Value of traces and Grafana Alloy

Distributed tracing provides comprehensive visibility into how requests flow through your application architecture. Unlike metrics that show what’s happening and logs that show discrete events, traces reveal the complete journey of a request as it moves between services, databases, and external dependencies.

With distributed tracing, you can:

• Visualize request flows across microservices and distributed systems
• Identify performance bottlenecks and latency issues in specific services
• Understand service dependencies and their impact on overall performance
• Trace errors back to their root cause across multiple system components
• Optimize application performance by analyzing request patterns
• Monitor service-level agreements and user experience metrics

Why use Grafana Alloy for trace collection

Grafana Alloy combines the strengths of the leading telemetry collectors into one place. Whether observing applications, infrastructure, or both, Alloy can collect, process, and export telemetry signals to scale and future-proof your observability approach.

The following diagram illustrates the architecture and data flow of Grafana Alloy in a telemetry pipeline. It shows how Alloy acts as a single point for collecting and forwarding telemetry data.

There are multiple ways to send telemetry data to Grafana Cloud, but using Alloy offers several key benefits:

• Alloy supports collecting metrics, logs, traces, and profiles in a single agent. Instead of running separate agents, you can use one tool to simplify your configuration, deployment, and maintenance.
• Alloy has native pipelines for leading telemetry signals, such as Prometheus and OpenTelemetry, and databases such as Loki and Tempo.
• Alloy improves reliability and provides advanced features for Enterprise needs, such as clusters of fleets and balancing workloads. Alloy is inspired by OpenTelemetry pipelines, which you may already be familiar with.
• Because Alloy runs on a single agent to collect multiple telemetry types, it reduces memory usage, CPU overhead, and other operational complexities.
• Alloy uses modular components to perform a single task, such as retrieving or redacting secrets, collecting Prometheus metrics, or sending traces to Tempo. Components are chained together, creating a customizable pipeline that suits your project needs.

In the next milestone, you’re going to install Alloy into your local machine.