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The latest News and Information on Distributed Tracing and related technologies.

Generating metrics from traces with cardinality control: A closer look at HyperLogLog in Tempo

While tracing is a critical component of any observability strategy, metrics — especially RED metrics (request rate, error rate, and duration) — are widely considered the gold standard for monitoring service health. Tempo, the open source, easy-to-use, and highly scalable distributed tracing backend, is well known in the OSS community for storing and querying traces. It can also, however, generate RED metrics directly from those traces using the optional metrics-generator component.

OpenTelemetry traces for Bitbucket Pipelines via webhooks

Continuous delivery is only as good as your ability to understand what’s happening inside your pipelines. When a build is slow, flaky, or burning through capacity, you need more than a green/red status and a wall of logs — you need traces. Bitbucket Pipelines now exposes pipeline execution as OpenTelemetry (OTel) traces via webhook events. This lets you stream detailed pipeline spans into your own observability stack and correlate them with the rest of your system. This post walks through.

Behind the magic of auto-instrumentation (Grafana OpenTelemetry Community Call)

You add the OpenTelemetry Java agent, restart your app - and like magic, observability appears. But is it really magic? What’s actually enabled by default? What telemetry should you expect to see? What’s missing? And what might you want to tweak, tune, or even turn off?
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SAP Application Performance Monitoring (APM): Beyond Generic Metrics

Your enterprise APM tool shows SAP is using 90% CPU. The dashboard turns red. An alert fires. Now what? You open Dynatrace. You see the Java Virtual Machine metrics for your NetWeaver stack. You see HTTP response times for your Fiori apps. You see a spike in database calls. None of this tells you why VA01 takes 45 seconds to create a sales order. None of this tells you which custom ABAP report is consuming memory. None of this explains the short dump that crashed your pricing routine. This is the gap between generic APM and true SAP application performance monitoring. Your enterprise tools see the symptoms.

Claude Code + OpenTelemetry: Per-Session Cost and Token Tracking

I was looking at our Claude Code spend in the Anthropic console the other day. Aggregate cost, aggregate tokens — no breakdown by developer, no breakdown by session. I knew my Hackathon team had been using it heavily on building out new features for the OpenTelemetry Distro Builder. But heavily how? I had no idea. Turns out Claude Code has been emitting OpenTelemetry signals the whole time. Per-session cost, token counts, every tool call it makes on your codebase.

Release v2.9: OTEL Logs, Database Functions, SNMP Functions and more.

What’s New in Netdata v2.9 In this video, we walk through the biggest updates in Netdata v2.9, including: Top Tab Database Functions to analyze slow queries and performance bottlenecks without logging into your database SNMP Network Interfaces Function for real-time visibility into network interfaces Microsoft SQL Server Collector with richer MSSQL metrics OpenTelemetry Logs Ingestion to correlate logs and metrics in one place.

What is OpenTelemetry and Why Do Organizations Use it?

Mining for information about environments is like trying to find gold. Looking for gold can be sifting through silty waters or blasting through a mine. In some cases, the gold nuggets are so small as to be almost invisible, some things look like gold but aren’t, and others are larger nuggets where the miner strikes it rich. Trying to understand how a distributed system works means sifting through vast amounts of telemetry, looking for patterns.

Turn Raw Data into Reliability by Changing Performance Perspectives

In a global microservices architecture, technical performance initially presents as a chaotic stream of disconnected telemetry. For a Technical Program Manager (TPM), success depends on the ability to move past these disconnected individual data points to identify stable patterns. If they have services entering critical states, looking at individual logs or traces is inefficient. Protecting system reliability requires an engine that can automate pattern recognition at scale.