Organizations continue to prioritize legacy application modernization, with 50% of companies planning to modernize their legacy appplications in the next two years. Within five years, at least 75% plan to complete their modernization. How businesses approach their modernization can determine how disruptive the shift will be. The methods can increase or decrease the cost and associated risk, so many business leaders fear the disruption that modernizing critical legacy applications may cause.
Adding to their hesitancy is the lack of available talent for supporting advanced technologies. Over half of the surveyed organizations said a skills gap was a limiting factor to modernization. Part of the difficulty in attracting top talent to migrate legacy systems is that candidates with modern technical skills don’t want to work on legacy systems.
In fact, it is one of the top reasons that Chief Information Officers (CIOs) want to move away from older technologies. Equally important is reducing license and support costs for aging hardware and software. However, the real value of legacy application modernization is the ability to support the business needs of an organization. For all these reasons, modernization is a worthy effort. But what is the best way to go about it? Here are six best practices for legacy application modernization.
What is Legacy Application Modernization?
Technically, legacy application modernization is the process of updating older software to newer languages, frameworks, and infrastructures that deliver improvements in efficiency, reliability, scalability, integrity, and security. But, it is also a process that changes how organizations design and build software. It involves training new and existing staff on modernization methods.
Too often, companies get lost in technology. They focus their efforts on decreasing costs and minimizing risk. They fail to develop a process that will ensure the continuous improvement that modernization promises. Employing best practices like the ones below can help organizations create a process to deliver improvements long after the immediate projects are complete.
Most programmers fear the unintended disruption that comes when an interdependency goes undetected. Work stops as the program returns to its last restore point. IT cringes at the possibility of hours of troubleshooting. Upper management loses confidence in the process, and the momentum for legacy application modernization declines.
What is exclusivity? An exclusive entity only appears in a single Java or .NET service. Measuring exclusivity helps identify those resources that are only used in a single service. Whether it is a class, a database table, or sockets, finding exclusivity identifies code that may be modularized quickly or removed completely if no longer needed. It helps clarify the complexities of legacy systems.
Adopting tools designed to maximize exclusivity saves not only time but also decreases the odds of interdependencies going undetected. With an optimized analysis algorithm, teams can prioritize code based on exclusivity. Perhaps, two methods share a class dependency that could become part of a shared library, making it easier to architect microservices.
Legacy application modernization, whether you are refactoring, rearchitecting, or rewriting, should focus on optimizing the overall exclusivity of architectural entities when deciding on a new target microservice architecture.
Maintain Integrity of Data Layers
Data is a company’s greatest asset. Maintaining the integrity of the asset should be part of any modernization effort. Before deciding to split a data layer, developers should first address the business logic that uses the data.
In the long term, a microservice architecture requires that data layers should not be shared across multiple services, but the first step developers need to take is splitting up the business logic to ensure application and data integrity is maintained in the modernization process.
For example, refactoring an application may indicate that several microservices use the same database tables. Since microservices should be self-contained, the data should eventually be divided among the various microservices.
However, splitting the database will be much easier once highly exclusive services are created that only access independent parts of the database.
The practical approach is to look at the risks involved in splitting the data layer too fast. Since a database change is highly impactful and hard to reverse, it may be a better option to continue to use the shared data in the first phase of modernization. Once data is split, it is irreversible.
Complete the rearchitecture into microservices first before addressing the data layer. Remember, modernization is an iterative process.
Related: Monolithic vs Microservices Architecture: Modernizing Monolithic Apps and Databases for the Cloud
Create and Evaluate Common Libraries
Although the ideal is to keep services self-contained, it isn’t always possible. Sometimes, classes must be shared. Creating common class libraries can minimize code duplication. Instead of programmers writing different code to do the same thing, they can create classes to place in a library. When a program needs to perform a specific function, the developer can call the class library.
Common class libraries can make coding less onerous by allowing programmers to integrate pre-existing classes into their code. However, not every class belongs in a library. If not monitored, class libraries can turn into monolithic structures that impact performance.
Evaluate existing libraries to determine what classes should remain and which ones should be removed. If possible, establish guidelines for evaluating whether a class remains. Apply the same criteria when looking to add a library.
One advantage of establishing library guidelines for modernization projects is the existing knowledge of how the code is used. Knowing what the code does makes it easier to decide whether a class belongs in a library.
Identify Dead Code
Dead code refers to code that executes but has no impact on the program’s behavior. It is not the same as unreachable code, which is code that cannot be executed. Dead code confounds developers who try to understand legacy applications. It complicates the maintenance of existing code.
Finding dead code requires static and dynamic analysis. Static code analysis identifies problems with logic and technique, while dynamic code analysis executes the code and examines the results. Tools exist to help identify these problems. Automated solutions can analyze dead code and identify interdependencies that cannot be eliminated, saving hours of manually working through code.
Although dead code may not appear to impact a program’s behavior, its removal cannot be assumed to be harmless. Dead code could represent security risks. Hackers are always looking to exploit vulnerabilities in legacy code.
Dead code accumulates as an application matures. More programmers touch the application. Experienced staff leave. Before long, the legacy application is a mystery that adds to the time to maintain the software and increases the technical debt.
Start With a Simple Service Topology
Starting with a simple service topology in your modernization reduces risk and simplifies rollout. Focus on topologies where each service performs specific tasks, sends requests, or acts on requests without creating a complex mesh topology too soon. A simpler implementation allows a service to control traffic to and from other services or applications, making it easier to discern operations within a cloud environment. It minimizes the complexities of cloud operations.
Trying to construct a more complex topology can complicate the migration process. For example, a full mesh implementation connects every device through a dedicated channel, increasing the number of ports per device. With multiple connections, monitoring traffic becomes more complex, and troubleshooting can be difficult.
A hub-and-spoke topology centralizes network control to a hub that inspects traffic between spokes. The hub may contain the services that each spoke consumes. Consolidating policies at the hub simplifies the deployment of security policies and reduces misconfiguration potential.
Simplifying the network topology of a microservices application will make life easier and minimize possible errors. Starting with a hub and spoke model and then evolving to a more mesh-centric topology Is a recommended best practice.
Use Practical Decision-Making
Migrating legacy solutions to the cloud is a journey. It happens in increments and requires iterative cycles to complete. It’s a process that demands balancing business needs with technology. Modernization requires a strategy based on best practices. A mini-service approach can much more easily evolve into a true microservice architecture in a stepwise manner versus attempting to do everything all at once – that’s just impractical.
Before changing anything, organizations need to first identify the business objectives of modernizing legacy systems by asking questions such as the following:
- Is the system slow to respond?
- How long does it take to add a feature?
- Is the company looking at new markets or new products?
- How well can the existing infrastructure support organizational change?
If a company plans on expanding into new markets in the next five years, addressing technical debt that makes that difficult should be a high priority.
Cross-functional teams should be created to help developers understand what’s needed to meet business objectives. If a new product launch is expected in the next three years, what functionality does the infrastructure require?
For example, the process for sourcing parts for the new product will change. It will require better integration of manufacturing and purchasing to reduce time to market. Purchasing functionality needs more flexibility to address supply chain disruptions. Legacy systems make it difficult to adapt to new business processes.
With these objectives in mind, developers must determine if they should refactor or rewrite code. Since purchasing integrates with accounting, manufacturing, shipping, and receiving, what typology would be best?
Use AI-Based Automation Tools
Tools help reduce the time to completion. Automated tools are even faster. They can identify dead code and highlight exclusivity to create a cleaner code base for modernization. AI-based solutions not only shorten timelines but they provide intelligent tools that support a strategy based on best practices.vFunction’s AI-based automated platform for refactoring Java and .NET applications is designed to move organizations forward on their journey to modernization. Why not get started today?