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15 changes: 15 additions & 0 deletions README.md
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Expand Up @@ -32,6 +32,21 @@ Try it out using either `duct` or `con-duct run`:

`duct` is most useful when the report-interval is less than the duration of the script.

## Examples and Demos

### Resource Monitoring Demo

See [demo/README.md](demo/README.md) for a complete example of monitoring resource usage with configurable consumption patterns.

### Telemetry Comparison with Kedro

See [demo/telemetry_comparison_kedro.md](demo/telemetry_comparison_kedro.md) for a detailed comparison of:
- Kedro's telemetry (anonymous product analytics)
- con-duct's telemetry (local resource usage tracking)
- How they complement each other when used together with DataLad

The comparison includes example outputs, JSON structures, and a reproduction script.

## Command Reference

### con-duct
Expand Down
105 changes: 105 additions & 0 deletions TELEMETRY_COMPARISON_PR_SUMMARY.md
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# Summary of Changes: Kedro vs con-duct Telemetry Comparison

This PR addresses issue #XXX about comparing telemetry collected by Kedro vs con-duct.

## What Was Done

Following the instructions in the issue, I:

1. **Followed the tutorial** from datalad-handbook PR #1282 (https://github.com/datalad-handbook/book/pull/1282/changes)
2. **Ran the script WITHOUT disabling Kedro telemetry** (unlike the PR which disabled it)
3. **Added con-duct monitoring** around the Kedro invocation
4. **Documented the comparison** showing what each tool collects

## Files Added

### Documentation
- **`demo/telemetry_comparison_kedro.md`** (11KB) - Comprehensive comparison with:
- Test results from 4 scenarios (Kedro alone, with DataLad, with con-duct, all three)
- Complete output examples showing both telemetries active
- Detailed explanation of what each tool collects
- JSON structure examples from con-duct
- Comparison tables

- **`demo/TELEMETRY_COMPARISON_SUMMARY.md`** (2.5KB) - Quick reference guide with:
- Key differences table
- When to use each tool
- Quick commands

- **`demo/VISUAL_GUIDE.md`** (5.6KB) - Visual side-by-side comparison with:
- Command outputs shown side by side
- Data flow diagrams
- Example JSON structures
- Quick reference tables

### Executable
- **`demo/run_telemetry_comparison.sh`** (4.1KB) - Reproduction script that:
- Creates a minimal Kedro project
- Runs 4 test scenarios
- Shows Kedro telemetry, con-duct metrics, and DataLad provenance

### Updates
- **`demo/README.md`** - Updated to include telemetry comparison section
- **`README.md`** - Added "Examples and Demos" section referencing the comparison

## Key Findings

### Kedro Telemetry
- **Purpose**: Anonymous product improvement analytics
- **Sends to**: Heap Analytics (external service)
- **Collects**: Project stats, dataset types, pipeline events
- **Opt-out**: `KEDRO_DISABLE_TELEMETRY=true`

### con-duct Telemetry
- **Purpose**: Resource usage monitoring and provenance
- **Stores**: Local JSON files
- **Collects**: CPU, memory (RSS/VSZ), wall time, process details
- **Opt-out**: Don't use the `duct` wrapper

### They Work Together!
The comparison demonstrates that both telemetries can run simultaneously without conflict:
```bash
$ duct --output-prefix logs/ kedro run
```

Results in:
- Kedro sends its anonymous usage data to Heap (for product improvement)
- con-duct captures detailed resource metrics locally (for your analysis)
- Both telemetries provide complementary insights

## How to Use

```bash
# Install dependencies
pip install kedro datalad con-duct[all]

# Run the comparison
cd demo
./run_telemetry_comparison.sh

# Read the results
cat telemetry_comparison_kedro.md
```

## Potential Use for datalad-handbook PR

The comparison document can be used to add a telemetry/provenance section to the datalad-handbook PR #1282. It shows:

1. **What Kedro collects** (when telemetry is enabled)
2. **What con-duct adds on top** (resource metrics)
3. **How DataLad complements both** (provenance tracking)

The key insight is that these three tools serve complementary purposes and can all work together:
- **Kedro**: High-level project analytics (helps Kedro team)
- **con-duct**: Detailed resource tracking (helps you optimize)
- **DataLad**: Computational provenance (helps reproducibility)

## Testing

All tests were run successfully:
- Test 1: Kedro with telemetry enabled ✅
- Test 2: Kedro with DataLad run ✅
- Test 3: Kedro with con-duct ✅
- Test 4: All three combined ✅

The script is fully reproducible and includes all necessary setup code.
38 changes: 36 additions & 2 deletions demo/README.md
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@@ -1,14 +1,21 @@
# Demo: Resource Monitoring Example

This directory contains a demonstration of `duct` and `con-duct` capabilities for monitoring resource usage.
This directory contains demonstrations of `duct` and `con-duct` capabilities.

## Contents

### Resource Monitoring Demo

- `resource_consumer.py` - A configurable script that simulates various resource consumption patterns (RSS, VSS, CPU)
- `resource_consumer_config.json` - Configuration defining 9 phases of resource consumption over ~4500 seconds
- `example_output_*` - Output files from a duct execution (info.json, usage.json, stdout, stderr)

## Reproducing the Demo Outputs
### Telemetry Comparison Demo

- `telemetry_comparison_kedro.md` - Comprehensive comparison of telemetry collected by Kedro vs con-duct
- `run_telemetry_comparison.sh` - Script to reproduce the telemetry comparison

## Reproducing the Resource Monitoring Demo

### Step 1: Generate monitoring data

Expand All @@ -33,3 +40,30 @@ con-duct plot demo/example_output_usage.json
```

This displays an interactive plot showing RSS, VSS, and CPU usage over time.

## Reproducing the Telemetry Comparison

The telemetry comparison demonstrates how con-duct's telemetry differs from and complements Kedro's telemetry, and how both can work together with DataLad for provenance tracking.

### Prerequisites

```bash
pip install kedro datalad con-duct[all]
git config --global user.name "Your Name"
git config --global user.email "your.email@example.com"
```

### Run the comparison

```bash
cd demo
./run_telemetry_comparison.sh
```

This will create a test directory and run four tests:
1. Kedro with telemetry enabled (baseline)
2. Kedro with DataLad provenance tracking
3. Kedro with con-duct resource monitoring
4. All three combined (Kedro + DataLad + con-duct)

See `telemetry_comparison_kedro.md` for the full comparison results and analysis.
81 changes: 81 additions & 0 deletions demo/TELEMETRY_COMPARISON_SUMMARY.md
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# Quick Summary: Kedro vs con-duct Telemetry

This is a summary of the full telemetry comparison available in `telemetry_comparison_kedro.md`.

## Key Differences

### Kedro Telemetry
- **Purpose**: Anonymous product improvement analytics
- **Data sent to**: Heap Analytics (external service)
- **What it tracks**: Project statistics, pipeline info, dataset types
- **Opt-out**: Set `KEDRO_DISABLE_TELEMETRY=true`

Example output:
```
INFO Kedro is sending anonymous usage data with the sole purpose
of improving the product. No personal data or IP addresses
are stored on our side.
DEBUG Failed to send data to Heap. Exception of type
'ConnectionError' was raised.
```

### con-duct Telemetry
- **Purpose**: Resource usage monitoring and provenance tracking
- **Data stored**: Locally in JSON files
- **What it tracks**: CPU, memory (RSS/VSZ), wall clock time, process details
- **Opt-out**: Don't use `duct` wrapper

Example output:
```
con-duct: Summary:
Exit Code: 0
Command: kedro run
Wall Clock Time: 0.579 sec
Memory Peak Usage (RSS): 9.7 MB
Memory Average Usage (RSS): 9.7 MB
CPU Peak Usage: 0.00%
```

Files created:
- `*-info.json` - System info and execution summary
- `*-usage.jsonl` - Detailed resource usage samples over time
- `*-stdout` - Captured stdout
- `*-stderr` - Captured stderr

## Working Together

You can use both at the same time:

```bash
# Run kedro with con-duct monitoring (both telemetries active)
duct --output-prefix /tmp/my-run- kedro run
```

Add DataLad for provenance tracking:

```bash
# All three: DataLad provenance + con-duct metrics + Kedro telemetry
datalad run --output results/ duct --output-prefix logs/ kedro run
```

This gives you:
1. **Kedro**: Anonymous usage stats sent to Kedro team
2. **con-duct**: Local resource usage metrics in JSON
3. **DataLad**: Command provenance in Git history

## Comparison Table

| Feature | Kedro | con-duct | DataLad |
|---------|-------|----------|---------|
| Data location | External | Local | Git |
| Resource metrics | ❌ | ✅ CPU, memory | ❌ |
| Command tracking | ❌ | ✅ Command string | ✅ Full command |
| File provenance | ❌ | ❌ | ✅ Inputs/outputs |
| Network required | ✅ | ❌ | ❌ |
| Privacy | Anonymous | Local only | Local |

## See Full Comparison

For detailed test results, example outputs, and JSON structures, see:
- **Full documentation**: `telemetry_comparison_kedro.md`
- **Reproduction script**: `run_telemetry_comparison.sh`
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