Operations | Monitoring | ITSM | DevOps | Cloud

As a developer, you often face the challenge of retrieving information from multiple sources with different structures. What if you could create a single interface that automatically routes queries to the right data source? Imagine your application needing to answer both “What’s the population of California?” and “What are popular attractions in Hawaii?”.

The software development landscape has fundamentally shifted. Teams are shipping more value faster than ever, leveraging AI to generate code at unprecedented speed. But with this velocity comes equally dramatic complexity — small teams now face challenges that once belonged only to large organizations, while large organizations grapple with codebases that strain human comprehension. This complexity isn’t a bug — it’s a productivity opportunity to embrace.

We’re excited to announce that we are starting a phased rollout of Rovo Chat in Bitbucket Cloud today! It will be available to 100% of users by September 30th, 2025. To check if it’s available on your account, look for the Rovo Chat button in your top navigation. Rovo is Atlassian’s AI-powered teammate that helps you find what matters, learn faster, and take action right in your workflow.

AI has made it faster and easier to change a codebase than ever before. But in a system as complex and interdependent as modern software delivery, writing code has never been the biggest challenge. For most teams, the real constraint is getting that code safely into production. So while AI assistants and autonomous coding agents have dramatically accelerated the pace of change, for many organizations those changes are piling up against bottlenecks that were already slowing them down.

We’re excited to announce step metrics – a new capability coming to Bitbucket Pipelines to help you better manage and optimise your CI/CD workflows. Ever wondered what’s happening under the hood during your pipeline runs? Step metrics provide a window into the resource usage of your build and service containers. More specifically, step metrics let you monitor CPU and memory usage for each build and service container in your pipeline steps.

Vector databases allow you to store, manage, and efficiently query high-dimensional vector data, which are numerical representations of data like text, images, or audio. Pinecone is a fully managed vector database optimized for fast, scalable similarity search—to power a Retrieval-Augmented Generation (RAG) system. This allows you to enhance language model responses by grounding them in relevant context retrieved from your own documents.

Since 2018, the General Data Protection Regulation (GDPR) compliance has been an important milestone in the evolution of privacy laws for web application users across Europe. GDPR requires companies to obtain explicit user consent for data collection and processing, and only for specified, legitimate purposes. It’s a law based on principles of transparency and purpose limitation. This law applies to global companies dealing with EU citizen data, giving individuals control over personal data.