Operations | Monitoring | ITSM | DevOps | Cloud

Discover why hiring DevOps engineers may not be the only path for mid-size companies scaling their teams. Explore how automation tools like Qovery can reduce costs, boost productivity, and streamline infrastructure and deployment.

Co-authored with Julie Muzina A year ago, during our Madrid Engineering Sprint, we challenged ourselves to dramatically reduce, or even eliminate, the need for constant design involvement in the day-to-day creation of web pages. Our strategy for achieving this is based on a smarter, more structured approach to content.

There is a huge amount of hype around AI. Companies are growing faster than ever, IT budgets are being redirected, and product roadmaps everywhere are being redrawn. There is no doubt LLM’s are a transformative technology. At the same time, as with any early technology cycle we are far from understanding the patterns of success. And for sure, mis-steps and bad takes abound.

Tableau database connectors are changing the narrative of how to work with data from your dashboard. A few years ago, the ability to pull data from almost any source, including your company’s internal database or even a web API, and immediately convert it into powerful, interactive dashboards sounded too good to be true. Today, with Tableau database connectors, you can pull data from virtually any data source and convert it instantly into a powerful dashboard.

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.

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.

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.

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.

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.

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.