If you’re already familiar with distributed tracing, you know that spans are the building blocks of traces. But are you sleeping on what span events can do for you? First, you may need a wake-up call as to what a span event even is. While spans represent units of work or operation within a trace, a span event is a unique point in time during the span’s duration.

Let’s cut to the chase: Managing metric volumes at scale is hard. In fact, when we asked the open source observability community about their biggest concerns in this year’s Grafana Labs Observability Survey, the top four responses — cost, complexity, cardinality, and signal-to-noise ratio — can all be tied back to exponential growth in telemetry data.

As a site reliability engineer, you need constant vigilance and a keen eye for detail if you want to manage your Kubernetes infrastructure effectively. As part of that effort, you need to see the historical data from your pods, nodes, and clusters — even after they’ve been deleted or recreated. Many SREs rely on kubectl for this, and while it’s indispensable for real-time Kubernetes management, it presents some significant challenges with historical data.

Identity providers (IdPs) such as Okta play a crucial role in enterprise environments by providing seamless authentication and authorization experiences for users accessing organizational resources. These interactions generate a massive volume of event logs, containing valuable information like user details, geographical locations, IP addresses, and more. These logs are essential for security teams, especially in operations, because they’re used to detect and respond to incidents effectively.

As we continue adding to our growing catalog of more than 100 plugins for Grafana, we have been focused on developing data sources for Grafana that are more purpose-built for the respective technologies. One example has been the recent update to our core Prometheus data source. We have deprecated AWS authentication from the original Prometheus data source, and we created a new dedicated Amazon Managed Service for Prometheus plugin that will specifically cater to the AWS use case.

Grafana Alloy 1.3 is here! First introduced earlier this year, Alloy is our open source distribution of the OpenTelemetry Collector. It has native pipelines for OpenTelemetry and Prometheus telemetry formats, and it uses the same components, code, and concepts that were previously introduced in Grafana Agent Flow. This new release introduces live debugging, enhancing debugging capabilities across key components, which are the building blocks of Alloy.

Grafana began as an open and composable platform for data visualization. Today, Grafana has evolved into an all-in-one observability platform, providing everything from infrastructure and application performance monitoring to load testing and incident response. As organizations extend their use of Grafana, efficient and secure authentication and authorization is essential.

In the previous blog post in this two-part series, we discussed the critical signals you need to monitor in your Kubernetes environment to ensure optimal resource provisioning. These signals include high CPU and memory utilization, frequent pod evictions, slow application performance, and other indicators that your resources are over- or under-provisioned. Monitoring these signals is essential for maintaining an efficient, cost-effective, and environmentally sustainable Kubernetes environment.

Organizations that run Kubernetes clusters in cloud native environments should do so in a way that’s both operationally efficient and cost effective. However, many organizations don’t prioritize cost optimization until it becomes a pressing need. This may be due to a directive from senior leadership, a significant scale-up or migration of Kubernetes clusters, or an unexpected surge in the cloud bill.

Whether they’re for synthetic monitoring, large-language models, or some other use case, Grafana application plugins are a fantastic way to enhance your overall Grafana experience. Data for these custom experiences can come from a variety of sources, including nested data sources. However, they can also come from third-party APIs, which usually require authentication to access.