Your software has become an integral part of your company, but it's ageing. It's becoming increasingly expensive to maintain and inhibiting your company's growth and innovation potential. What do you do? You've been considering upgrading your systems, but you're unsure if it's better to rewrite your existing legacy software or cut the cord and buy new software. The problem is, both of these options come with a variety of possible consequences, and so you're stressing over your legacy system upgrade. Does this scenario sound familiar? Let's unpack the situation and discover the pros and cons of each option.
A rewrite bears perhaps the highest risk of all, as it requires further investment into an ageing, failing system. Furthermore, despite your efforts, your company will remain at a technical disadvantage. However, if you go down the path of finding a software development company to develop a completely new software stack, then there will be a steep learning curve for your employees, which means decreased productivity. You also risk losing valuable features and gaining unnecessary ones. And then there's the price tag. Of course, you could always continue using your existing legacy application(s) for the time being, however, this could limit your business' potential. Enter cloud migration.
Migrating legacy systems to the cloud is a third option that you may be interested in. This process is usually three to four times faster than a rewrite, and far less intrusive or expensive as new software and/or systems. Admittedly, there are risks. Some businesses can spend millions of dollars migrating data between applications, such as legacy applications to the cloud, only to have the results of this migration fall short of expectations. This is usually because of flaws in the migration process (sometimes data is inadequately validated for its intended tasks). Although there are risks associated with all of these options, including doing nothing, cloud migration services are becoming increasingly appealing because they combine the best of both worlds: fixing existing software and developing new technologies.
Migrations are an experimental process. You are trialling your legacy applications in a whole new ecosystem. Therefore, the best way to go about the move is to be scientific. This means building a hypothesis, testing its level of success, and then building from the data. The benefits of working in iterations are allowing your business to build upon successes and address failures. This build-measure-learn concept is an extremely valuable asset for all businesses for two reasons:
Withholding from one big release of your software allows you to avoid building on flawed code and ideas.
Finding small problems in your application as you incrementally release updates is better than finding a big problem on launch.
Of course, the other big reason to not stress about your legacy migration are the innovative new software development tools and practices beginning to make an appearance in Australian software development companies.
Both of these considerations synergise with cloud migration. Nothing is more iterative than cloud migration, as the intention is to retain all existing functionalities; only migrate them to the cloud, where upgrade and maintenance costs are cheaper and user experience is better.
Model-Driven Engineering and Domain Specific Language
There have been huge developments in automatic programming, which have increased the power of code robots, or codebots. These automatic code writers can be used in a legacy migration. Academic research in this area is known as Model-Driven Engineering and Domain Specific Language (DSL). Model-Driven Engineering relies on creating and exploiting models as opposed to depending on complicated computer algorithms and concepts. DSL is an alternative to general-purpose language (GSL). The advantage of DSL is that it can allow a particular type of problem or solution to be expressed more clearly than an existing language, especially if the type of problem in question reappears sufficiently often. Pragmatically, a DSL may be specialised to a particular problem domain or representation technique, a particular solution technique, or some other aspect of a domain. Both Model-Driven Engineering and DSL are awesome examples of the advanced and innovative technologies that are emerging, they also synergise with agile business practices.
Agile, MVPs, And Codebots
The first release of your application should be a minimal viable product (MVP). By starting with a MVP, you can "build, measure and learn". This process combines well with the innovative methods of coding, such as codebots, mentioned above. Codebots write code faster than humans do, allowing for more iterations, which means more opportunities for measuring and learning. Furthermore, because both agile and codebots are powered by precedence (earlier builds and models), the template of your legacy system serves as an awesome springboard, allowing for faster, cheaper, and better cloud solutions. So don't stress about legacy application migration.