The Inflectra Blog contains articles on all aspects of the software lifecycle.
September 8, 2026
Atlassian has announced that Jira Software Data Center and other affected Data Center products will reach end of life on March 28, 2029. At that point, impacted Data Center subscriptions and associated Marketplace apps will expire and become read-only. Atlassian's phased transition began in March 2026, giving existing customers a defined window to evaluate their options and migrate.
For many organizations, that sounds like a technology refresh. For aerospace and defense teams, it is a much larger operational decision.
Read MoreSeptember 3, 2026
September 2, 2026
It's not always about going live. When immutable audit trails are necessary for government bodies or highly regulated enterprise organisations, the biggest compliance trap in decommissioning is proving how data was handled. SpiraPlan simplifies this through its Auditability & Compliance architecture:
Customers have been using SpiraPlan to manage Product Launches and decommissioning for two decades, ensuring compliance and security.
Read MoreAugust 20, 2026
Yesterday, we spent the day with 180 engineering and technology leaders at the Sydney Engineering & DevOps Summit discussing one of the biggest questions facing software teams today:
As AI accelerates software development, how do we maintain the quality, control, and trust required to deploy it at enterprise scale?
Across roundtables and panel discussions, one thing became clear: AI has removed some of the traditional bottlenecks in software development, only to expose new ones.
Read MoreAugust 13, 2026
AI is not making quality assurance less important. It is expanding the QA mandate.
For decades, quality teams have focused on a familiar set of questions: Did the software meet its requirements? Did the integration work? Did a new release introduce a regression? Did the system produce the expected result?
Those questions still matter. But as organizations begin deploying generative AI and autonomous agents into production, quality leaders face an additional challenge: assuring systems whose behavior cannot always be specified in advance.
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