Operations | Monitoring | ITSM | DevOps | Cloud

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.

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.

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.

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.

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.

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.

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.

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.

At Microsoft Build 2025, PagerDuty was featured in key announcements showcasing how intelligent agents and real-time automation redefine digital operations. From Microsoft Copilot to the launch of a new Azure SRE Agent, PagerDuty was highlighted as a strategic partner in enabling intelligent, scalable incident response.

Prometheus is supposed to help you monitor your stack, not become the thing you need to monitor. But if you’ve ever seen it spike in CPU and slow everything down, you know that’s not always the case. High Prometheus CPU usage usually shows up when you're scraping too many metrics, using expensive queries, or running with default configs that don’t fit your workload. This guide covers how to track Prometheus CPU usage, what typically causes it, and how to fix it.