Trajectory

As explained in gRPC Microservices in Go

Tracing records and correlates the path and timing of requests as they propagate through distributed components.

A trace records a request’s journey across distributed services. It groups the operations handling one transaction and carries request metadata until the request reaches its final service. section 9.1.1

A trace ID lets teams group request flows and investigate latency across downstream services. A trace can contain multiple spans, each representing an operation; spans can expose service, method, and client-or-server metadata. section 1.4.4 section 9.1.1

PlaceOrder trace

A PlaceOrder request can produce spans for saving to a database and calling the Payment service. Inspecting the trace ID and spans helps follow the request across those operations. section 9.1.1

Figure 9.1 Journey of a request

View the request journey as it crosses services and operations. section 9.1.1

How gRPC Microservices in Go covers it

How deep it goes

Defines traces and spans and explains gRPC span metadata, without detailing instrumentation setup.

Examples

Shows a PlaceOrder trace with database and Payment operations, plus gRPC span metadata.

What you can do after

Diagnose request latency by grouping operations with trace IDs and inspecting service-to-service flows.

How it connects

Connects traces with spans, metrics, logs, OpenTelemetry, and gRPC.

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Also explained in

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  Quarkus in ActionTracing data is telemetry describing the operations and timing of requests as they pass through application components and services.
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  AI Agents in Action, Second EditionAn execution history is a record of operations and attempts performed during an agent's task.
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  LLMs in ProductionModel tracing is the capture of operations invoked during a model execution to construct an intermediate computational representation.
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  Optimization Algorithms: AI techniques for design, planning, and control problemsA sequence of states and actions generated during an agent's interaction with an environment.
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  Reinforcement Learning from Human FeedbackAn episode is a finite sequence of interaction steps experienced by an agent during one trial.
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  Evolutionary Deep Learning: Genetic algorithms and neural networksAn episode is one complete trajectory of interaction between a reinforcement-learning agent and its environment, from an initial state to termination.
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  AI Agents and ApplicationsExecution history is the recorded sequence of workflow decisions, transitions, and intermediate states produced during graph execution.
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  Generative AI in ActionTracing is the technique of following a request through the operations and services involved in processing it.
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  Graph Neural Networks in ActionA time-ordered sequence of positions or states describing the evolution of an entity.
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  Build a Reasoning Model (From Scratch)A generated response trajectory sampled from the model, treated as one complete candidate output in policy optimization.
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  Build an AI Agent (From Scratch)An execution trace is a chronological record of events and intermediate activity produced during program or agent execution.
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  Google Anthos in ActionA rollout is the controlled deployment of a new application or service version and its progression toward the intended state.
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  100 Go Mistakes and How to Avoid ThemAn execution tracer is a diagnostic tool that records runtime events such as scheduling, synchronization, and processor activity over time.
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  Machine Learning Platform EngineeringTracing is the recording and correlation of operations across a system to reveal execution paths, timings, and intermediate results.
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  Platform Engineering on KubernetesTracing is the practice of recording and correlating the operations performed during a request across services and infrastructure.
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  Building LLM Applications with DSPyA history of language-model calls, candidate prompts, and the model's responses.

Compare how 19 books explain trajectory →

Related concepts

• spanhas part · A span is a record of an individual operation within a trace, typically including its timing, context, outcome, and relationships to other operations.
• observabilitypart of · Observability is the ability to infer a system’s internal state and behavior from its externally available outputs, such as logs, metrics, and traces.
• Jaegeruses · Jaeger is an open-source distributed tracing system for collecting, storing, querying, and visualizing trace data to monitor and troubleshoot distributed applications.
• OpenTelemetryuses · OpenTelemetry is an open, vendor-neutral observability standard and framework for instrumenting software and generating, collecting, and exporting telemetry such as traces, metrics, and logs.
• qualityused by · Quality is the degree to which an entity, process, or outcome satisfies relevant criteria or exhibits desirable properties.

This explainer was generated by Manning's knowledge graph from the text of gRPC Microservices in Go. The section links point to the parts of the book it draws on.