The low-no-code series – Software AG: Automating-out technical debt

The Computer Weekly Developer Network gets high-brow on low-code and no-code (LC/NC) technologies in an analysis series designed to uncover some of the nuances and particularities of this approach to software application development.

Looking at the core mechanics of the applications, suites, platforms and services in this space, we seek to understand not just how apps are being built this way, but also… what shape, form, function and status these apps exist as… and what the implications are for enterprise software built this way, once it exists in live production environments.

This piece is written by Subhash Ramachandran, senior vice president of product management at Software AG. 

Ramachandran writes as follows…

More than two-thirds of businesses (69%) in our Reality Check report believe technical debt means that they can’t continue their digital transformation at the same pace as during 2020. It’s understandable that companies (68%) will need to commit more resources to pay down technical debt in the future, but it’s important to balance this with continuing transformation.  

Technical expertise is required in order to complete the coding and development needed to clear technical debt. But it’s those same skills that are needed to continue transformation as well as ensure that an MVP is resilient enough to avoid some of the costliest debt. 

Automation is an answer. If companies can automate heavily manual processes, then they can free up valuable developer time not only to manage technical debt tasks, but also to continue transformation initiatives. What is crucial though is to identify the processes where automation has the highest positive impact.

Discovery & integration tasks

At an architectural / infrastructure level, it’s possible to help speed up the time-to-completion of many jobs by automating a lot of discovery and integration tasks. For instance, Integration & API platforms that automate API discovery and connection can save time for developers.

In parallel, low-code and no-code systems can help to satisfy the growing demand for relatively simple application or process development. If developer time can be freed up from these simple tasks and focused on the more complex projects, companies can stay more focused on their technical debt management, amongst other mission-critical initiatives.

Goldman Sachs recently announced a high profile – and high value – investment into a low-code platform. This clear intention to bring more automated tools into the organisation, to speed up the implementation of new tools shows what the future could look like for this kind of approach. They can be tremendously empowering – one of our own governmental customers in Europe has been able to roll out 800 new apps in just a few years with a no-code platform.  

Limiting limitation situations 

Ramachandran: Automation (and easier API consumption) can be tremendously empowering.

Low code or no-code applications are beneficial in situations where the task is relatively simple and completely definable. If the owner can be very specific about the process and the outcomes, then it’s possible to have a very functional outcome. However, where any complexity is needed – or the owners want the app to do too much – a gulf can emerge requiring more development. 

The issue of how and where to use low or no-code platforms is one for businesses to decide for themselves on a case-by-case basis. However, for those that do decide to go down this route, the issue of technical debt should be high in their thinking. 

As with any automation effort – whether low code development, RPA, AI, IoT or anything else – the open standards that enable it are crucial. If low-code/no-code automation is not designed initially by the IT department so that all new applications adhere to basic standards then significant levels of technical debt could build up here too.  

Bringing in API automation

The simplicity of many low/no-code generated tools is also a reason why they are susceptible to technical debt build up. As they become more widely used and potentially need to scale, they might hit the limitations of the initial coding.

However, automated API discovery and wizard-driven tools to consume and build APIs are enterprise-wide functions that could greatly alleviate some of this burden. The current API Management market focuses more on providing APIs but the underserved market as identified by industry analysts like Gartner is actually easy API consumption. 

Apps need access to a lot of data that are currently provided as APIs. 

As these simple apps run into a need to connect with other applications or data streams, it becomes important to easily consume these APIs – low-code API consumption tools can help with this. If these connections can be established automatically, it’s problem solved. 

The same is true of other automated process – if RPA bots run into a need to talk to one another, having a standardized and automated way for them to connect via APIs using low-code tools potentially swerves the issue of technical debt entirely.

 

 

 

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