Distributed tracing is a household term nowadays – if your house is an IT department! Modern enterprises use cloud-native applications for agility and responsiveness to customer needs. When monitoring cloud-native applications, distributed tracing follows how transactions perform while traversing services or containers in the backend architecture. By definition, we’re describing production applications with requests, methods, database calls and logs that accompany a transaction.

If you’re new to OpenTelemetry, like I was, you might be wondering how to quickly get started. OpenTelemetry is becoming the gold standard to collect all of your machine data and is changing observability as we know it. Instead of learning multiple technologies to collect all data, you can leverage a single cloud-native framework to complete your observability.

At Cisco and AppDynamics, we believe that OpenTelemetry™ is the future of observability. To that end, we’re working hard alongside the open source community to ensure the telemetry you collect can be leveraged to deliver the world-class business insights you need.

Nowadays, microservice architecture is a pattern that helps to innovate quicker by enabling easier scalability, giving language flexibility, improving fault isolation, etc. Systems built this way also bring some downsides. Moving parts, concurrent invocations, and different retries policies can make operating and troubleshooting such systems challenging. Without proper tools, correlating logs with metrics may be difficult. To overcome these challenges, you need observability.

Modern digital organizations have rapidly adopted microservices-based architecture for their applications. Microservices-based apps have components designed around business capabilities serving a specific purpose. It enables smaller engineering teams to own specific services that lead to increased productivity. But componentization also leads to complexity. Today’s modern internet-scale businesses have hundreds or thousands of microservices.

There are standalone distributed tracing tools like Jaeger, and there are APM tools that do not provide distributed tracing capabilities. In this article, we will see how distributed tracing complements an APM tool for a holistic performance monitoring experience. Both APM and distributed tracing are critical tools to understand the performance of your applications. And if your application is facing performance issues impacting customer experience, you need to understand what’s causing it fast.

This week we have turned on full trace retention search (beta) in Grafana Cloud Traces. This feature was also introduced in the recent release of Grafana Tempo v1.3. Previously, if you brought up your Grafana Cloud Traces data source, you were greeted with this message: This message simply warned the user that the Grafana Tempo search was calibrated for recent traces only, regardless of the selected time window.