Operations | Monitoring | ITSM | DevOps | Cloud

Shipping application code, especially for LLM-based applications, can be a stressful and complex task. These applications demand intricate model management, careful resource allocation, and manual handling of dependency conflicts. Traditionally, preparing such applications for deployment involves integration tests, containerization, and updating image registries: all time-consuming manual steps. This is where an automated CI pipeline becomes invaluable.

Sigstore’s Fulcio certificate authority now recognizes CircleCI’s OIDC tokens. This means you can sign container images and other artifacts directly from your CircleCI pipelines—without managing long-lived signing keys.

Every year is a big year for Bitbucket, but in 2025, we delivered transformative changes that cap off years of work to make Bitbucket Cloud the secure, scalable, cloud-first standard for large engineering teams around the world. Today, 15M developers build on Bitbucket, including all of Atlassian’s 10,000-strong engineering organization, and Bitbucket Pipelines runs more than 1 billion build minutes per month.

Stop managing complex YAML and plugin hell. Compare the top 10 CI/CD platforms for DevOps, from Jenkins to Qovery, and learn how to build high-velocity, automated pipelines on your own cloud.

Recently, we introduced autonomous validation as a new approach to CI/CD that brings adaptive, context-aware intelligence into the delivery pipeline. As AI increases both the volume and reach of code changes, teams are seeing more failures, longer queues, and rising maintenance costs. Traditional pipelines simply weren’t built for this level of velocity or variability.

Development teams depend on microservices to build, deploy, and scale features independently. Microservices have become the backbone of modern, scalable applications. Scaleway’s managed Kubernetes service (Kubernetes Kapsule) offers a powerful, cost-effective platform for running containerized workloads in the cloud. It’s a great fit for startups and solo engineers who want to focus on shipping features, not managing infrastructure.

In my previous posts, we discussed the where and the how of managing your ML assets. We showed you how JFrog Artifactory acts as a powerful, universal model registry (the “where”) and how the FrogML SDK serves as the gateway to get your models and metadata into it (the “how”). Now, let’s talk about the why.

Imagine being able to automatically detect when a high-value order is placed, then log it and notify your sales team – without manually accessing your app code. Azure SQL Trigger Functions make this possible. By automating the response to database changes as they happen, you can streamline operations, sync data, and power workflows in near real-time. Azure SQL Triggers, especially when combined with serverless functions, offers a powerful, low-maintenance way to respond to real-time data changes.

AI coding assistants have transformed how developers write and debug code. But there’s a gap: these assistants often can’t see what’s happening in your CI/CD pipelines. When a build fails, you’re still stuck switching tabs, hunting through logs, and copying error messages back into your editor. What if your AI assistant could talk directly to CircleCI? In this tutorial, you’ll learn how to connect Cursor, an AI-powered code editor, to CircleCI using the CircleCI MCP server.

Amazon Elastic Kubernetes Service (Amazon EKS) is a fully managed, compliant Kubernetes service that simplifies running, managing, and scaling containerized applications. EKS automatically handles the availability and scalability of the Kubernetes control plane, allowing teams of any size or skill level to focus on building and deploying production-ready applications across diverse environments, including AWS, on-premises, and at the edge.