Operations | Monitoring | ITSM | DevOps | Cloud

In our previous posts (Part 1 & Part 2), we covered how Linux coredumps are structured, how they’re collected, and how we could reduce the size of them to fit on systems with less memory. In this post, we’ll go over a method of coredump collection that does the stack unwinding on-device.

Frederik Van Leeckwyck is the co-founder and CRO at Factry. He oversees go-to-market activities and ensures their software solutions align with real factory demands. Passionate about open technologies, he believes in making data-driven insights accessible to everyone in the factory. Factories today are often rich in process data, but poor in insights.

Running apps in production? You need visibility fast. Traditional logging gives you scattered events. Prometheus gives you structured, queryable data that scales. In this guide, we’ll break down how to use Prometheus for logging-style observability, where it fits in your stack, and how to plug it into tools like Grafana or your cloud-native setup.

Today, managing a data center requires striking a balance between cost, security, and performance. Long-term costs are a different matter, even though upfront capital expenditures (CapEx) like real estate and hardware are well-known and reasonably predictable. According to industry surveys, operational expenses (OpEx), which include system provisioning, patching, compliance, and troubleshooting, steadily increase over time and frequently exceed 50% of total cost of ownership (TCO) by the third year.

Large Language Models (LLMs) are now at the cutting edge of mainstream AI systems. Their impact has been seismic, sparking a new gold rush as application developers transform the user experience away from clicks and commands into natural language and advanced automation. However, application developers have a barrier to overcome. AI models need data to reason and respond to a particular application domain.

The boundaries of what organizations build internally and what they adopt externally have blurred. Developers routinely integrate third-party services into critical CI/CD pipelines, often with minimal friction and limited oversight. This rapid plug-and-play convenience, while key to modern engineering velocity, is also quietly expanding the attack surface in ways many teams struggle to track - let alone govern.

GitLens 17.2 is here with a comprehensive set of improvements designed to enhance how you work with Git. This release introduces Commit Composer – AI-powered commit organization, refines the Home View experience based on your feedback, expands AI model support, and delivers enterprise-grade security controls for teams using AI features. Let’s explore what’s new and how these features can improve your development workflow.

AWS remains the largest cloud service provider (CSP) of the 21st century. It also provides over 240 cloud-based products and services. In some cases, these services help customers like you collect, analyze, and act on data about cloud usage and related costs. In this post, we explore how AWS services support FinOps’ best practices, including the features they offer. If you are looking for even more robust AWS FinOps tools, we will also include third-party platforms.

Fluentd and Fluent Bit are both open-source data collection and processing tools, but they serve different purposes. Fluentd offers a comprehensive, plugin-rich architecture ideal for centralized log aggregation. Fluent Bit is designed for performance and efficiency, making it a better fit for edge devices and environments with limited resources. This Fluentd vs Fluent Bit comparison outlines their key differences, helping you decide which fits your infrastructure best.