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[Docs] Clarify managed spot jobs against sky launch #3561

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May 19, 2024
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[Docs] Clarify managed spot jobs against sky launch #3561

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Clarify managed spot jobs against sky launch
Michaelvll May 16, 2024
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Michaelvll May 18, 2024
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Update docs/source/examples/managed-jobs.rst
Michaelvll May 19, 2024
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22 changes: 20 additions & 2 deletions docs/source/examples/managed-jobs.rst
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Expand Up @@ -7,7 +7,7 @@ Managed Jobs

This feature is great for scaling out: running a single job for long durations, or running many jobs (pipelines).

SkyPilot supports **managed jobs**, which can automatically recover from any spot preemptions or hardware failures.
SkyPilot supports **managed jobs** (:code:`sky jobs`), which can automatically recover from any spot preemptions or hardware failures.
It can be used in three modes:

#. :ref:`Managed Spot Jobs <spot-jobs>`: Jobs run on auto-recovering spot instances. This can **save significant costs** (e.g., up to 70\% for GPU VMs) by making preemptible spot instances useful for long-running jobs.
Expand All @@ -20,9 +20,27 @@ It can be used in three modes:
Managed Spot Jobs
-----------------

SkyPilot automatically finds available spot resources across regions and clouds to maximize availability.
*SkyPilot managed spot job* (:code:`sky jobs launch --use-spot`) automatically finds available spot resources across regions and clouds to maximize availability.
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Any spot preemptions are automatically handled by SkyPilot without user intervention.


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.. list-table::
:widths: 30 18 12 35
:header-rows: 1

* - Command
- Managed?
- SSH-able?
- Best for
* - :code:`sky launch --use-spot`
- Unmanaged spot cluster
- Yes
- Interactive dev on spot instances (e.g., :ref:`SSH, VSCode, Jupyter <dev-connect>`).
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* - :code:`sky jobs launch --use-spot`
- Managed spot job (auto-recovery)
- No
- Scaling out long-running jobs (e.g., data processing, training, batch inference).
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Here is an example of a BERT training job failing over different regions across AWS and GCP.

.. image:: https://i.imgur.com/Vteg3fK.gif
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