Software solutions developed some time ago that operated efficiently then may now not meet business and market needs. In general, legacy (meaning old) systems are defined as those built with monolithic architecture, using outdated technologies, which are difficult to change.
Modernization is crucial for efficient performance and business development. If your internal team can’t handle doing this, that’s no reason to feel desperate. Many software development companies can help you modernize a legacy system using advanced technologies. The DigitalMara team has vast experience dealing with old code and can determine the proper approach and tech stack for each individual use case.
Some legacy technology examples are Borland Delphi, COBOL, Visual Basic, RPG/400, and Oracle Forms. These old systems aren’t really adapted to the modern development environment and have become incompatible with current systems and platforms. Legacy code troubleshooting takes a long time and can be costly.
Main issues with legacy systems:
Slow performance and regular failures.
A poor user interface leads to a poor user experience for both system administrators/employees and end consumers of the service. Legacy systems have low efficiency and productivity, and adapt inadequately to market changes.
Lack of stability.
Legacy systems suffer from insufficient support and maintenance. Keeping an old system just for the sake of continuing to operate is costly. Fewer and fewer programmers and engineers are able to work with and support a system that has an outdated technology stack.
Adding new functions and updating existing features may be challenging and take a lot of time. Legacy systems are not very compatible, which makes it hard to connect them with third-party services and tools.
Legacy systems work on old security standards and protocols, which means they’re exposed to data breaches and cyber-attacks. Also, there is a lack of compliance with current regulations when it comes to data storage, use and protection.
The system doesn’t have to be that old to be considered obsolete. Any software system can be deemed a legacy system if it matches these issues.
Where can you find legacy systems?
A lot of companies and organizations from a variety of industries continue to use legacy software. They conduct their daily core operations and process large volumes of data.
Legacy banking systems are facing many issues, such as fragmented data architecture, slow performance, long transaction times, etc. The most pressing concerns are those related to security and fraud prevention. Banks must constantly update security control components in compliance with current standards. Old systems are not set up to take advantage of machine learning operations or processing ever-growing numbers of transactions and data exchanges. Data cannot be automatically converted into a machine-readable format.
Another challenge comes from the rise of FinTech and digital payments. Today’s customers want to have access to their financial assets at any time and pay instantly, on any device. Banking applications should be simple, with clear user flow and high functionality. But legacy software often doesn’t perform properly on mobile devices and has outdated user interfaces. Obviously, dealing with such a bank’s digital ecosystem tends to be frustrating for both customers and employees.
Legacy insurance systems are built more around policy records, rather than customer records. This makes it harder to conduct key operations, from billing and claims to reporting and analysis. Data entry manual processes lead to additional errors. During the pandemic, another problem appeared: legacy systems based on on-premises operations are not able to provide secure and seamless remote access to employees.
Insurance companies should transition to a more customer-centric approach. In terms of technologies, that means implementing data lakes, MDM projects, asset management systems, automation, advanced CRM applications, straight-through data processing and self-service opportunities. Insurtech startups are driving the industry and gaining market share. These provide customers with a personalized digital insurance experience — easy access to guides, services and payments, any time and anywhere. In the absence of an omnichannel solution available 24 hours a day, today’s customers find traditional systems hard to use and frustrating.
The retail industry in essence should be dynamic, considering the impact of customer preferences, pandemic consequences and advanced technologies, all while the traditional scenario of physical retail is transitioning to digital. Customers want to have personalized and omnichannel shopping experiences. In response, retailers need to implement an on-demand model. But integration of a legacy system with, for example, a new CRM or a live chatbot is not so simple.
Retail legacy systems are slow and take a long time to accomplish standard tasks. This can be frustrating for customers, harming the brand image. Also, let’s not forget that for retail, business logistics and order management are crucial processes. Software should synchronize inventory positions and show real-time stock information in order to manage all flows properly. To overcome these challenges, retailers can adapt a data-driven approach and agile methodologies.
Government legacy systems have monolithic and massive architecture. They have to store and process enormous amounts of data about the population, such as taxes, pensions, utility bills, health cards, immigration status and much more. Meanwhile, as data is stored in multiple systems (fragmented architecture), security risks are high. Old systems are also incompatible with modern components, for example, augmented and advanced analytics, and intelligent automation.
Government provides support and services to thousands of citizens. But the software is often slow, user-unfriendly, complex and inflexible. However, like any other service today, it has to adjust to the online experience and an on-demand approach. Citizens depend on government resources that need improvement. Missed benefits payments, system hangs and delays in service are only some of the possible system failures. Trust and satisfaction are essential.
The core element of logistics is a large number of data types. Logistics legacy systems can’t handle all these data flows in real-time and don’t have advanced analytics modules. Not all components of the system are interoperable, which means some data can’t be transferred from one to another in a readable format. In many cases, due to lack of support, decisions on production, inventory and transportation have to be made manually.
Logistics companies or logistics departments need to see everything that goes on in the supply chains and manage multiple data flows. They want to have one data source with full access to accurate, comprehensive and transparent data in real-time. It should be a single-control platform that collects information from several sources and ensures visibility of the whole supply chain.
Why is legacy software still here?
Legacy software typically runs essential business processes of the organization, so the prospect of major changes provokes fear and uncertainty. While the current process remains cumbersome, employees don’t want to lose the stability of core operations.
Major risks associated with migration include:
- High costs
- Data loss
- Lack of skills
Often old systems lack technical specifications. This can complicate the transfer process, making it long and expensive. In addition, the internal team may not have the necessary skills and knowledge. That means organizations have to find qualified professionals who will help them choose the right approach and the best technology stack, and perform the migration.
During migration, some core operations might not be performed properly and productivity may decrease. Even after the process is completed, employees and other users of the system will have to study the updated workflow.
How to update a legacy system
One day, today’s ideal solution will ultimately become obsolete and ineffective. In this case, updating means migrating from an outdated tech stack to modern frameworks, libraries and protocols. Here are 4 major approaches for migrating from the old system.
Approach 1 – Microservice architecture
Microservice architecture is suitable for high-load systems. The benefit of this approach is that there’s no need to rebuild the entire legacy system. The new system comprises a set of components. Each unit has an individual codebase and can be scaled independently, while communication moves via APIs. This composite architecture is agile enough to add third-party integrations and updates. It’s a time- and cost-efficient approach, being holistic and business domain–focused. Microservice architecture provides enhanced data security, stability and maintenance.
Approach 2 – Cloud solutions
This approach incorporates two scenarios: migrating to the cloud, and replacing the legacy system with a cloud solution. Security concerns are addressed with reinforced data protection, which means data encryption and multilevel authorization are obligatory. Cloud solutions are flexible and easy to scale. They can be updated automatically and connected with third-party services and systems. New features can be implemented faster. Such an approach also helps cut operational costs and save time through optimizing automated processes and data storage.
Approach 3 – Container-based architecture
Container architecture assumes that the legacy system is split into parts, each running independently. Each part is deployed as a separate container. The number of containers can vary, from a simple structure to one that’s more complex. In the first case, slight modifications are introduced into the system. In a more complex structure, refactoring and even recoding will be required. However, the components are lightweight, with defined availability and scalability properties. Parts responsible for state management and data persistence also can be turned into containers, using extra tools.
Approach 4 – RPA-automation
Legacy systems typically perform numerous repetitive tasks, and, obviously they are not automated. RPA-automation can solve this issue without making it necessary to interrupt operations of the old application and therefore the entire workflow. With this approach, you can automate repetitive, rule-based and time-consuming tasks, decreasing operational costs and errors, for example, in customer service and back-office operations. RPA-automation enables reliable data security and consistency when running your legacy application. Importantly, it’s more agile and takes less time to deploy than for API or other integrations.
Modernizing a legacy system is a long-term project that requires deep knowledge and established processes. Achieving a seamless transition requires the proper choice of approach and extensive experience. This is definitely one time when it’s better to hand over the job to a professional software development team with proven experience that can create a custom software solution according to your requirements and objectives.