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cintel-06-continuous-intelligence\n\n[![Docs](https://img.shields.io/badge/docs-GitHub%20Pages-blue)](https://denisecase.github.io/cintel-06-continuous-intelligence/)\n[![CI Status](https://github.com/denisecase/cintel-06-continuous-intelligence/actions/workflows/ci-python-zensical.yml/badge.svg?branch=main)](https://github.com/denisecase/cintel-06-continuous-intelligence/actions/workflows/ci-python-zensical.yml)\n[![Python 3.14+](https://img.shields.io/badge/python-3.14%2B-blue?logo=python)](#)\n[![MIT](https://img.shields.io/badge/license-see%20LICENSE-yellow.svg)](./LICENSE)\n\n\u003e Professional Python project for continuous intelligence.\n\nContinuous intelligence systems monitor data streams, detect change, and respond in real time.\nThis course builds those capabilities through working projects.\n\nIn the age of generative AI, durable skills are grounded in real work:\nsetting up a professional environment,\nreading and running code,\nunderstanding the logic,\nand pushing work to a shared repository.\nEach project follows the structure of professional Python projects.\nWe learn by doing.\n\n## This Project\n\nThis project brings together several techniques used in continuous intelligence systems.\n\nThe goal is to copy this repository,\nset up your environment,\nrun the example analysis,\nand explore how monitoring techniques can be combined\nto assess the current state of a system.\n\nRun the example pipeline, read the code, and see how:\n\n- raw system metrics are transformed into useful signals\n- anomalies are detected in those signals\n- monitoring results are summarized to assess system health\n\nThis project demonstrates how monitoring data can support operational awareness and decision-making.\n\nThis module serves as a capstone:\nit encourages you to combine techniques developed\nin earlier modules into a simple continuous intelligence pipeline:\n\n- Module 2. anomaly detection\n- Module 3. signal design\n- Module 4. rolling monitoring\n- Module 5. drift comparison\n- Module 6. system assessment (integration).\n\n## Data\n\nThe example pipeline reads system metrics from:\n\n`data/system_metrics_case.csv`\n\nEach row represents one observation of system activity.\n\nThe pipeline derives signals such as\n**error rate** and **average latency**,\nchecks for anomalous conditions,\nand produces a summary assessment of system behavior.\n\nThe dataset includes a short period of degraded performance\nso that monitoring signals and anomaly detection\nproduce visible results.\n\n## Working Files\n\nYou'll work with just these areas:\n\n- **data/** - it starts with the data\n- **docs/** - tell the story\n- **src/cintel/** - where the magic happens\n- **pyproject.toml** - update authorship \u0026 links\n- **zensical.toml** - update authorship \u0026 links\n\n## Instructions\n\nFollow the [step-by-step workflow guide](https://denisecase.github.io/pro-analytics-02/workflow-b-apply-example-project/) to complete:\n\n1. Phase 1. **Start \u0026 Run**\n2. Phase 2. **Change Authorship**\n3. Phase 3. **Read \u0026 Understand**\n4. Phase 4. **Modify**\n5. Phase 5. **Apply**\n\n## Challenges\n\nChallenges are expected.\nSometimes instructions may not quite match your operating system.\nWhen issues occur, share screenshots, error messages, and details about what you tried.\nWorking through issues is part of implementing professional projects.\n\n## Success\n\nAfter completing Phase 1. **Start \u0026 Run**, you'll have your own GitHub project, running on your machine, and running the example will print out:\n\n```shell\n========================\nPipeline executed successfully!\n========================\n```\n\nAnd a new file named `project.log` will appear in the project folder.\n\n## Command Reference\n\nThe commands below are used in the workflow guide above.\nThey are provided here for convenience.\n\nFollow the guide for the **full instructions**.\n\n\u003cdetails\u003e\n\u003csummary\u003eShow command reference\u003c/summary\u003e\n\n### In a machine terminal (open in your `Repos` folder)\n\nAfter you get a copy of this repo in your own GitHub account,\nopen a machine terminal in your `Repos` folder:\n\n```shell\n# Replace username with YOUR GitHub username.\ngit clone https://github.com/username/cintel-06-continuous-intelligence\n\ncd cintel-06-continuous-intelligence\ncode .\n```\n\n### In a VS Code terminal\n\n```shell\nuv self update\nuv python pin 3.14\nuv sync --extra dev --extra docs --upgrade\n\nuvx pre-commit install\ngit add -A\nuvx pre-commit run --all-files\n# repeat if changes were made\ngit add -A\nuvx pre-commit run --all-files\n\nuv run python -m cintel.continuous_intelligence_case\n\nuv run ruff format .\nuv run ruff check . --fix\nuv run zensical build\n\ngit add -A\ngit commit -m \"update\"\ngit push -u origin main\n```\n\n\u003c/details\u003e\n\n## Notes\n\n- Use the **UP ARROW** and **DOWN ARROW** in the terminal to scroll through past commands.\n- Use `CTRL+f` to find (and replace) text within a file.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdenisecase%2Fcintel-06-continuous-intelligence","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdenisecase%2Fcintel-06-continuous-intelligence","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdenisecase%2Fcintel-06-continuous-intelligence/lists"}