Today, modern software organizations’ requirements for DevOps tooling has become more sophisticated and bespoke. We hear from many customers that they are building large, complex systems to augment and extend their DevOps workflows in ways that don't work well with the tools they're using. This is why Bitbucket Cloud is on a mission to become the world's most extensible cloud SCM and CI/CD product.

As part of the graduation of custom merge checks from open-beta to general availability (GA) that is planned for late-April 2024, we're making a range of changes to several areas of the core Bitbucket Cloud workflow. This includes changes to the core pull request review and authoring experience, as well as changes to how merge checks are configured within a repository. Different changes will be relevant to different audiences, so feel free to use the navigation shortcuts below.

Deploying database code using pipelines in various CI/CD tools is a common practice among our customers who use Flyway. To enhance security and avoid hardcoding sensitive information like connection strings, they frequently employ variables and secrets in the pipelines.

There’s a common misconception about running workloads in the cloud: the cloud provider is responsible for reliability. After all, they’re hosting the infrastructure, services, and APIs. That leaves little else for their customers to manage, other than the workloads themselves…right?

Last week in Paris, at KubeCon EU 2024, platform engineering was the talk of the event. The topic had a full-day co-located event and also a dedicated track during KubeCon itself. Here’s what I’ve learned from sitting in keynote rooms and then standing at the Spot and NetApp booth till my knees hurt. (Spoiler: It was well worth it.)

🚨 To read the full findings from this research, visit The Machine Learning State of Play 2024 white paper. Are the challenges of deploying machine learning (ML) overshadowing its true potential in the modern workplace? Through our recent white paper , we spoke to 500+ developers who have experience working with ML systems to gain an understanding of the pain points faced by developers when using ML solutions.

Endpoint Management is so inherent to IT that it is canon in this industry, especially now that remote work is the new normal. Setting a robust system is paramount for any organization that relies on digital devices. These devices are connected to the corporate network and can access its resources, so the goal is to ensure that these devices are secure, compliant with company policies, and operating efficiently.

Jenkins pipelines play a pivotal role in achieving continuous delivery in software development processes. Continuous delivery (CD) is a software delivery approach aimed at ensuring that code changes are systematically and automatically prepared for release to production. In modern software development practices, CD pipelines streamline the process of building, testing, and deploying software, enabling organizations to accelerate software delivery and provide value to its customers.