Operations | Monitoring | ITSM | DevOps | Cloud

We’re excited to announce the launch of parent/child pipelines for Bitbucket Pipelines. This powerful new capability lets you define a step within a pipeline that triggers and encapsulates a whole other pipeline, which can help to streamline more complex workflows into modular pieces and achieve greater parallelism within your pipeline.

The data center industry’s rapid evolution requires innovative tools to address its ever-changing demands. Cloud-based Data Center Infrastructure Management (DCIM) solutions have emerged as a powerful alternative to traditional on-premise systems, offering unmatched scalability, cost savings, real-time monitoring, and AI-driven insights.

LLM-powered apps are growing fast, and frameworks like the Vercel AI SDK make it easy to build them. But with AI comes complexity. Latency issues, unpredictable outputs, and opaque failures can impact user experience. That’s why monitoring is essential. By using OpenTelemetry for standard instrumentation and SigNoz for observability, you can track performance, detect errors, and gain insights into your AI app’s behavior with minimal setup.

Inventory management is a critical function for any organization. Many small businesses begin with Excel inventory management because it’s accessible and low-cost. While inventory management in Excel may work in the short term, it quickly becomes inefficient as your operations grow.

We’re happy to announce that our Trace Export Plugin for MPLAB X IDE has been updated to version 2.3.1 and now supports the latest versions of Microchip’s IDE, including MPLAB X v6.20 and v6.25. This plugin enables saving trace files from Percepio’s TraceRecorder library via the MPLAB X IDE debugger, making it easy to open the trace in Percepio Tracealyzer and related tools.

You don’t need to be a power user to get powerful results. I’m not training models or prompting GPTs into poetry—I’m just using them to do what great managers already try to do: communicate clearly, prioritize outcomes, and lead with intention. Over the last few quarters, I’ve built a handful of custom GPTs to support my weekly, monthly, and quarterly workflows.

Working in front-end development involves writing features and bug fixes in different branches. But how do you ensure that reviewers, testers, and other stakeholders find it easy to view changes? Using preview deployments is one solution. Preview deployments allow you to automatically create a live URL each time someone opens a pull request (PR). It’s like giving every branch its mini website so that changes can be tested and proven in isolation.