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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.

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.

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.

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!

AppSignal's Future with OpenTelemetry

AppSignal is a strong supporter of open-source technology. We owe so much of our modern world to the unseen, hard-working software developers who build and maintain the many technologies that make everything from reading this article to sending a message from your phone possible. That's why we're investing in OpenTelemetry, the open-source standard for telemetry data collection, rather than developing our own independent standard.

Independence with OpenTelemetry on Elastic

The drive for faster, more scalable services is on the rise. Our day-to-day lives depend on apps, from a food delivery app to have your favorite meal delivered, to your banking app to manage your accounts, to even apps to schedule doctor’s appointments. These apps need to be able to grow from not only a features standpoint but also in terms of user capacity. The scale and need for global reach drives increasing complexity for these high-demand cloud applications.

Reduce Data Costs: Log Sampling with OpenTelemetry and BindPlane OP

Redundant logs are a common nuisance in observability pipelines of all kinds. In large environments, excess logs can multiply data costs to unsustainable amounts. Log sampling is the process of randomly sampling logs to produce the same valuable insight with dramatically reduced data flow. Configuring agents in a pipeline to appropriately sample logs can be a pain. Pipeline managers, like BindPlane OP, make that process simple and scalable.

5 Reasons Why OpenTelemetry is the Future of Observability

It has been said that open source is eating the world and in the observability space, the project behind this movement is OpenTelemetry. The project is quickly becoming the standard for instrumentation and collection of observability data. Why is an open standard and open-source approach to instrumentation and data collection so compelling? This talk will provide five reasons why OpenTelemetry is disrupting the observability market.

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!