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# Monitoring and debugging

::::{grid} 1 2 2 2
:gutter: 2

:::{grid-item-card} 🕵️ Features & Diagnostics
:link: monitoring_and_debugging/features_and_diagnostics
:link-type: doc

Diagnostic tools and features for monitoring MaxText.
:::

:::{grid-item-card} ☁️ GCP Observability
:link: monitoring_and_debugging/gcp_workload_observability
:link-type: doc

Observability for workloads running on Google Cloud Platform.
:::

:::{grid-item-card} 🚫 Hang Playbook
:link: monitoring_and_debugging/megascale_hang_playbook
:link-type: doc

Troubleshooting guide for training hangs at megascale.
:::

:::{grid-item-card} 📈 Goodput
:link: monitoring_and_debugging/monitor_goodput
:link-type: doc

Monitoring efficient training time (Goodput).
:::

:::{grid-item-card} 📊 Logs & Metrics
:link: monitoring_and_debugging/understand_logs_and_metrics
:link-type: doc

Understanding MaxText logs and performance metrics.
:::

:::{grid-item-card} 📉 TensorBoard
:link: monitoring_and_debugging/use_vertex_ai_tensorboard
:link-type: doc

Using Vertex AI TensorBoard for visualization.
:::

:::{grid-item-card} ⏱️ XProf
:link: monitoring_and_debugging/xprof_user_guide
:link-type: doc

Profiling performance with XProf.
:::
::::

```{toctree}
---
hidden:
maxdepth: 1
---
monitoring_and_debugging/features_and_diagnostics.md
monitoring_and_debugging/gcp_workload_observability.md
monitoring_and_debugging/megascale_hang_playbook.md
monitoring_and_debugging/monitor_goodput.md
monitoring_and_debugging/understand_logs_and_metrics.md
monitoring_and_debugging/use_vertex_ai_tensorboard.md
monitoring_and_debugging/xprof_user_guide.md
monitoring_and_debugging/ml_workload_diagnostics.md
```