Systems | Development | Analytics | API | Testing

At Assurity Consulting, our experts are deeply experienced in leveraging a variety of industry-leading Test Management tools, with Xray for Jira being a prominent example in our toolkit. Our commitment, however, extends beyond proficiency in a single platform. Our core approach is fundamentally tool-agnostic, meaning we prioritize the client’s unique context, goals, and technological ecosystem over allegiance to any specific vendor or solution.

Xray has won the Atlassian Marketplace Partner of the Year 2026: Software Collection Apps, recognizing its continued contribution to the Atlassian Marketplace and its role in supporting software teams with native test management inside Jira. The award was announced in Anaheim during Atlassian Team ’26, as part of the Atlassian Marketplace Partner Awards celebrations recognizing outstanding partners across the Atlassian ecosystem.

The first-ever Sembi Software Quality Pulse Report is based on nearly 4,000 responses from QA engineers, developers, security professionals, and engineering leaders worldwide. The findings paint a picture of an industry in motion—and a QA function that increasingly relies on tighter integration, thoughtful AI adoption, and better-connected workflows to keep up. Here's a look at some of the data that matters most for agile QA teams working inside Jira-native environments. TL;DR.

Over the past few years, Easysecrets has established itself as a trusted partner within the Atlassian ecosystem. Beyond consistently delivering efficient solutions through strong development capabilities, the company has also built a reputation for offering a diverse and innovative portfolio tailored to evolving customer needs. When discussing Atlassian, it is impossible not to mention Jira.

DevOps has transformed how quickly software can be delivered, but speed alone does not guarantee resilience. As organizations scale, their systems become increasingly interconnected, with more services, more dependencies, and more edge cases that must be considered in every release. What once felt manageable with a handful of regression tests can quickly become opaque when dozens of teams are contributing to the same ecosystem1.

In modern software development, speed is no longer the biggest challenge. Most organizations have adopted agile practices, CI/CD pipelines, and automation frameworks that enable rapid delivery. What slows teams down today is uncertainty. Stakeholders constantly face critical questions: When answers rely on scattered reports, manual interpretation, or partial visibility, decision-making becomes reactive, leaders will hesitate.

Test automation is widely recognized as essential to modern delivery; it enables faster feedback, supports CI/CD practices, and increases release confidence. Yet in many organizations, automation growth lags behind development velocity. The reason is rarely a lack of intent. It’s the effort required to convert validated manual tests into automation scripts.

As organizations embed Quality Assurance into their SDLC with Jira and Xray, the resulting test data becomes a strategic enterprise asset, vital for product quality, test case traceability, and regulatory compliance. Protecting this asset is paramount, and as its scale and importance grow, organizations require specialized data management capabilities that go beyond standard application features to ensure complete resilience and governance.

Test automation is essential for modern software delivery. It supports faster feedback loops, strengthens release confidence, and enables continuous integration at scale. Yet despite its importance, many teams struggle to expand automation at the pace they need. The biggest obstacle is not validating functionality. It is converting structured manual tests into actionable automation scripts. Manual tests already represent validated logic.

Software development has never been faster, yet it has never felt more fragmented. QA, development, and product teams often chase the same goals from different directions. Deadlines tighten, requirements shift, and communication gaps lead to rework or misaligned expectations. While DevOps practices have bridged some of those gaps, true collaboration remains a challenge.