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Level 10 / Project 10 - Executive Metrics Publisher

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Concept This project — Quiz Flashcards — —

Focus

  • Adapter pattern for normalizing metrics from different sources
  • KPI transformation with trend and health analysis
  • Pluggable report formatters via Protocol
  • Business-meaningful narratives from technical data

Why this project exists

Engineering teams track hundreds of metrics, but executives need concise answers: "Are we on track?" This pipeline bridges the gap by transforming raw technical data into business-meaningful KPIs with traffic-light health ratings, trend indicators, and natural-language narratives.

Run (copy/paste)

cd <repo-root>/projects/level-10/10-executive-metrics-publisher
python project.py
pytest -v

Expected terminal output

{
  "report_type": "executive_summary",
  "overall_health": "yellow",
  "kpi_count": 9,
  "categories": { "reliability": [...], "velocity": [...], "quality": [...] },
  "attention_needed": [...]
}

Alter it (required)

  1. Add a CostSource that tracks cloud spend, cost per request, and budget utilization.
  2. Add a TrendReportFormatter that groups KPIs by trend direction (improving/stable/declining).
  3. Add sparkline-style text indicators (up arrow, down arrow, dash) to the narrative.

Break it (required)

  1. Pass a target of 0 to a "higher is better" metric and observe division-by-zero handling.
  2. Create a KPI with no previous value and verify the trend is STABLE.
  3. Register no sources and call publish — verify the report is empty but valid.

Fix it (required)

  1. Add a minimum KPI count validation — report should warn if fewer than 3 KPIs are collected.
  2. Handle the case where all KPIs are RED — add an "executive alert" section.
  3. Test both fixes.

Explain it (teach-back)

  1. How does the Adapter pattern normalize metrics from different source systems?
  2. Why is "lower is better" handled separately from "higher is better" for health ratings?
  3. What makes a narrative more useful than a raw number for executives?
  4. How would you extend this to send reports via email or Slack?

Mastery check

You can move on when you can: - add a new MetricSource and see it flow through the pipeline, - explain the trend computation logic and its 5% threshold, - interpret the traffic-light health system (green/yellow/red), - describe how DORA metrics (deploy frequency, lead time, MTTR, change failure rate) map to this system.

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