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


Tracing with InfluxDB IOx

Tracing has always been a key use case for time series data. But admittedly, it’s also one that past versions of InfluxDB could not handle as well as we wanted. One of the roadblocks was the cardinality issue. Tracing data is, almost by definition, high cardinality data and prior to InfluxDB IOx, high cardinality data could affect query performance.


A Modern Guide to Distributed Tracing

You’ve probably heard of Distributed Tracing -- it’s a form of application telemetry, sometimes referred to as a “pillar of observability” alongside metrics, and logs. You might be familiar with tools like Jaeger and Zipkin, which are open source trace storage and analysis tools -- they help you visualize and search for distributed traces. Perhaps you know of OpenTelemetryOpenTelemetry, an open source standard on instrumenting software to create distributed trace data?


TraceQL: a first-of-its-kind query language to accelerate trace analysis in Tempo 2.0

The much-anticipated release of Grafana Tempo 2.0, which we previewed at ObservabilityCON 2022, will represent a huge step forward for the distributed tracing backend. Among the biggest highlights will be TraceQL, a first-of-its-kind query language that makes it easier than ever to find the exact trace you’re looking for. There’s supposed to be a video here, but for some reason there isn’t. Either we entered the id wrong (oops!), or Vimeo is down.


Seeing vs. Understanding - The Power of Visualization

It’s common in our everyday language to conflate seeing and understanding when the two are actually very different things. For example, if every day for the last few years we spoke briefly and wrote down the total number of Covid cases in the world, it would be easy to see some trends in the data—you would see the data. But if we present the same data drawn as a chart, it’s easy to understand where the spikes and dips are and when the situation got really bad.


AppSignal for Node.js 3.0 Introduces OpenTelemetry Support

After a period of beta testing, we're happy to announce the launch of our latest AppSignal for Node.js package. This package features six new integrations and uses the OpenTelemetry framework for reliable telemetry data collection. OpenTelemetry is an open standard that facilitates the instrumentation of standardized telemetry data collection. AppSignal is committed to using OpenTelemetry in new integrations, and our Node.js integration is the first to use the standard.

vmware tanzu

Unified Observability: The Role of Metrics, Logs, and Traces

There is significant momentum around observability, as detailed in VMware’s 2022 State of Observability report, with almost all respondents stating that observability would benefit their organization. This is further validated by Gartner including observability in their Magic Quadrant for Application Performance Monitoring and Observability report for the first time this year.

Native OSS instrumentation: OpenTelemetry and the Future of Observability - Part 4

How does OpenTelemetry relate to open source software libraries? If you are an OSS maintainer, how should you provide observability for your end users? DM me there if you have any questions, or leave a comment below.

RedHat OpenShift monitoring with Splunk's OpenTelemetry Operator

Do you have an instant view of all the full-stack automated operations in your OpenShift environment. Would you like to monitor your self-service provisioning as code, to better understand health and performance? Have you been struggling to resolve service issues and reduce the time taken for troubleshooting across all your Kubernetes deployment? We’ve got you covered!

Jaeger vs. Helios: Which One Should You Choose?

OpenTelemetry (OTel), is an open source, CNCF (Cloud Native Computing Foundation) project that provides tools, APIs and SDKs for observability data collection (i.e, logs, metrics and traces) from cloud-native applications. Developers can use the data collected from OTel to monitor and analyze application health and performance. To leverage the data and its insights, you can export the data to external solutions, like APMs, open source Jaeger and Zipkin, Helios, and others.