---
title: Telemetry
description: A description of the opt-in telemetry implementation in Axolotl.
---

# Telemetry in Axolotl

Axolotl implements anonymous telemetry to help maintainers understand how the library
is used and where users encounter issues. This data helps prioritize features, optimize
performance, and fix bugs.

## Data Collection

We collect:

- System info: OS, Python version, Axolotl version, PyTorch version, Transformers
version, etc.
- Hardware info: CPU count, memory, GPU count and models
- Runtime metrics: Training progress, memory usage, timing information
- Usage patterns: Models (from a whitelist) and configurations used
- Error tracking: Stack traces and error messages (sanitized to remove personal
information)

No personally identifiable information (PII) is collected.

## Implementation

Telemetry is implemented using PostHog and consists of:

- `axolotl.telemetry.TelemetryManager`: A singleton class that initializes the
telemetry system and provides methods for tracking events.
- `axolotl.telemetry.errors.send_errors`: A decorator that captures exceptions and
sends sanitized stack traces.
- `axolotl.telemetry.runtime_metrics.RuntimeMetricsTracker`: A class that tracks
runtime metrics during training.
- `axolotl.telemetry.callbacks.TelemetryCallback`: A Trainer callback that sends
runtime metrics telemetry.

The telemetry system will block training startup for 15 seconds to ensure users are
aware of data collection, unless telemetry is explicitly enabled or disabled.

## Opt-In Mechanism

Telemetry is **disabled by default** on an opt-in basis. To enable it, set `AXOLOTL_DO_NOT_TRACK=0`.

To remove the warning message about telemetry that is displayed on train, etc. startup,
explicitly set: `AXOLOTL_DO_NOT_TRACK=0` (enable telemetry) or `AXOLOTL_DO_NOT_TRACK=1`
(explicitly disable telemetry).

**Note**: Telemetry will move to an opt-out model in a later release.

## Privacy

- All path-like config information is automatically redacted from telemetry data
- Model information is only collected for whitelisted organizations
    - See `axolotl/telemetry/whitelist.yaml` for the set of whitelisted organizations
- Each run generates a unique anonymous ID
    - This allows us to link different telemetry events in a single same training run
- Telemetry is only sent from the main process to avoid duplicate events