises data centers in terms of scalability also become a concern while adapting to the business agility needs.The licensing cost of the database contributes heavily to the overall ownership cost. Legacy proprietary database systems reaching end-of-life need license renewals/fresh licenses which are quite expensive. With the advancements in the open-source database systems, customers are now seeking to migrate to open-source databases such as MySQL or variants and Postgres and eliminate the licensing cost.Amazon RDS is a managed RDBMS offering from AWS which addresses these concerns. Many customers, however, are still reluctant especially in case of heterogeneous migrations due to the lack of experience and the required skill set. Below are some of the best practices we recommend for overcoming the challenges faced by the customers before and during the migration phase.

Key Learnings and Best Practices

Any solution always starts with defining the problem. Database Migration is no exception. Make sure that you have all the information that you need to make the right decisions. The requirement analysis should include the business needs, current and expected I/O, durability and performance expectations, and security and compliance need such as GDPR, SOC 2, HIPAA, PCI DSS, and of course ISO 27001. Thorough data analysis on what is stored and how the data is ingested or consumed is also a must before proceeding with the migration.
Assuming you have studied the requirements including compliance with the advancements in the open-source database systems there is little to choose among PostgreSQL, the good old MySQL, and MariaDB which is forked from MySQL. Decisions sometimes get complex here with conflicting views from different customer teams and stakeholders. Customers often need help in deciding to go with cloud-native databases such as Aurora or the stock MySQL or Postgres. To add to this complexity, the advantages and popularity of the purpose-built databases such as Amazon RDS, DynamoDB, Aurora, DocumentDB, Neptune, Redis, etc becoming evident it’s imperative to analyse the data and choose the right product for the right purpose.
One of the biggest challenges for adopting cloud-native services, especially for databases has been low confidence, in customers, related to the uncertainties revolving around the schema and data migration. The AWS Schema conversion Tool (SCT) and the Database Migration Service (DMS) address these concerns and ensure a smoother migration. The SCT tool can be run on the source DB for analysing compatibility in terms of the schema and data with the target database. The analysis report contains a statistics summary, estimated database objects, and code that can be converted automatically. It also lists the complexity level for the objects and code that will need manual intervention along with some recommendations.
While SQL has been the common factor among popular relational database systems, each DB system has its own set of data types, objects, functions, and even syntaxes. These differences make heterogeneous migrations complex and time-consuming. The AWS DMS and the SCT come to our rescue here. While these tools are excellent, ensure that you also explore other migration tools relevant to your source and target databases. Pgloader, Sqlserver2pgsql, Ora2pg, pg_chameleon, DBConvert, are some of the popular tools for migrating to PostgresSQL. For migratingSQL server database to Postgres Aurora, another option is to use Babelfish. With BabelFish, minimal changes are required during migration and the clients can connect with existing MS SQL drivers. T-SQL queries are directly supported on PostgresSQL with this feature. You may run the Babelfish Compass tool for compatibility assessment of T-SQL code of MS SQL with Babelfish.
Having the right technical team is crucial for ensuring a successful migration. The DB developers and administrators should have knowledge of both the source and the target database systems. Any prior migration experience with AWS SCT and DMS or other migration tools adds a lot of value. Working knowledge of different database systems including NoSQL, memoryDB, and other purposeful database systems also aids in choosing the right product, especially in a modernization project. With these technical skills, it’s also important to study the business requirement including purpose, budget, timelines, criticality of the application, and how the data is consumed.
With the above steps, you are well-equipped to handle the migration technically. It is also important to understand the business impact, availability of business and technical teams, infrastructure, and other logistics requirements. Using these parameters, a detailed migration plan can be prepared. Common steps include converting the schema and code first to the target database using tools such as AWS SCT, converting unsupported objects manually, migrating the data using tools such as AWS DMS, and finally verification and testing.

Our Experience

LTIMindtree helps the clients and end customers to define their requirement better by asking the right questions, understanding the business need, analysing the existing systems, and then recommending the right product(s). It also helps in defining the overall architecture considering the cost, performance, availability needs, compliance, and other parameters.

With our extensive experience and dedicated migration teams, we have helped our clients and end customers to set up the SCT analysis and accurately estimate and plan the migration. A detailed migration plan backed up by our success stories on such migrations brings in transparency and confidence, which has helped our customers in executing migrations successfully.

LTIMindtree has helped clients and customers build automated migration jobs for migrating on-premises databases to the cloud. These range from like-to-like to heterogeneous migrations including commercial databases such as MS SQL server and Oracle to PostgreSQL or MySQL, SQL to NoSQL such as DynamoDB, migrating to purposeful databases such as Redshift, OpenSearch, Neptune, MemoryDB for Redis, and S3.

LTIMindtree’s Service Offering for RDS

1. Consulting
Our consulting service offering focuses on application and Database assessment using the LTIMindtree Infinity platform and AWS Migration Hub services to build the right disposition strategy, cloud migration roadmap, and data migration strategy.
2. Application modernization
LTIMindtree has deep expertise in transforming customer-facing web applications and re-platforming legacy integration platforms into cloud-native or serverless PaaS-based architecture. Application modernization journey to AWS serverless PaaS is accelerated by 25-30% with the LTIMindtree’s reusable Lambda layers, best practices based on Well Architect Framework, observability solution, and Infinity DevOps platform for end-to-end continuous integration and delivery.
3. Modernizing data pipeline, data lakes
Our data engineering service line helps clients and end customers to modernize data pipeline/ETL and data lakes using AWS Data services and AWS Lambda. This service line helps to migrate commercial databases to serverless cloud databases such as Arora and DynamoDB using Lambda-based ETL or AWS DMS and SCT tools.
4. Low code development
Low code development offering is responsible for modern application development using AWS amplify and LTIMindtree Infinity Studio.
5. Mainframe modernization to cloud-native or serverless PaaS
LTIMindtree is focusing on assessing mainframe application workload for domain-led transformation, auto-code conversion using partner solutions, and API-Fication of business-critical functionality. LTIMindtree is also helping customers to migrate data from DB2, DB400 databases, and VSAM file system to AWS Purposeful databases.
6. DevOps engineering
LTIMindtree DevOps engineering services help in defining quality gates during application development to ensure all quality requirements are met and to deliver features at the scale. LTIMindtree has deep expertise in various open-sourced and AWS Cloud DevOps platform and services.

LTIMindtree’s Accelerators

This platform is equipped with efficiency kits for application assessment, development, deployment, FinOps, Operations and DevOps tools to accelerate AWS Lambda-based application development.
Architecture blueprints and best practices Architecture blueprints using AWS RDS for web applications, and business workflow use cases.
Cloud Ensure A self-service SaaS platform that provides FinOps governance on AWS serverless services viz RDS, AWS Lambda, API Gateway.
Observability platform for serverless LTIMindtree’s observability solutions help to navigate to the root cause of the problem easily, which helps to reduce application development using RDS databases and Lambda functions.

Conclusion

Amazon RDS helps clients and end customers to build secure, scalable, compliant, and highly available systems. It empowers customers to set up high-performance production-ready databases within minutes. Tools such as AWS SCT and DMS help in migrating the databases to RDS.

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