Splunk announced the new Splunk Observability Cloud, the full-stack, analytics-powered and enterprise-grade Observability solution.
The digital world is witnessing changes related to mergers and acquisitions, data and analytics, rollouts of apps, mobile commerce, and cybersecurity, among others. These are reshaping the expectations of customers by increasing their appetite for high-quality products. The changed reality is making enterprises grapple with performance, cost, and outcomes. In doing so, they are increasingly adopting Agile and DevOps methodologies.
With quality becoming the sole differentiator in delivering superior user experiences, mere shift-left testing is not sufficient. In order to present value to the customers, quality testers are moving away from a quality-driven approach to one driven by software quality engineering.
Why Digital Quality Engineering?
When quality is the centerpiece of any IT system and is responsible for driving customer satisfaction and growth of any business, traditional QA principles are not enough. Digital quality engineering is all about re-imagining quality by integrating industry expertise, end-to-end workflow, innovation, automated technologies, and the culture of an organization. It helps enterprises to adapt to technology changes, increase the quality of product/service and its speed of delivery, and deliver a better customer experience.
On one side, when we have the advent of new technologies and methodologies, on the other, we have enterprises struggling to stay afloat with legacy systems. With a staggering number of companies going bust, the focus has duly turned towards maintaining quality. And to ensure the delivery of quality products within quick turnarounds, there is a need to implement a dedicated end-to-end workflow integrated with QA at every step of the way.
Software quality engineering is about streamlining the SDLC by breaking silos around teams. Further, it smoothens the build-test-deliver pipeline and establishes a continuous feedback mechanism. A software quality engineer integrates quality into the code itself rather than testing the same post-development.
As the pace of digital technologies grows rapidly, enterprises should bring about a change in their culture or outlook. This means adopting a proactive approach to issues rather than a reactive one. The net result of ushering in a change in culture (along with streamlining the processes) includes high product quality, better customer experiences, reduced testing costs, and faster time to market. Let us understand how implementing quality engineering solutions can lead to qualitative improvement in various parameters.
Benefits of Implementing Software Quality Engineering
The three parameters upon which the success of a digital enterprise depends — quality, cost, and time — can be managed/assured by using a quality engineering process. The benefits are as follows:
■ Reduced risks and vulnerabilities: In a siloed system, any glitch in the codes can be overlooked by teams running to fulfill their immediate deliverables within expected timelines. Such a glitch or vulnerability can impair the overall quality of the product. However, in a quality engineering process with better end-to-end visibility, the likelihood of glitches remaining undetected is remote. The best part is that such glitches are identified early in the development process and mitigated, thereby eliminating the chances of any rework.
■ Improved productivity: In traditional QA, iterative processes done manually can leave a lot of scope for the ingress of errors. Also, manual testers may not conduct comprehensive testing for every variable or parameter. The result — erroneous codes flowing through the system and defective products being delivered to the users. A robust quality engineering strategy can involve the use of automation in testing iterative processes. This can relieve testers from the labor-intensive testing process who can then be deployed in other productive works. Further, in manual supervision of the testing process, a human eye can miss any telltale signs of errors. However, test automation enabled through QE can identify such signs leading to better detection of errors.
■ Enhanced brand equity: A software product with glitches is likely to leave the user dissatisfied and annoyed. Further, these glitches can lead to adverse consequences for the user like data breaches and loss of information. A disgruntled user can spread the news about the quality of software and brand in no time. This can lower the credibility of the brand in the market, minimize sales, and invite lawsuits and regulatory censure. But a QE-driven product pipeline delivering superior quality products can lead to enhanced brand equity.
Software quality engineering services can deliver a near-perfect quality product in a market driven by highly-discerning customers. Instead of focusing on detecting glitches, QE is about implementing a streamlined build-test-deliver pipeline where glitch-free codes can become non-existent.