Operations | Monitoring | ITSM | DevOps | Cloud

In my role as Senior Observability Architect here at Grafana Labs, one of the things I focus on is making sure customers are getting the most out of our products. Recently, I noticed a trend where customers were struggling to get SAML authentication configured properly. They were getting stuck on some of the steps needed to configure the users key pair values, which allows users to log in with the correct roles assigned in Grafana.

Within the utility sector, a lot is changing. Utilities continue to pursue digital transformation, altering the way services are delivered and operations are managed. What hasn’t changed is the criticality of the services provided. These organizations deliver essential resources like natural gas, electricity, and water—services that we as consumers rely upon constantly for our comfort, sustenance, communications, and more.

Throughout this blog series, we’ve followed how AI reshapes network operations – from foundational data harmonization to real-time correlation, from contextual insights to agent-driven automation, and most recently, to conversational access through natural language interfaces. But we haven’t reached the final destination.

Containers have been with us for a while and are ubiquitous in the Secure Software Development Life Cycle (SSDLC). According to some reports, nearly 60% of organizations use containers for most or all of their production applications. It’s no surprise really, as containers provide consistency and standardization across the lifecycle while speeding up delivery pipelines. They revolutionized how we develop and deploy apps in the cloud and there is no sign of this changing anytime soon.

Companies using AI are expected to grow by 5.6% in 2025, pushing AI-driven business value to $4.9 trillion, up from $4.7 trillion in 2024, predicts Forrester. If this momentum continues, we won’t just see growth in AI adoption; we’ll witness a transformation in how businesses operate, opening doors to even greater innovation and long-term success.

Once upon a time in the world of metrics, Wavefront was a pioneer. Before Prometheus took over and tools like OpenTelemetry unified tracing and metrics, Wavefront brought something novel to the table: human-readable metrics with real-time querying and tag-based dimensionality. In enterprise environments running VMware or early microservices, it offered a scalable way to understand a system's behavior. But as the telemetry landscape evolved, many systems that spoke Wavefront were left behind.

Most CircleCI pipelines are configured to trigger automatically on code commits, but not every development scenario fits that model. Sometimes you need to trigger a build manually—to test pipeline changes, retry a flaky test, or run CI on a colleague’s branch—without the friction of pushing empty commits or navigating to the UI to manually trigger a build.

Security, operations, and development teams rely more and more on the ability to efficiently query logs. As these teams monitor the health, performance, and usage of their systems and investigate incidents, delving into log data can often be a matter of urgency.

If you use Checkly, eventually you'll be looking at alerts about something failing, and wonder how to debug a failed check. For most of us, the first thing we want to see is the video of a failed check run. Sometimes, though, our check doesn’t capture video. This guide will cover three common reasons a video doesn’t show up on a check run. This advice is general for Playwright as well as those running Playwright tests on Checkly.

In the race to deliver groceries in record time, traditional retail stores are undergoing a digital and operational transformation. At the heart of this shift are dark grocery stores—specialized facilities designed exclusively for fulfilling online orders. Unlike conventional retail outlets, these locations are not open to the public. Instead, they are optimized for speed, precision, and scalability, forming the backbone of the rapid delivery ecosystem.