Think big, execute small: lean thinking for cloud modernization

Enterprise migration to Amazon Web Services (AWS) is only a first step in the cloud modernization journey. Migrating applications to AWS with minimal or no changes is often considered a high-velocity approach to achieving a higher net present value (NPV) and to reducing production issues and customer downtime.

AWS migration programs are followed by a continuous cycle of right-size optimization, reserved instances and continuous tweaking based on usage analytics.

Businesses can magnify the commercial benefits of the cloud, however, by modernizing the enterprise application portfolio, using AWS’s purpose-built databases, serverless computing, containerization and microservices architectures. When properly leveraged, these technologies help build a high-frequency change organization that can respond to disruption.  

A New Take on Modernization

Modernization approaches can follow the “strangler” pattern proposed by Martin Fowler, where new code and refactoring is handled on the edges of the legacy systems. As Fowler explains, the new code gradually creates a new system around the edges of the old, letting it grow slowly over several years until the old system is “strangled.”

Historically, enterprise legacy modernization programs like service-oriented architectures have been start-stop affairs, with challenges ranging from competing demands from users for adding new features, re-architecting and re-factoring application code and choosing the right products from a crowded marketplace.

Choosing a Cloud Modernization Approach

AWS makes the road to modernization easier with a number of services that allow enterprises to think big and execute small while continuing to deliver new features to customers. These approaches include adoption of serverless architectures, containerization and implementation of continuous integration/continuous deployment (CI/CD) pipelines, and migration of commercial databases to Amazon Aurora.

• Serverless architectures: Serverless computing services like AWS Lambda enable enterprises to run applications/code without needing to provision or manage servers. For example, you can build serverless applications to provide scalable API services to customers from legacy web applications without having to invest in highly available infrastructure. Serverless applications can also be built to process real-time data and back-end processing to serve requests from mobile applications and Internet of Things (IoT) devices.  You don’t have to break down your big monolithic applications to microservices right away. Just look for use cases (typically all code that responds to events) for serverless implementations to modernize your legacy applications.

• Containerization: Containers provide many benefits, including environmental consistency, interoperability (between on-premise and public cloud systems) and microservices implementation. Containers also provide an easier path to migrate legacy applications to the cloud, including commercial off-the-shelf (COTS) products. AWS services such as Amazon ECR and AWS Fargate help store, manage and run containers.

• Migration to cloud-native databases: Migrating commercial databases to cloud-native databases such as Amazon Aurora not only provides long-term cost savings but also increases the agility of application releases and operations. This approach frees up resources from managing routine database tasks and also provides performance benefits in production environments. Businesses can move away from commercial one-size-fits-all databases to purpose-built databases for transactions, analytics, text search and machine learning.

The above patterns can help your organization incrementally modernize its portfolio without disruption to product backlog and velocity.