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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Built for More: Unlocking a Sovereign and AI-Driven Future

Join us as Civo's leadership team, including Mark Boost, Deshish Majrekar, Kelsey Hightower, and Josh Mesout, come together to share their vision for a new kind of cloud that prioritizes data sovereignty, simplicity, and flexibility. This session explores the challenges of traditional cloud infrastructure and how Civo is addressing them with its cloud native platform. Civo's Flex Core private cloud solution is also showcased, highlighting its applications in various industries, including cybersecurity and advanced materials design.

Implement Distributed Tracing with Spring Boot 3

A slow checkout request. A background job stuck waiting on another service. A log message that looks fine — until performance drops. In a Node.js microservices setup, these are the moments that test your observability. You know something's wrong, but tracing the request across dozens of services feels impossible. Distributed tracing changes that. It connects every span in the request's journey, showing exactly where time is spent and where things start to break down.

Announcing the AI chief of staff for engineering leaders

You see MTTR creeping up, but you don’t know why. You could ask your teams, but that means meetings, pulling people off projects, and waiting days for answers. What if you could just…ask? We’re excited to introduce the new strategic AI chief of staff for engineering leadership, powered by the Cortex MCP. By connecting your Engineering Intelligence data with your scorecards and standards, the MCP allows you to have a strategic conversation about your organization’s performance.

Your metrics, your way: Announcing custom views in Engineering Intelligence

Every engineering organization measures success differently. A dashboard that’s perfect for one team might be meaningless for another. While out-of-the-box views for DORA are a great starting point, leaders need the ability to define and share the specific combination of metrics that matter most to their business. Without this, you're either forcing your teams to conform to generic reports or wasting time rebuilding the same views every week.

Understand how AI is affecting your engineering team with Cortex's AI Impact Dashboard

Rolling out a powerful AI tool like GitHub Copilot is a big win for any engineering leader. But because it’s such a significant investment, leadership will inevitably ask if it was worth the cost. Until now, answering this was nearly impossible. While GitHub provides adoption stats, connecting that data to real-world performance metrics like cycle time or code quality has been a manual, frustrating process. We built the Cortex AI Impact Dashboard to provide a clear answer.

Industry Reports Agree: DevOps is the Key to Unlocking AI's Potential

Recent industry research shows that AI is accelerating code creation, but having mixed results downstream. They also show that better platforms and pipelines yield better outcomes for teams adopting AI for coding. Every engineering leader I talk to is asking the same questions about AI coding assistants: How much faster can we ship? How much more productive can my developers be? On the surface, the answers look pretty good.

Building LLM agents to validate LangGraph tool use and structured API responses

Transitioning LLM agents from intriguing prototypes to reliable, production-grade solutions introduces a unique and significant challenge: the inherent stochasticity of LLMs. Unlike conventional software, where inputs predictably yield precise outputs, an LLM’s response can exhibit variability even when presented with identical prompts. To ensure the dependability of your LLM agent, you will need a rigorous validation strategy.