CodeRigor
Course map

FREE COURSE / REAL PRACTICE

Logs, metrics & debugging services

Investigate structured logs, metric support and trace fixtures; write a reproducible report that separates observations, hypotheses and limits.

Free lessons & exercises7 authored lessons3 units
Open the first lesson →Open the interactive course map

What you’ll work toward

Validate and correlate local telemetry fixtures, compute supported rates and latency summaries, reason about trace models and produce a redacted evidence-aware report. This course does not instrument or operate production services.

Read an explanation, inspect the diagrams and work through the available checks, debugging exercises and builds. Feedback and prerequisite links guide the next step.

Before you start

This course builds on these skills:

Individual lessons can add prerequisites. The course map shows your actual readiness.

A look inside the first lesson

Structured logs with a schema

Python 
import json
row = json.loads('{"service":"checkout","level":"warn","event":"request.failed","attributes":{"route":"/pay"}}')
print(row["level"].upper(), row["event"], row["attributes"]["route"])

Your course outline

Follow the lessons in curriculum order. Open a unit to preview the ideas you’ll work with.

UNIT 012 lessons Structured evidence & time
  1. LESSON 01.01

    Structured logs with a schema

    Parse a deterministic log stream into validated events without turning arbitrary text into evidence.

    Open lesson
  2. LESSON 01.02

    Time, context & correlation

    Normalize offset timestamps, retain ingestion lag and order correlated fixture events without claiming causality.

    Open lesson
UNIT 023 lessons Measured populations & trace models
  1. LESSON 02.01

    Counters, rates & denominators

    Turn cumulative snapshots into measured deltas and ratios with explicit reset and coverage policies.

    Open lesson
  2. LESSON 02.02

    Latency distributions & tail evidence

    Compute support-aware latency summaries, nearest-rank percentiles and cumulative threshold buckets.

    Open lesson
  3. LESSON 02.03

    Spans, overlap & critical paths

    Distinguish inclusive span time, uncovered parent time and longest dependency paths in explicit offline models.

    Open lesson
UNIT 032 lessons Triage & an evidence-aware report
  1. LESSON 03.01

    Alert signals, triage & safe context

    Evaluate sustained symptom signals without treating missing data as health or a correlated event as proven cause.

    Open lesson
  2. LESSON 03.02

    Capstone: an evidence-aware incident report

    Investigate deterministic log and metric fixtures, preserve source evidence and report uncertainty without inventing a root cause.

    Open lesson