Trajectory

As explained in 100 Go Mistakes and How to Avoid Them

An execution tracer is a diagnostic tool that records runtime events such as scheduling, synchronization, and processor activity over time.

An execution tracer records Go runtime events and makes them available for visualization. Use it to investigate performance and understand what happens while an application runs. section 12.8.2

A trace can help diagnose:

• Garbage-collection activity. section 12.8.2
• How goroutines execute and whether work is poorly parallelized. section 12.8.2

Spotting poor parallelization

Tracing a parallel merge-sort benchmark reveals many short goroutine executions and gaps spent orchestrating goroutines rather than running application code. Comparing it with a faster implementation shows longer executions and fewer gaps. section 12.8.2

$ go test -bench=. -v -trace=trace.out

Run a benchmark with tracing enabled to create a trace file for inspection. section 12.8.2

Figure 12.40 Too many small bars mean poorly parallelized execution.

Many short bars in the timeline indicate poorly parallelized execution. section 12.8.2

How 100 Go Mistakes and How to Avoid Them covers it

How deep it goes

Explains event capture and timeline interpretation, including goroutine activity, CPU gaps, and garbage collection.

Examples

Compares traces from two parallel merge-sort implementations to expose goroutine overhead and differences in execution.

What you can do after

Diagnose poor parallelization by capturing and inspecting a Go execution trace.

How it connects

Connects profiling with goroutines, garbage collection, and concurrency.

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  Grokking AI Algorithms, Second EditionAn episode is a complete reinforcement-learning trial consisting of the states and actions from an initial state until a terminal outcome.
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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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  gRPC Microservices in GoTracing records and correlates the path and timing of requests as they propagate through distributed components.
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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 100 Go Mistakes and How to Avoid Them. The section links point to the parts of the book it draws on.