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Project Instructions

WEDNESDAY: Complete Workflow Phase 1-3

Follow the instructions in ⭐ Workflow: Apply Example.

Complete:

  1. Phase 1. Start & Run
  2. Phase 2. Read & Understand
  3. Phase 3. Take Ownership

FRIDAY/SUNDAY: Complete Workflow Phases 4-5

Complete:

  1. Phase 4. Make a Technical Modification
  2. Phase 5. Apply the Skills to a New Problem

Topic

System assessment using continuous intelligence techniques.

In this project, you combine several techniques introduced earlier in the course to interpret the current state of a monitored system.

Continuous intelligence systems often:

  • measure system activity
  • transform raw data into useful signals
  • detect unusual behavior
  • summarize the overall state of the system

This project demonstrates how those steps work together.

Learning Objectives

After completing this project, you should be able to:

  • interpret signals that describe system behavior
  • detect anomalous conditions in system metrics
  • summarize system health using derived signals
  • communicate system state clearly through data artifacts and documentation

Example Code

The example file is located in:

src/cintel/continuous_intelligence.py

It demonstrates:

  • reading system metrics from a dataset
  • designing signals from raw system measurements
  • detecting anomalous signal values
  • summarizing system metrics
  • assigning a simple system health state

Run the example and review the code before creating your own version.

Dataset

The example dataset is located in the data/ folder.

Example fields include:

  • requests
  • errors
  • total_latency_ms

Each row represents one observation of system behavior.

Signals such as error rate and average latency help analysts interpret system performance.

Your Phase 4: Technical Modification Task

Using the example as a guide:

  1. Copy src/cintel/continuous_intelligence_case.py.
  2. Rename the copy to src/cintel/continuous_intelligence_yourname.py.
  3. Run your copied file to confirm it executes correctly.
  4. Make a small modification to the pipeline.

Examples of modifications include:

  • adding an additional monitoring signal
  • adding another anomaly condition
  • adjusting system thresholds
  • improving logging or output structure

Run the program again and verify that your modification works.

Phase 5: Apply the Skills

In this phase, apply the techniques from this course to your own monitoring scenario.

You may choose to:

  • extend the current monitoring pipeline
  • apply the techniques to a different dataset
  • add new signals or anomaly logic
  • experiment with different system health rules

Describe your approach on the docs/index.md page.

Explain:

  • what signals you used
  • how anomalies were detected
  • how the system state was determined
  • what the results suggest about system behavior

Continuous intelligence systems help organizations monitor complex systems and make informed operational decisions.

If you would like to apply these skills to a real dataset instead of the provided example data, see suggested datasets:

https://denisecase.github.io/pro-analytics-02/reference/datasets/cintel/

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