Structured Logging

Learn structured logging through an executable example, then connect the small demonstration to production code.

Go’s log/slog writes messages with levels and named attributes. Structured fields such as request IDs and counts make events easier to filter than prose-only logging.

Logs often contain timestamps, so the example decodes JSON output and prints only stable fields.

Follow this diagram before executing the example. Check where a value or decision changes what runs next.

See the log/slog package documentation. Emit meaningful error context but redact or omit sensitive values.

This example is a complete program. Save it as main.go or paste it into the Go Playground.

Go code

package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"log/slog"
)

func main() {
	var buf bytes.Buffer
	logger := slog.New(slog.NewJSONHandler(&buf, nil))
	logger.Info("task created", "task_id", 42)
	var entry map[string]any
	if err := json.Unmarshal(buf.Bytes(), &entry); err != nil {
		panic(err)
	}
	fmt.Println("Level:", entry["level"])
	fmt.Println("Message:", entry["msg"])
	fmt.Println("ID:", entry["task_id"])
}

Output

Level: INFO
Message: task created
ID: 42

The JSON handler writes one structured record to the buffer. Decoding allows the program to report level, message and task ID without depending on the current timestamp.

• Do not log passwords, session tokens or personal data unnecessarily.
• Use stable field names so dashboards and alerts can query the logs.

Add a request_id attribute and print it after decoding the JSON log record.

Tip: Edit the example above, predict the output, and run the modified code to test your reasoning.

You have practiced Structured Logging in a small, self-contained program. The important habit is to predict what runs, inspect the actual output and distinguish the language rule from the particular example.

Before continuing, make sure you can explain the program to someone who has not seen it, including the line that changes its result.