Bitbucket cloud is on a mission to become the world’s most extensible cloud SCM and CI/CD product, and we're thrilled to be able to share the next stage of that journey. Upcoming Webinar: Join us for a live-webinar on May 8th/9th, 2024 for a deep-dive into building your own Dynamic Pipelines. Today, we're announcing the release of a new capability in Bitbucket Cloud called Dynamic Pipelines.

Kubernetes troubleshooting is a critical skill for developers and system administrators managing containerized applications. It involves diagnosing and resolving issues within a Kubernetes cluster, ensuring that applications run smoothly and efficiently. Troubleshooting can range from simple configuration errors to complex networking issues, requiring a deep understanding of Kubernetes architecture and components.

What it means to be “enterprise grade” has changed. In software development, the size of new artifacts and the pace of development has increased dramatically. Developers are now releasing new components daily, if not multiple times a day. With containerization, and now AI/ML models, new pieces of software can be multiple GBs or larger.

It’s April 22 and everybody knows today is Earth Day. But do you know how much energy your IT infrastructure is consuming and what that translates to in cost and carbon footprint? As we place more demands on our IT infrastructure to store and manage the reams of data we’re collecting and run advanced analytics and artificial intelligence on that data, we are inevitably consuming more energy in our data centers.

Data centers are the backbone of our increasingly interconnected world. They power everything from streaming services to AI, handling vast amounts of data every second. However, this technological advancement comes at a cost, with energy consumption being a significant concern. In fact, data center energy consumption is forecasted to double by 2026. As we venture further into 2024, it is important to review some of the key trends around energy consumption in data centers.

In the digital era, where data reigns supreme, the ability to extract meaningful insights from vast datasets has become indispensable. Though we have many data sources and data processing languages, SQL (Structured Query Language) stands as a cornerstone in this realm, empowering analysts, and data scientists to navigate through intricate databases with ease.