Software Developers Face Mounting Pressure

Uploaded on 2021-01-12 in NEWS-Cybersecurity News, FREE TO VIEW, BUSINESS-Services-IT & Telecoms

Forrester Research predict that the world of software development is facing some big challenges in 2021, not least because of long-term remote working driven by Coronavirus will increase the importance of digital collaboration. 

Most software developers have proved  able to successfully adapt to these changes compared to other professions, however, working hours became longer  and workloads grew heavier. 

In 2021 Forrester expect there to be larger disruptions to the way development teams work, especially as the executive demand for new and modernised apps take business and development leaders outside their traditional comfort zones.

Agile scaling best practices emphasise the usefulness of cross-function, co-located teams. Physical co-location enables high-bandwidth collaboration, even with low-technology practices like Kanban walls and firesides. As the reality of remote working continues, digital tools that enable “spiritual co-location” will become more important. 

Developers will need to make better use of collaborative work and value stream management tools, as well as new cloud-based team enablers like shared code-spaces and pipelines.

Modernisation efforts will put pressure on developers to master new skills. Almost three-quarters of infrastructure and operations pros report that migrating existing apps to cloud platforms is a priority of their enterprise’s cloud strategy. It’s developers that will need to containerise and refactor these monoliths. Taking full advantage of Kubernetes-based container platforms requires developers to master new tools, architecture patterns, and technologies in order to deliver application modernisation benefits. 

Artificial Intelligence (AI) will drive more development automation and Forrester's prediction is that more than a third of developers will use machine learning in 2021 to automate development activities. 

Teams will use machine learning models to make test automation smarter, and natural language processing will be used to review test cases and eliminate duplicates, as well as identify gaps in test coverage. It all looks quite a steep learning curve for the software industry.

Forrester:      TechRepublic:      ZDNet:       Technology For You:

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