If you already had some experience with Kamon, you probably saw Kamon create Spans automatically for a lot of stuff, including HTTP server requests, database calls, actor messages, and more. But what happens when you want to create Spans for methods or code blocks that Kamon doesn’t instrument automatically? Let’s look at the two simplest ways to create Spans programmatically with Kamon.

Logz.io is always looking to improve the user experience when it comes to Kubernetes and monitoring your K8s architecture. We’ve taken another step with that, adding OpenTelemetry instrumentation with Helm charts. We have made Helm charts available before, previously with editions suitable for Metricbeat and for Prometheus operators.

The OpenTelemetry project is an ambitious endeavor with of goal of bringing together various technologies to form a vendor neutral observability platform. Within the past year, many of the biggest names in tech provide native support within their commercial projects.

In microservices architecture, to identify performance issues—including latency—it’s important to monitor each service and all inter-service communication. Jaeger and VMware Tanzu Observability can help. Jaeger is an open source, distributed tracing system released by Uber Technologies. VMware Tanzu Observability is a high-performance streaming analytics platform that supports 3D observability (e.g., metrics, histograms, and traces/spans).

In this article we discuss the origin story of Kamon’s Range Samplers: what they are, how they work, and how we use them to monitor queues, connection pools and more.

It’s no secret that Jaeger and OpenTelemetry are known and loved by the open source community — and for good reason. As part of the Cloud Native Computing Foundation (CNCF), they offer one the most popular open source distributed tracing solutions out there as well as standardization for all telemetry data types.