Decades ago, developers were solely responsible for code or design changes made to a system including testing and deployment in the field of software.
Dependencies were minimal so this ensured quick closure. In the era of specialization, numerous roles and functions evolved within organizations that included testers, managers, developers and also others for assistance during scaling to build large systems to optimize the effort.
However, this affected the production servers by slowing down the code moment due to multiple handovers and quality issues.
DevOps Challenges
To overcome these challenges around a decade ago several tools were advanced to automate the effort-required tasks that were manual like code reviewing against standards that were defined or test automation.
There was a need to bring in discipline despite the tool being successful to an extent. The formation of unified teams and the usage of more tools resulted in DevOps being recognized as a set of practices that combined development and IT operation a couple of years later.
2008 witnessed a downturn in the market with the competition being cutthroat. Businesses were looking for systems that could publish updates for the end-users faster and were always on the lookout to innovate their products and services constantly to retain and attract customers.
During this time, agile methodology was already gaining popularity for developing code faster.
Software development had two shortcomings due to the increase in the demand for speed by businesses which led to the real uptake in DevOps within the software industry. One of which was the added cost and the schedule overruns due to the numerous handover issues among the specialized functions including the manual errors.
Business logic saw a major loss in the translation as an outcome of a lack of cohesion between roles such as developers, testers, business analysts and deployment teams. The second shortcoming was that the tools were not being used to their full potential to obtain results in terms of quality improvement, speed and reliability.
Product companies that wanted speed without compromising quality were the early takers. DevOps suited these companies’ needs, as they were looking for faster and multiple releases. Retail and telecom companies followed their footsteps and adopted agile in their digital sales portfolio for faster market reach.
Several sectors in the finance and manufacturing industries saw a wider adoption of agile in their digital portfolios a few years later.
Why DevOps
Answering the age-old question of why DevOps matters, the answer is simple, Except for code development and test script writing DevOps automation meant using tools for nearly every other task in the software lifecycle.
Several tasks are involved in developing a software product like code analysis, developers testing units, functional performance and testers performing other types of testing, deployment stage-wise and release management.
These tasks were automated in an integrated manner with no mutual intervention and automated quality checks between each stage.
Investing in DevOps made sense to organizations once they realized that there was more to it than just achieving early time to market, it also saved organizations a lot of cost and effort. Highly reliable systems meant happy & loyal customers.
Businesses attracted end users through more frequent releases in turn increasing their sales. IT automation wasn’t alone benefitted by DevOps but it also impacted business growth and revenue.
DevOps is being adopted and expanded by most industries today. Organizations are including non-digital portfolios that provide support to their digital applications that ensure the entire value stream is faster, expanding their DevOps adoption. Through DevOps automation security checks organizations can avoid million-dollar losses due to fraud.
DevOps has still not reached its full potential. Application migration to the cloud and cloud-native development is picking up pace across industries, giving the spotlight to DevOps on the cloud. DevOps for SAAS, AI-ML code, and DevOps is gaining popularity.
Clients are leaning toward cloud-specific or cloud agnostic agile solutions. The increased usage of AI in DevOps automation and improvement in DevOps tools by product vendors shows promise in the emergence of intelligent and tools that are efficient. We can conclude that DevOps is here to stay.
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