Generative AI is dissolving the economic logic that made standardized enterprise software the only practical choice for most companies. What replaces it will be shaped not just by the rapidly evolving capabilities of this new technology, but by leaders willing to ask a harder question: Which workflows do we actually need to own?
"Snowflake gives customers one place to bring their data together, connect the systems they rely on, and turn AI into something that actually helps teams get work done," says Baris Gultekin, VP of AI at Snowflake.
Red Hat OpenShift on Google Cloud Dedicated is designed to address several key pillars of digital sovereignty: data residency, technological autonomy, and supply chain resilience. With isolated infrastructure, it must comply with regulations such as the GDPR and regional sovereignty rules.
Almost a quarter of those surveyed said they had experienced a container-related security incident in the past year. The bottleneck is rarely in detecting vulnerabilities, but mainly in what happens next. Weeks or months can pass between the discovery of a problem and the actual implementation of a solution. During that period, applications continued to run with known risks, making organizations vulnerable, reports The Register.
Modern web applications are no longer just "sites." They are long-lived, highly interactive systems that span multiple runtimes, global content delivery networks, edge caches, background workers, and increasingly complex data pipelines. They are expected to load instantly, remain responsive under poor network conditions, and degrade gracefully when something goes wrong.
Industry professionals are realizing what's coming next, and it's well captured in a recent LinkedIn thread that says AI is moving on from being just a helper to a full-fledged co-developer - generating code, automating testing, managing whole workflows and even taking charge of every part of the CI/CD pipeline. Put simply, AI is transforming DevOps into a living ecosystem, one driven by close collaboration between human judgment and machine intelligence.
The Harness Resilience Testing platform extends the scope of the tests provided to include application load and disaster recovery (DR) testing tools that will enable DevOps teams to further streamline workflows.
