Software development is in a state of constant evolution.
Nonetheless, 2019 still promises some unprecedented changes, many of which could completely transform the way your company develops software.
In particular, there are two software-development trends your team should know about. As they could become commonplace by 2020, now’s the time to identify what they are and understand how to put them to use.
Continuous delivery has become the heir apparent to the Agile methodologies that successfully disrupted traditional software development decades ago and which have continued impacting the industry ever since then.
In fact, this disruption will continue right on through 2019, too.
As author Jez Humble explained in Continuous Delivery: A Reliable Software Releases through Built, Test, and Deployment Automation, this approach repositions the entire software development lifecycle as a single process. As such, the vast majority – if not all – of it can easily be automated.
In 2019, expect to see even more companies adopt continuous delivery to:
• Accelerate time-to-market
• Build the right platform (the first time)
• Improve productivity and efficiency
• Launch more reliable releases
• Increase overall product quality
• Reduce overall costs
You can leverage this change at your company by treating software development as one single process. Then, apply Agile methods to it both by taking an iterative approach and looking for every opportunity to apply automation to the aforementioned areas where continuous delivery can help.
Artificial intelligence and machine learning will be one of this year’s most dominant trends in software development.
These twin technologies offer a seemingly endless list of benefits. Three common examples of where AI and machine learning can be applied to improve development include:
• Detecting threats and updating cybersecurity
• Finding opportunities for greater automation
• Collecting and preparing necessary data
However, don’t be surprised if 2019 is the year that AI and machine learning completely overhaul the entire process. If you combine a continuous-development approach with this technology, not only will developers be able to stay focused on the tasks that require human attention. They’ll also have better information and more development automation tools, like JFrog, Helm and Kubernetes for completing them.
If you’re looking for an easy place to get started with applying this technology, begin with using machine-learning bots for code reviews and code checking.
As your machine-learning bots gain more intelligence about these areas, their ability to carry out automated code reviews will only improve, leading to better and quicker deployments. Your actual developers will only need to spot-check their work to ensure quality.
After that, the sky’s the limit. Depending on your unique software-development goals, you can focus these bots on any number of different tasks.
Although these changes are very exciting, it’s also vital that you prepare for their ramifications. Now is the time for your development team to double-down on winning strategies and decide how they can apply them to the concepts above.
Adaptation is always critical to surviving evolution, but especially adept teams will turn it into their secret weapon.