Machine Learning to Bring a Transformation in Software Testing

The test automation effort will continue to accelerate. Surprisingly, a lot of businesses do have manual checks in their distribution pipeline, but you can't deliver quickly if you have humans on the vital path of the supply chain, slowing things down.

FREMONT, CA: Over the last decade, there has been an unwavering drive to deliver applications faster. Automated testing has emerged as one of the most relevant technologies for scaling DevOps, businesses are spending a lot of time and effort to develop end-to-end software delivery pipelines, and containers and their ecosystem are keeping up with their early promise.

Testing is one of the top DevOps monitors that companies can use to ensure that their consumers have a delightful brand experience. Others include access

 management, logging, traceability and disaster recovery.

Quality and access control are preventive controls, while others are reactive. In the future, there will be a growing emphasis on consistency because it prevents consumers from having a bad experience. So delivering value quickly—or better still delivering the right value quickly at the right quality level—is the main theme that everyone will see this year and beyond.

Here are the five key trends in 2021:

Automation of exams

The test automation effort will continue to accelerate. Surprisingly, a lot of businesses do have manual checks in their distribution pipeline, but you can't deliver quickly if you have humans on the vital path of the supply chain, slowing things down.

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Automation of manual tests is a long process that takes dedicated engineering time. While many companies have at least some kind of test automation, much needs to be done. That's why automated testing will remain one of the top trends in the future.

DevOps-driven data

Over the past six to eight years, the industry has concentrated on linking various resources through the development of robust distribution pipelines. Each of these tools produces a significant amount of data, but the data is used minimally, if at all.

The next stage is to add the smarts to the tooling. Expect to see an increased focus on data-driven decision-making by practitioners.