Cloud computing, the technology that helped carry global supply chains and remote workforces during the coronavirus pandemic, will continue to be an essential target for organizations looking for increased scalability, business continuity, and cost-efficiency in 2021. The effects of COVID-19 will linger throughout the year as businesses look to lay a foundation for increased agility
Enterprises’ technology needs have increased in complexity over the past year, as workplaces quickly became decentralized during the pandemic, with remote workers worldwide. In computer programming, these schemes have been working for years. Nonetheless, they have changed during the past 12 months. What are those changes, and how will they integrate into our future?
To the Cloud
Moving to the cloud is modifying the usual processes in technological environments, also affecting programming. With the jump to the cloud, terms such as Platform-as-a-Services (PaaS) and Software-as-a-Service (SaaS) emerge, which offer layers of abstraction that facilitate the development and deployment of software. They help programming firms focus on the product without worrying about the details of the infrastructure.
However, this is not a significant change for programming languages. The roles most affected by this change are those of DevOps, systems administrators, or system architects.
The adaptation to the cloud seeks to unify, in essence, all the trends of the software life cycle with new functionalities, such as the Internet of Things (IoT) or artificial intelligence (AI). Nonetheless, the implications can have a high impact on development costs in specific scenarios, such as the Microsoft Azure decision, with in-house programming language applications, rather than greater flexibility.
A Better Workflow
But there is one big positive: this transition can only bring creativity and optimization to development teams by implementing the microservices architecture, which will provide greater efficiency and add value to the technical layer. Likewise, the settlement of the stack belonging to the DevOps environment can affect those environments that are not so up-to-date.
Davide Cortellino, a senior marketing data insights analyst from SAS Spain, points out that “increasingly, the production of data models is related to implementations carried out with cloud providers such as Microsoft Azure, Amazon Web Services (AWS) or Google AI Platform, because these services allow end-to-end management of the entire analytical life cycle in the pipeline, almost fully automated ”.
In this sense, he explains that “the fact that most of these technologies already integrate the most popular programming languages facilitates the transition from on-premise solutions to the cloud, without depending on the tools and languages used.”
The pervading view among industry watchers and stakeholders seems to be that the pandemic is likely to have a lasting impact on how enterprises view cloud technologies and their willingness to deploy them.
This coming year will be an opportunity for companies to look at what they have done so far, see what went well and what could be optimized, and then make any necessary adjustments.
