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

Anthropic Monitoring & Observability with OpenTelemetry and SigNoz

Learn how to implement end-to-end monitoring and observability for Anthropic (Claude) API-based applications using OpenTelemetry and SigNoz. In this video, we walk through instrumenting your Anthropic API calls, collecting traces, metrics, and logs, and visualizing everything in SigNoz to gain real-time visibility into performance, failures, and bottlenecks. You'll see how to move from basic logging to production-grade observability, so you can debug faster, optimize latency, and confidently run Claude-powered AI systems at scale.

Using AI to Instrument Applications with OpenTelemetry

OpenTelemetry is one of the best things that’s happened to observability in the last decade. It’s open. It has SDKs for every language that matters. It’s vendor neutral. The OTel community has been doing the hard work of standardizing how applications emit telemetry, so that you, the engineer, don’t have to learn five different agent formats to monitor five different services.

Building a CloudWatch metrics pipeline: parsing OpenTelemetry data

AWS delivers CloudWatch metrics in OpenTelemetry format via Firehose, but AppSignal uses its own internal format. Building the parser to bridge these two formats presented several technical challenges. The metrics arriving through this pipe power AWS automated dashboards. When AppSignal detects metrics from a supported AWS service, it creates a dashboard for it automatically, with pre-built charts grouped by category: compute, databases, networking, messaging, storage, and others.

One Collector, Two Teams: How Bindplane Bridges Security and Observability with OpenTelemetry

Observability engineers will spend weeks tuning instrumentation. Security engineers? They want a collector installed and logs flowing — yesterday. And that's actually the magic of OpenTelemetry + Bindplane: from day one you're routing firewall logs, endpoint data, server logs straight into your SIEM with zero instrumentation lift. One toolchain. Two teams. No silos. Filmed at Google Cloud Next '26 — Las Vegas bindplane.com#OpenTelemetry.

Contributing Distributed Partition Ownership to the Azure Event Hub Receiver

If you're running OpenTelemetry collectors against Azure Event Hubs, distributed partition ownership and checkpointing just got significantly better. Your fleet now self-organizes. Failover is automatic. Restarts don't lose data. Here's how we got here.

OpenTelemetry Fleet Management: Scalable Control

OpenTelemetry has turned observability pipelines into production infrastructure, but managing them at scale often creates a massive operational burden. In this demo, we show how Coralogix Fleet Management acts as the central control plane for your OTel ecosystem, providing the governance and orchestration required for modern DevOps. Stop the "manual marathon" of PRs and Helm upgrades. Move toward a safer, more predictable operating model where telemetry is consistent, audited, and scalable.

Turn Noisy Logs Into Structured Data with Uptrace Grouping Rules

Here are 3 YouTube title options plus a description optimized for technical/dev audiences: Same log pattern. Hundreds of useless groups. In this video, we show how to use Uptrace Grouping Rules to automatically turn noisy logs into structured, searchable data — without changing application code. You'll learn how to: Examples covered: Perfect for:#OpenTelemetry users, backend engineers, SREs, and anyone dealing with noisy logs.

Making Semantic Conventions Work for You With OpenTelemetry Weaver

Your dataset has hundreds of attributes. Some are self-explanatory: http.response.status_code, server.address. Others are not: meta.refinery.reason, dataset.slug, sli.latency_target_ms. If you don't know what an attribute means, you can't write a good query. And if an AI agent doesn't know what it means, it guesses.

Managing OpenTelemetry at Scale: Why OTel Pipelines Need a Control Plane

OpenTelemetry made telemetry possible everywhere – turning observability pipelines into distributed production infrastructure. Distributed infrastructure requires a control plane for inventory, governance, and safe change. At 500 collectors across hybrid environments, operational overhead becomes a production risk. The moment telemetry pipelines become a distributed infrastructure, they inherit the operational problems of one.