DevOps might be a relatively young practice but the wow factor it brings, is making it hard to resist. Many of the organizations who wanted to reap the benefits but were cautious about taking the leap are now doing so. The allure of faster software deployments and high efficiency make it an attractive proposition despite the necessary attitude and culture change that comes with this type of ‘hybrid’ methodology. The gangly youth is growing into itself and as it continues its evolution there will be a greater adoption this year. So what is on the cards?
How about DevSecOps?
Security is always on the radar and this past year was no different particularly with the growth in cloud and DevOps, with many companies moving to the cloud in some capacity or another. So an amalgamation of all three was inevitable especially as code being released was at a much faster rate resulting in greater vulnerability to attack. Integrating security into the process is logical risk mitigating step. Now it has a hand in the entire IT arena instilling a security forward mentality that pervades everything. The consequences of this approach means speed and agility in security mechanisms and rapid detection of vulnerabilities, bugs and error.
What about using AI to automate?
It was a matter of time before the AI and data science model was applied to DevOps where it could help teams to determine CI or CD issues or even both. Predicting what the pipeline does would fuel improvements in an intuitive way, this can only push the outcome towards greater efficiency and faster software deployments, two things that make business leaders very happy. AI can provide data seamlessly to DevOps teams in very little time and allow them to focus on innovation.
Could a serverless architecture become a reality?
Once servers defined the landscape of computer architecture but the advent of the cloud has seen the move to a web-based server model. DevOps has invented this concept leading to improved developer productivity, faster deployment and enhanced scalability. Kubernetes might very well be leading the charge with its networking, service discovery, agile scaling, auto-scaling, load balancing and DNS management etc. It allows developers can easily share different software and applications with the IT operations team in real time, eradicating bugs and errors.
How does testing fit into the landscape?
The bottom line is it will become more intensive because it is necessary at each stage of the DevOps cycle as a long term strategy. This means automated testing will be the most effective way to tackle it. The QA team’s input has therefore increased in synchrony with this. QA needs to work in tandem with the DevOps workflow, they collaborate. Essentially QA feeds code into the production environment for the DevOps team to provide a smooth path ensuring all changes function as expected. QA and DevOps take a shared responsibility for ensuring quality. Specialized automation can help automate testing procedures through correct configuration leading to higher accuracy standards in DevOps.