Operations | Monitoring | ITSM | DevOps | Cloud

Here's something nobody talks about at the AI strategy meetings. Your organization just spent six figures on Cursor licenses, Claude seats, and Copilot subscriptions. Ninety percent of your engineers have access. By most internal measures, the rollout was a success. But somewhere on your team, one developer is running circles around everyone else.

We’re excited to announce that JFrog has officially earned the Microsoft Solutions Partner with certified software designation for Azure. This status is granted to partners who complete a technical review audit for interoperability with Microsoft products and demonstrate a consistent track record of customer success.

Regression testing is the practice of re-running existing tests after a code change to confirm that previously working functionality hasn’t broken. It answers a single question: did this change break something that used to work? In CI/CD pipelines, regression tests run automatically on every commit, giving teams immediate feedback before code reaches production.

Continuous delivery is only as good as your ability to understand what’s happening inside your pipelines. When a build is slow, flaky, or burning through capacity, you need more than a green/red status and a wall of logs — you need traces. Bitbucket Pipelines now exposes pipeline execution as OpenTelemetry (OTel) traces via webhook events. This lets you stream detailed pipeline spans into your own observability stack and correlate them with the rest of your system. This post walks through.

AI is creating an overwhelming surge of digital artifacts and software components. The key to success is learning how to ride, secure, govern, and manage that wave – rather than being overwhelmed by it. This weekend, I asked my team to watch Chasing Mavericks. Jay Moriarity (not J-Frog, but stay with me) was one of the most driven and determined surfers imaginable. His courage and spirit were extraordinary. But those virtues were shaped and refined by his mentor, Frosty Hesson.

More and more often, infotainment systems are being developed and delivered like software, yet often they are still tested and validated using hardware-centric processes. This is far from ideal: access to devices is limited, environments are difficult to reproduce, and iteration slows down as soon as multiple teams need to work in parallel. These challenges become even more visible as cockpit systems move toward wide displays and high resolutions.