Legacy modernization is a type of application modernization that consists of migrating legacy systems to new, modern platforms. This often involves updating application architecture, infrastructure, and features. The primary driver for this transformation is the need for businesses to adapt to new market demands, improve user experiences, and leverage modern technologies like cloud computing, data analytics, and artificial intelligence.

Undertaking a legacy modernization software project involves a comprehensive assessment of the existing application portfolio to identify modernization candidates. From there, an organization can choose from a range of strategies, from simply moving an application to a modern infrastructure to completely rebuilding it with cloud-native principles. The goal is to evolve critical systems, helping to ensure they can support the business's long-term strategic goals rather than holding it back.

Replacing legacy systems or choosing to modernize legacy apps can provide tangible business benefits that go far beyond just having newer technology.

Modernized applications are easier to update, allowing development teams to release new features faster and respond more quickly to changing market conditions. This agility is a key competitive advantage.

Legacy systems are often expensive to maintain, requiring specialized skills and aging hardware. Moving to a modern, cloud-based platform can shift costs from capital expenditure (CapEx) to operational expenditure (OpEx) and reduce overhead.

Older software may have unpatched vulnerabilities and may not meet current compliance standards. Legacy software modernization provides an opportunity to build in robust, modern security controls and ensure adherence to regulatory requirements.

Legacy applications frequently struggle to handle modern traffic loads. Migrating a legacy application to the cloud provides access to elastic infrastructure that can automatically scale to meet demand, ensuring a reliable user experience.

Modern platforms provide native access to advanced services for data analytics, machine learning, and AI. This allows businesses to unlock new insights and capabilities from their data that were inaccessible with older systems.

Containerization has emerged as a powerful technology for accelerating legacy app modernization. By packaging an application and its dependencies into a container, you create a lightweight, portable, and consistent unit of software. This is beneficial across multiple modernization strategies. For a "rehosting" or "replatforming" project, containerizing a legacy application can simplify the migration process and ensure it runs reliably in the new cloud environment. For a "refactoring" project, containers are the ideal deployment model for the new microservices that are being carved out of the original monolith.

Containerization allows you to package a legacy application and its dependencies into a standardized, portable unit—a container—that can run consistently across any environment. This approach effectively decouples the application from its underlying legacy hardware and operating system, providing a direct bridge to a modern cloud platform.

By containerizing a legacy application, you create a consistent artifact that can be easily deployed onto a managed Google Cloud service like Google Kubernetes Engine (GKE) or Cloud Run. This initial step can be achieved without immediate, large-scale changes to the application's source code, offering a lower-risk path to migrating a legacy application to the cloud. Once running in a modern environment, the application can then be iteratively improved, connected to managed cloud services, and gradually refactored over time.

This process breaks down the modernization journey into a series of manageable steps, using containerization as the core technology.

Begin by analyzing your portfolio of legacy applications. A good first candidate for containerization is often a stateless application or a service with minimal, well-understood external dependencies. This reduces the initial complexity and allows your team to build experience and confidence with the process.

The next step is to define how to package your application as a container. You can do this by creating a simple text file that contains a set of instructions, such as a Dockerfile. This file specifies a base operating system, copies your application's source code into the image, and lists the commands needed to install all necessary runtimes, libraries, and other dependencies.

Using the file, you build the container image. This can be done on a local developer machine or, for a more robust workflow, automated using a CI/CD service like Cloud Build. The resulting image—a static, portable file—should then be pushed to a secure, private container registry like Google Cloud's Artifact Registry, which acts as a centralized location to store and manage your application images.

With your containerized legacy application now stored in Artifact Registry, you can deploy it to a modern, managed platform on Google Cloud.

• For applications requiring more configuration control or that are part of a larger system, Google Kubernetes Engine (GKE) is an ideal target
• For simpler, stateless web applications or APIs, Cloud Run offers a fully serverless experience, handling all infrastructure management for you

Once your application is running in a container on Google Cloud, you can begin to incrementally modernize its dependencies. Instead of connecting to an old, on-premises database, you can configure the application to connect to a managed service like Cloud SQL. This offloads the burden of database management and improves reliability.

With the application now running in the cloud, you can use Google Cloud's operations suite (Cloud Monitoring, Cloud Logging) to gain deep insights into its performance. This data can help you identify bottlenecks and plan the next phase of modernization, which could involve refactoring specific parts of the application into separate microservices, further optimizing its performance and agility.