DEVOPSdigest

As companies move to more agile development, automated testing and process discovery will be critical to their ability to achieve innovation and success. Nearly 90% of software development teams have adopted agile and adoption is spreading throughout the organization, including IT, where close to two-thirds of teams have adopted it.

Speed and agility are essential for business success today and DevOps is enabling businesses to build better products and services and keep pace with today's ever-evolving customer. Without the right tools for automated testing and process discovery, however, it's unlikely that a DevOps strategy will produce the desired results.

AI and ML Drive ROI in Process Discovery and Automated Testing

Process discovery provides businesses with visibility across application workflows, enabling them to prioritize the tasks that are most frequent and time-consuming. It also takes the guesswork out of not just what needs to be developed but also what needs to be tested, it also enables automated testing, which is the ability to free up resources and shift timing to enable faster time to market and more innovative development. Together, process discovery and automated testing help businesses increase productivity across the DevOps workflow.

When artificial intelligence and machine learning are applied to process discovery and automated testing, DevOps can really take off and drive significant ROI. AI enables predictive testing, which alerts businesses if a process is succeeding or failing. With ML, businesses can ascertain what and why testing failed, fix it, and run the test again. Teams can release application updates faster, thereby responding more quickly to employee, customer, and market needs while driving results to the organization's bottom line.

As businesses move forward with DevOps, testing is crucial in successfully enabling new approaches to DevOps processes, such as shift left testing, shift left security and microservices.

Shift Left Testing

Shift left testing refers to the practice of doing more testing early on in the application development cycle, meaning every time teams update code, an automated test can be run too — before it even heads to quality assurance (QA). Traditional testing happened shortly before software goes into production, leaving teams in a difficult spot if bugs are discovered. Fixing a bug at that stage runs the risk of breaking other strands of code, throwing the project into delays and costing companies potentially millions of dollars.

With automated testing, shift left testing enables teams to identify and fix bugs earlier in the process, particularly when using continuous integration/continuous delivery (CI/CD) pipelines, which enable teams to apply application changes on a continuous basis. Process discovery is driving better shift left testing and speeding up the development cycle. It's not too long before AI is introduced to this testing process to enable predictive testing.

Shift Left Security

Similar to shift left testing, shift left security is the practice of moving security testing up earlier in the application development cycle. With the acceleration of cycles, security is often a bottleneck. Shift left security moves security more to the development teams, enabling them to work with security to put the right security guardrails in place for the application.

Automated testing enables teams to detect and fix external threats to applications, speeding up development cycles and reducing time to market.

Microservices

Microservices offer an effective way to break up an application to make it independent and easier to scale so it can meet the big-scale needs of today's businesses. Microservices not only enable scalable applications but stable ones. Microservices have become popular with containerization because they eliminate the need for big virtual machines to deploy applications.

Microservices let teams test their ideas and optimize their user experiences without requiring constant maintenance. The core of the microservices model is the ability to combine discrete functions in a way that optimizes alignment with business workflows — and to make changes quickly when new workflows are required. Test automation simplifies arriving at the right workflow.

As the demands on the business increase as customer expectations continue to escalate, agile DevOps presents a unique opportunity for businesses to speed up development without sacrificing quality or security. Automated testing and process discovery elevate the promise of agile DevOps, particularly as AI and ML become more of a factor in the development promise.