DevOps and quality engineering enable better development practices and improve business resiliency, but many teams struggle to sustain this transformation outside of an initial proof of concept. One of the key challenges with scaling DevOps and quality engineering is determining how software testing fits into an overall business strategy.
By leveraging automated testing tools that collect valuable data, organizations can create shared goals across teams that foster a DevOps culture and drive the business forward. Testing data also helps tie quality engineering to customer experiences, leading to better business outcomes in the long run.
Creating Shared Data-Driven Goals
Collaborative testing is essential for scaling DevOps sustainably because it encourages developers to have shared responsibility over software quality. Setting unified goals backed by in-depth testing data can help every team involved with a software project take ownership over its quality. This collaborative approach helps break down the silos that have traditionally prevented organizations from scaling DevOps across teams.
More specifically, testing data and trend reports that can be easily shared across teams make it easier for organizations to maintain focus on the same core goals. Sharing this testing knowledge better aligns testing and development so that quality goals are considered throughout every stage of the software development lifecycle (SDLC).
When software-related insights can move seamlessly between developers, testers, and product owners, organizations can deliver a higher quality product faster than before. This reinforces the benefits of sharing responsibility for software quality and helps get more teams on board with DevOps and quality engineering throughout the organization.
In short, tracking testing data is crucial for setting goals that scale DevOps adoption across multiple teams and throughout the SDLC. Intelligent reporting and test maintenance also help quality engineering teams implement quality improvements that directly impact DevOps transformation and business outcomes.
Tying Quality Engineering to Customer Experiences
Sharing data and goals can help encourage developer participation with quality engineering efforts, but tying quality to customer outcomes can encourage investment in software quality from the broader organization. The key is using testing data to adapt quality engineering to new features and customer use patterns.
In our previous article, we discussed how quality engineering connects development teams to customers. A quality-centric approach can help retain customers and lead to a more resilient business over time because a poor user experience encourages them to consider a competitor’s product.
For example, tracking data from quality testing can reveal a decline in application performance before it’s noticeable to users. These types of changes can build up over time and be difficult to detect without data analysis. By sharing these data insights with the development team, however, the issue can be resolved before it leads to a poor customer experience. This means testing data forms an essential link between code and customers.
Actionable insights from testing data can drive a quality engineering strategy that makes a lasting improvement on customer experiences. And this leads to positive business results that encourages larger investments in software quality throughout the organization. Using data to tie software quality to customer experiences, therefore, endorses the role of quality engineering as a key part of DevOps adoption.
Sustainable Quality Engineering and DevOps
As organizations struggle to build sustainable DevOps practices, they should consider how they can leverage the quality engineering team as an enabler. Quality engineering teams have an enormous amount of testing data that can help development teams improve their processes for delivering high-quality software much faster.
However, testing data is only useful if it can be easily shared with the right stakeholders, whether it’s developers or product managers. This requires collaborative testing tools that integrate throughout the SDLC and empower teams to access data that improves their workflows related to software delivery.
In short, testing data can transform a small-scale adoption of DevOps practices into an organization-wide culture of quality. Data-driven collaboration helps align code to customers through shared goals and insights. Over time, this leads to stronger customer experiences and greater business resilience.
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