diff --git a/docs/source-pytorch/governance.rst b/docs/source-pytorch/community/governance.rst
similarity index 100%
rename from docs/source-pytorch/governance.rst
rename to docs/source-pytorch/community/governance.rst
diff --git a/docs/source-pytorch/community/index.rst b/docs/source-pytorch/community/index.rst
new file mode 100644
index 0000000000000..bd500a914146e
--- /dev/null
+++ b/docs/source-pytorch/community/index.rst
@@ -0,0 +1,68 @@
+
+.. toctree::
+   :maxdepth: 1
+   :hidden:
+
+   ../generated/CODE_OF_CONDUCT.md
+   ../generated/CONTRIBUTING.md
+   ../generated/BECOMING_A_CORE_CONTRIBUTOR.md
+   governance
+   ../versioning
+   ../past_versions
+   ../generated/CHANGELOG.md
+
+#########
+Community
+#########
+
+.. raw:: html
+
+    <div class="display-card-container">
+        <div class="row">
+
+.. displayitem::
+   :header: Code of conduct
+   :description: Contributor Covenant Code of Conduct
+   :col_css: col-md-12
+   :button_link: ../generated/CODE_OF_CONDUCT.html
+   :height: 100
+
+.. displayitem::
+   :header: Contribution guide
+   :description: How to contribute to PyTorch Lightning
+   :col_css: col-md-12
+   :button_link: ../generated/CONTRIBUTING.html
+   :height: 100
+
+.. displayitem::
+   :header: How to Become a core contributor
+   :description: Steps to be a core contributor
+   :col_css: col-md-12
+   :button_link: ../generated/BECOMING_A_CORE_CONTRIBUTOR.html
+   :height: 100
+
+.. displayitem::
+   :header: Lightning Governance
+   :description: The governance processes we follow
+   :col_css: col-md-12
+   :button_link: governance.html
+   :height: 100
+
+.. displayitem::
+   :header: Versioning
+   :description: PyTorch Lightning's versioning policy
+   :col_css: col-md-12
+   :button_link: ../versioning.html
+   :height: 100
+
+.. displayitem::
+   :header: Changelog
+   :description: All notable changes to PyTorch Lightning
+   :col_css: col-md-12
+   :button_link: ../generated/CHANGELOG.html
+   :height: 100
+
+.. raw:: html
+
+        </div>
+    </div>
diff --git a/docs/source-pytorch/glossary/index.rst b/docs/source-pytorch/glossary/index.rst
new file mode 100644
index 0000000000000..2c91a7c2d0b80
--- /dev/null
+++ b/docs/source-pytorch/glossary/index.rst
@@ -0,0 +1,331 @@
+
+.. toctree::
+   :maxdepth: 1
+   :hidden:
+
+   Accelerators <../extensions/accelerator>
+   Callback <../extensions/callbacks>
+   Checkpointing <../common/checkpointing>
+   Cluster <../clouds/cluster>
+   Cloud checkpoint <../common/checkpointing_advanced>
+   Console Logging <../common/console_logs>
+   Debugging <../debug/debugging>
+   Early stopping <../common/early_stopping>
+   Experiment manager (Logger) <../visualize/experiment_managers>
+   Finetuning <../advanced/finetuning>
+   GPU <../accelerators/gpu>
+   Half precision <../common/precision>
+   HPU <../accelerators/hpu>
+   Inference <../deploy/production_intermediate>
+   IPU <../accelerators/ipu>
+   Lightning CLI <../cli/lightning_cli>
+   LightningDataModule <../data/datamodule>
+   LightningModule <../common/lightning_module>
+   Log <../visualize/loggers>
+   TPU <../accelerators/tpu>
+   Metrics <https://torchmetrics.readthedocs.io/en/stable/>
+   Model <../model/build_model.rst>
+   Model Parallel <../advanced/model_parallel>
+   Plugins <../extensions/plugins>
+   Progress bar <../common/progress_bar>
+   Production <../deploy/production_advanced>
+   Predict <../deploy/production_basic>
+   Pretrained models <../advanced/pretrained>
+   Profiler <../tuning/profiler>
+   Pruning and Quantization <../advanced/pruning_quantization>
+   Remote filesystem and FSSPEC <../common/remote_fs>
+   Strategy <../extensions/strategy>
+   Strategy registry <../advanced/strategy_registry>
+   Style guide <../starter/style_guide>
+   SWA <../advanced/training_tricks>
+   SLURM <../clouds/cluster_advanced>
+   Transfer learning <../advanced/transfer_learning>
+   Trainer <../common/trainer>
+   Torch distributed <../clouds/cluster_intermediate_2>
+
+########
+Glossary
+########
+
+.. raw:: html
+
+    <div class="display-card-container">
+        <div class="row">
+
+.. displayitem::
+   :header: Accelerators
+   :description: Accelerators connect the Trainer to hardware to train faster
+   :col_css: col-md-12
+   :button_link: ../extensions/accelerator.html
+   :height: 100
+
+.. displayitem::
+   :header: Callback
+   :description: Add self-contained extra functionality during training execution
+   :col_css: col-md-12
+   :button_link: ../extensions/callbacks.html
+   :height: 100
+
+.. displayitem::
+   :header: Checkpointing
+   :description: Save and load progress with checkpoints
+   :col_css: col-md-12
+   :button_link: ../common/checkpointing.html
+   :height: 100
+
+.. displayitem::
+   :header: Cluster
+   :description: Run on your own group of servers
+   :col_css: col-md-12
+   :button_link: ../clouds/cluster.html
+   :height: 100
+
+.. displayitem::
+   :header: Cloud checkpoint
+   :description: Save your models to cloud filesystems
+   :col_css: col-md-12
+   :button_link: ../common/checkpointing_advanced.html
+   :height: 100
+
+.. displayitem::
+   :header: Console Logging
+   :description: Capture more visible logs
+   :col_css: col-md-12
+   :button_link: ../common/console_logs.html
+   :height: 100
+
+.. displayitem::
+   :header: Debugging
+   :description: Fix errors in your code
+   :col_css: col-md-12
+   :button_link: ../debug/debugging.html
+   :height: 100
+
+.. displayitem::
+   :header: Early stopping
+   :description: Stop the training when no improvement is observed
+   :col_css: col-md-12
+   :button_link: ../common/early_stopping.html
+   :height: 100
+
+.. displayitem::
+   :header: Experiment manager (Logger)
+   :description: Tools for tracking and visualizing artifacts and logs
+   :col_css: col-md-12
+   :button_link: ../visualize/experiment_managers.html
+   :height: 100
+
+.. displayitem::
+   :header: Finetuning
+   :description: Technique for training pretrained models
+   :col_css: col-md-12
+   :button_link: ../advanced/finetuning.html
+   :height: 100
+
+.. displayitem::
+   :header: GPU
+   :description: Graphics Processing Unit for faster training
+   :col_css: col-md-12
+   :button_link: ../accelerators/gpu.html
+   :height: 100
+
+.. displayitem::
+   :header: Half precision
+   :description: Using different numerical formats to save memory and run fatser
+   :col_css: col-md-12
+   :button_link: ../common/precision.html
+   :height: 100
+
+.. displayitem::
+   :header: HPU
+   :description: Habana Gaudi AI Processor Unit for faster training
+   :col_css: col-md-12
+   :button_link: ../accelerators/hpu.html
+   :height: 100
+
+.. displayitem::
+   :header: Inference
+   :description: Making predictions by applying a trained model to unlabeled examples
+   :col_css: col-md-12
+   :button_link: ../deploy/production_intermediate.html
+   :height: 100
+
+.. displayitem::
+   :header: IPU
+   :description: Graphcore Intelligence Processing Unit for faster training
+   :col_css: col-md-12
+   :button_link: ../accelerators/ipu.html
+   :height: 100
+
+.. displayitem::
+   :header: Lightning CLI
+   :description: A Command-line Interface (CLI) to interact with Lightning code via a terminal
+   :col_css: col-md-12
+   :button_link: ../cli/lightning_cli.html
+   :height: 100
+
+.. displayitem::
+   :header: LightningDataModule
+   :description: A shareable, reusable class that encapsulates all the steps needed to process data
+   :col_css: col-md-12
+   :button_link: ../data/datamodule.html
+   :height: 100
+
+.. displayitem::
+   :header: LightningModule
+   :description: A base class organizug your neural network module
+   :col_css: col-md-12
+   :button_link: ../common/lightning_module.html
+   :height: 100
+
+.. displayitem::
+   :header: Log
+   :description: Outpus or results used for visualization and tracking
+   :col_css: col-md-12
+   :button_link: ../visualize/loggers.html
+   :height: 100
+
+.. displayitem::
+   :header: Metrics
+   :description: A statistic used to measure performance or other objectives we want to optimize
+   :col_css: col-md-12
+   :button_link: https://torchmetrics.readthedocs.io/en/stable/
+   :height: 100
+
+.. displayitem::
+   :header: Model
+   :description: The set of parameters and structure for a system to make predictions
+   :col_css: col-md-12
+   :button_link: ../model/build_model.html
+   :height: 100
+
+.. displayitem::
+   :header: Model Parallelism
+   :description: A way to scale training that splits a model between multiple devices.
+   :col_css: col-md-12
+   :button_link: ../advanced/model_parallel.html
+   :height: 100
+
+.. displayitem::
+   :header: Plugins
+   :description: Custom trainer integrations such as custom precision, checkpointing or cluster environment implementation
+   :col_css: col-md-12
+   :button_link: ../extensions/plugins.html
+   :height: 100
+
+.. displayitem::
+   :header: Progress bar
+   :description: Output printed to the terminal to visualize the progression of training
+   :col_css: col-md-12
+   :button_link: ../common/progress_bar.html
+   :height: 100
+
+.. displayitem::
+   :header: Production
+   :description: Using ML models in real world systems
+   :col_css: col-md-12
+   :button_link: ../deploy/production_advanced.html
+   :height: 100
+
+.. displayitem::
+   :header: Prediction
+   :description: Computing a model's output
+   :col_css: col-md-12
+   :button_link: ../deploy/production_basic.html
+   :height: 100
+
+.. displayitem::
+   :header: Pretrained models
+   :description: Models that have already been trained for a particular task
+   :col_css: col-md-12
+   :button_link: ../advanced/pretrained.html
+   :height: 100
+
+.. displayitem::
+   :header: Profiler
+   :description: Tool to identify bottlenecks and performance of different parts of a model
+   :col_css: col-md-12
+   :button_link: ../tuning/profiler.html
+   :height: 100
+
+.. displayitem::
+   :header: Pruning
+   :description: A technique to eliminae some of the model weights to reduce the model size and decrease inference requirements
+   :col_css: col-md-12
+   :button_link: ../advanced/pruning_quantization.html
+   :height: 100
+
+.. displayitem::
+   :header: Quantization
+   :description: A technique to accelerate the model inference speed and decrease the memory load while still maintaining the model accuracy
+   :col_css: col-md-12
+   :button_link: ../advanced/post_training_quantization.html
+   :height: 100
+
+.. displayitem::
+   :header: Remote filesystem and FSSPEC
+   :description: Accessing files from cloud storage providers
+   :col_css: col-md-12
+   :button_link: ../common/remote_fs.html
+   :height: 100
+
+.. displayitem::
+   :header: Strategy
+   :description: Ways the trainer controls the model distribution across training, evaluation, and prediction
+   :col_css: col-md-12
+   :button_link: ../extensions/strategy.html
+   :height: 100
+
+.. displayitem::
+   :header: Strategy registry
+   :description: A class that holds information about training strategies and allows adding new custom strategies
+   :col_css: col-md-12
+   :button_link: ../advanced/strategy_registry.html
+   :height: 100
+
+.. displayitem::
+   :header: Style guide
+   :description: Best practices to improve readability and reproducability
+   :col_css: col-md-12
+   :button_link: ../starter/style_guide.html
+   :height: 100
+
+.. displayitem::
+   :header: SWA
+   :description: Stochastic Weight Averaging (SWA) can make your models generalize better
+   :col_css: col-md-12
+   :button_link: ../advanced/training_tricks.html#stochastic-weight-averaging
+   :height: 100
+
+.. displayitem::
+   :header: SLURM
+   :description: Simple Linux Utility for Resource Management, or simply Slurm, is a free and open-source job scheduler for Linux clusters
+   :col_css: col-md-12
+   :button_link: ../clouds/cluster_advanced.html
+   :height: 100
+
+.. displayitem::
+   :header: Transfer learning
+   :description: Using pre-trained models to improve learning
+   :col_css: col-md-12
+   :button_link: ../advanced/transfer_learning.html
+   :height: 100
+
+.. displayitem::
+   :header: Trainer
+   :description: The class that automates and customizes model training
+   :col_css: col-md-12
+   :button_link: ../common/trainer.html
+   :height: 100
+
+.. displayitem::
+   :header: Torch distributed
+   :description: Setup for running on distributed environments
+   :col_css: col-md-12
+   :button_link: ../clouds/cluster_intermediate_2.html
+   :height: 100
+
+.. raw:: html
+
+        </div>
+    </div>
diff --git a/docs/source-pytorch/index.rst b/docs/source-pytorch/index.rst
index 9560190717931..0bd78b6fb63a8 100644
--- a/docs/source-pytorch/index.rst
+++ b/docs/source-pytorch/index.rst
@@ -165,7 +165,7 @@ Current Lightning Users
    levels/expert
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :name: pl_docs
    :caption: Core API
 
@@ -173,105 +173,30 @@ Current Lightning Users
    common/trainer
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :name: api
-   :caption: API Reference
+   :caption: Optional API
 
    api_references
 
 .. toctree::
    :maxdepth: 1
-   :name: Common Workflows
-   :caption: Common Workflows
-
-   Avoid overfitting <common/evaluation>
-   model/build_model.rst
-   cli/lightning_cli
-   common/progress_bar
-   deploy/production
-   advanced/training_tricks
-   tuning/profiler
-   Manage experiments <visualize/logging_intermediate>
-   Organize existing PyTorch into Lightning <starter/converting>
-   clouds/cluster
-   Save and load model progress <common/checkpointing>
-   Save memory with half-precision <common/precision>
-   advanced/model_parallel
-   Train on single or multiple GPUs <accelerators/gpu>
-   Train on single or multiple HPUs <accelerators/hpu>
-   Train on single or multiple IPUs <accelerators/ipu>
-   Train on single or multiple TPUs <accelerators/tpu>
-   Train on MPS <accelerators/mps>
-   Use a pretrained model <advanced/pretrained>
-   data/data
-   model/own_your_loop
-
-.. toctree::
-   :maxdepth: 1
-   :name: Glossary
-   :caption: Glossary
-
-   Accelerators <extensions/accelerator>
-   Callback <extensions/callbacks>
-   Checkpointing <common/checkpointing>
-   Cluster <clouds/cluster>
-   Cloud checkpoint <common/checkpointing_advanced>
-   Console Logging <common/console_logs>
-   Debugging <debug/debugging>
-   Early stopping <common/early_stopping>
-   Experiment manager (Logger) <visualize/experiment_managers>
-   Finetuning <advanced/finetuning>
-   Flash <https://lightning-flash.readthedocs.io/en/stable/>
-   GPU <accelerators/gpu>
-   Half precision <common/precision>
-   HPU <accelerators/hpu>
-   Inference <deploy/production_intermediate>
-   IPU <accelerators/ipu>
-   Lightning CLI <cli/lightning_cli>
-   LightningDataModule <data/datamodule>
-   LightningModule <common/lightning_module>
-   Log <visualize/loggers>
-   TPU <accelerators/tpu>
-   Metrics <https://torchmetrics.readthedocs.io/en/stable/>
-   Model <model/build_model.rst>
-   Model Parallel <advanced/model_parallel>
-   Plugins <extensions/plugins>
-   Progress bar <common/progress_bar>
-   Production <deploy/production_advanced>
-   Predict <deploy/production_basic>
-   Pretrained models <advanced/pretrained>
-   Profiler <tuning/profiler>
-   Pruning and Quantization <advanced/pruning_quantization>
-   Remote filesystem and FSSPEC <common/remote_fs>
-   Strategy <extensions/strategy>
-   Strategy registry <advanced/strategy_registry>
-   Style guide <starter/style_guide>
-   SWA <advanced/training_tricks>
-   SLURM <clouds/cluster_advanced>
-   Transfer learning <advanced/transfer_learning>
-   Trainer <common/trainer>
-   Torch distributed <clouds/cluster_intermediate_2>
-
-.. toctree::
-   :maxdepth: 1
-   :name: Hands-on Examples
-   :caption: Hands-on Examples
+   :name: Examples
+   :caption: Examples
    :glob:
 
    notebooks/**/*
 
+
 .. toctree::
    :maxdepth: 1
-   :name: Community
-   :caption: Community
-
-   generated/CODE_OF_CONDUCT.md
-   generated/CONTRIBUTING.md
-   generated/BECOMING_A_CORE_CONTRIBUTOR.md
-   governance
-   versioning
-   past_versions
-   generated/CHANGELOG.md
+   :name: More
+   :caption: More
+
+   Community <community/index>
+   Glossary <glossary/index>
+   How to <common/index>
+
 
 .. raw:: html
 
diff --git a/docs/source-pytorch/past_versions.rst b/docs/source-pytorch/past_versions.rst
index be8f516824681..374303735ed32 100644
--- a/docs/source-pytorch/past_versions.rst
+++ b/docs/source-pytorch/past_versions.rst
@@ -3,7 +3,7 @@ Past PyTorch Lightning versions
 
 PyTorch Lightning :doc:`evolved over time <versioning>`. Here's the history of versions with links to their respective docs.
 
-To help you with keeping up to spead, check :doc:`Migration guide <./upgrade/migration_guide>`.
+To help you with keeping up to spead, check :doc:`Migration guide <../upgrade/migration_guide>`.
 
 .. list-table:: Past versions
    :widths: 5 50 30 15
@@ -22,7 +22,7 @@ To help you with keeping up to spead, check :doc:`Migration guide <./upgrade/mig
        `1.9.3 <https://lightning.ai/docs/pytorch/1.9.3>`_,
        `1.9.4 <https://lightning.ai/docs/pytorch/1.9.4>`_,
        `1.9.5 <https://lightning.ai/docs/pytorch/1.9.5>`_
-     - :doc:`from 1.9 to 2.0 <upgrade/from_1_9>`
+     - :doc:`from 1.9 to 2.0 <../upgrade/from_1_9>`
 
    * - `1.8 <https://github.com/Lightning-AI/lightning/releases/tag/1.8.0>`_
      - `Colossal-AI Strategy, Commands and Secrets for Apps, FSDP Improvements and More! <https://lightning.ai/docs/pytorch/1.8.6>`_
@@ -33,7 +33,7 @@ To help you with keeping up to spead, check :doc:`Migration guide <./upgrade/mig
        `1.8.4 <https://lightning.ai/docs/pytorch/1.8.4>`_,
        `1.8.5 <https://lightning.ai/docs/pytorch/1.8.5>`_,
        `1.8.6 <https://lightning.ai/docs/pytorch/1.8.6>`_
-     - :doc:`from 1.8 to 2.0 <upgrade/from_1_8>`
+     - :doc:`from 1.8 to 2.0 <../upgrade/from_1_8>`
 
    * - `1.7 <https://github.com/Lightning-AI/lightning/releases/tag/1.7.0>`_
      - `Apple Silicon support, Native FSDP, Collaborative training, and multi-GPU support with Jupyter notebooks <https://lightning.ai/docs/pytorch/1.7.7>`_
@@ -45,7 +45,7 @@ To help you with keeping up to spead, check :doc:`Migration guide <./upgrade/mig
        `1.7.5 <https://lightning.ai/docs/pytorch/1.7.5>`_,
        `1.7.6 <https://lightning.ai/docs/pytorch/1.7.6>`_,
        `1.7.7 <https://lightning.ai/docs/pytorch/1.7.7>`_
-     - :doc:`from 1.7 to 2.0 <upgrade/from_1_7>`
+     - :doc:`from 1.7 to 2.0 <../upgrade/from_1_7>`
 
    * - `1.6 <https://github.com/Lightning-AI/lightning/releases/tag/1.6.0>`_
      - `Support Intel's Habana Accelerator, New efficient DDP strategy (Bagua), Manual Fault-tolerance, Stability and Reliability <https://lightning.ai/docs/pytorch/1.6.5>`_
@@ -55,7 +55,7 @@ To help you with keeping up to spead, check :doc:`Migration guide <./upgrade/mig
        `1.6.3 <https://lightning.ai/docs/pytorch/1.6.3>`_,
        `1.6.4 <https://lightning.ai/docs/pytorch/1.6.4>`_,
        `1.6.5 <https://lightning.ai/docs/pytorch/1.6.5>`_
-     - :doc:`from 1.6 to 2.0 <upgrade/from_1_6>`
+     - :doc:`from 1.6 to 2.0 <../upgrade/from_1_6>`
 
    * - `1.5 <https://github.com/Lightning-AI/lightning/releases/tag/1.5.0>`_
      - `LightningLite, Fault-Tolerant Training, Loop Customization, Lightning Tutorials, LightningCLI v2, RichProgressBar, CheckpointIO Plugin, and Trainer Strategy Flag <https://lightning.ai/docs/pytorch/1.5.10>`_
@@ -70,7 +70,7 @@ To help you with keeping up to spead, check :doc:`Migration guide <./upgrade/mig
        `1.5.8 <https://lightning.ai/docs/pytorch/1.5.8>`_,
        `1.5.9 <https://lightning.ai/docs/pytorch/1.5.9>`_,
        `1.5.10 <https://lightning.ai/docs/pytorch/1.5.10>`_
-     - :doc:`from 1.5 to 2.0 <upgrade/from_1_5>`
+     - :doc:`from 1.5 to 2.0 <../upgrade/from_1_5>`
 
    * - `1.4 <https://github.com/Lightning-AI/lightning/releases/tag/1.4.0>`_
      - `TPU Pod Training, IPU Accelerator, DeepSpeed Infinity, Fully Sharded Data Parallel <https://lightning.ai/docs/pytorch/1.4.9>`_
@@ -84,7 +84,7 @@ To help you with keeping up to spead, check :doc:`Migration guide <./upgrade/mig
        `1.4.7 <https://lightning.ai/docs/pytorch/1.4.7>`_,
        `1.4.8 <https://lightning.ai/docs/pytorch/1.4.8>`_,
        `1.4.9 <https://lightning.ai/docs/pytorch/1.4.9>`_
-     - :doc:`from 1.4 to 2.0 <upgrade/from_1_4>`
+     - :doc:`from 1.4 to 2.0 <../upgrade/from_1_4>`
 
    * - `1.3 <https://github.com/Lightning-AI/lightning/releases/tag/1.3.0>`_
      - `Lightning CLI, PyTorch Profiler, Improved Early Stopping <https://pytorch-lightning.readthedocs.io/en/1.3.8>`_
diff --git a/src/lightning/app/CHANGELOG.md b/src/lightning/app/CHANGELOG.md
index ac547a4e24c50..23468376248fb 100644
--- a/src/lightning/app/CHANGELOG.md
+++ b/src/lightning/app/CHANGELOG.md
@@ -7,14 +7,29 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ## [UnReleased] - 2023-04-DD
 
+- Added the property `LightningWork.public_ip` that exposes the public IP of the `LightningWork` instance ([#17742](https://github.com/Lightning-AI/lightning/pull/17742))
+
+
+- Add missing python-multipart dependency ([#17244](https://github.com/Lightning-AI/lightning/pull/17244))
+
+
 ### Changed
 
--
+- Made type hints public ([#17100](https://github.com/Lightning-AI/lightning/pull/17100))
 
 
 ### Fixed
 
--
+- Fixed `LightningWork.internal_ip` that was mistakenly exposing the public IP instead; now exposes the private/internal IP address ([#17742](https://github.com/Lightning-AI/lightning/pull/17742))
+
+
+- Fixed resolution of latest version in CLI ([#17351](https://github.com/Lightning-AI/lightning/pull/17351))
+
+
+- Fixed property raised instead of returned ([#17595](https://github.com/Lightning-AI/lightning/pull/17595))
+
+
+- Fixed get project ([#17617](https://github.com/Lightning-AI/lightning/pull/17617), [#17666](https://github.com/Lightning-AI/lightning/pull/17666))
 
 
 ## [2.0.2] - 2023-04-24
diff --git a/src/lightning/app/components/database/server.py b/src/lightning/app/components/database/server.py
index 05a21894dc6f7..6da7710cfa4f0 100644
--- a/src/lightning/app/components/database/server.py
+++ b/src/lightning/app/components/database/server.py
@@ -231,9 +231,10 @@ def db_url(self) -> Optional[str]:
         use_localhost = "LIGHTNING_APP_STATE_URL" not in os.environ
         if use_localhost:
             return self.url
-        if self.internal_ip != "":
-            return f"http://{self.internal_ip}:{self.port}"
-        return self.internal_ip
+        ip_addr = self.public_ip or self.internal_ip
+        if ip_addr != "":
+            return f"http://{ip_addr}:{self.port}"
+        return ip_addr
 
     def on_exit(self):
         self._exit_event.set()
diff --git a/src/lightning/app/components/serve/auto_scaler.py b/src/lightning/app/components/serve/auto_scaler.py
index 1ce7f45bef318..dde7722f5da43 100644
--- a/src/lightning/app/components/serve/auto_scaler.py
+++ b/src/lightning/app/components/serve/auto_scaler.py
@@ -180,9 +180,9 @@ def __init__(
                 raise ValueError("cold_start_proxy must be of type ColdStartProxy or str")
 
     def get_internal_url(self) -> str:
-        if not self._internal_ip:
-            raise ValueError("Internal IP not set")
-        return f"http://{self._internal_ip}:{self._port}"
+        if not self._public_ip:
+            raise ValueError("Public IP not set")
+        return f"http://{self._public_ip}:{self._port}"
 
     async def send_batch(self, batch: List[Tuple[str, _BatchRequestModel]], server_url: str):
         request_data: List[_LoadBalancer._input_type] = [b[1] for b in batch]
@@ -386,7 +386,7 @@ def update_servers(self, server_works: List[LightningWork]):
         """
         old_server_urls = set(self.servers)
         current_server_urls = {
-            f"http://{server._internal_ip}:{server.port}" for server in server_works if server._internal_ip
+            f"http://{server._public_ip}:{server.port}" for server in server_works if server._internal_ip
         }
 
         # doing nothing if no server work has been added/removed
diff --git a/src/lightning/app/core/work.py b/src/lightning/app/core/work.py
index 67b3fb0361dfd..f5416c0cfae3d 100644
--- a/src/lightning/app/core/work.py
+++ b/src/lightning/app/core/work.py
@@ -60,6 +60,7 @@ class LightningWork:
         "_url",
         "_restarting",
         "_internal_ip",
+        "_public_ip",
     )
 
     _run_executor_cls: Type[WorkRunExecutor] = WorkRunExecutor
@@ -138,6 +139,7 @@ def __init__(
             "_url",
             "_future_url",
             "_internal_ip",
+            "_public_ip",
             "_restarting",
             "_cloud_compute",
             "_display_name",
@@ -148,6 +150,7 @@ def __init__(
         self._url: str = ""
         self._future_url: str = ""  # The cache URL is meant to defer resolving the url values.
         self._internal_ip: str = ""
+        self._public_ip: str = ""
         # setattr_replacement is used by the multiprocessing runtime to send the latest changes to the main coordinator
         self._setattr_replacement: Optional[Callable[[str, Any], None]] = None
         self._name: str = ""
@@ -212,6 +215,15 @@ def internal_ip(self) -> str:
         """
         return self._internal_ip
 
+    @property
+    def public_ip(self) -> str:
+        """The public ip address of this LightningWork, reachable from the internet.
+
+        By default, this attribute returns the empty string and the ip address will only be returned once the work runs.
+        Locally, this address is undefined (empty string) and in the cloud it will be determined by the cluster.
+        """
+        return self._public_ip
+
     def _on_init_end(self) -> None:
         self._local_build_config.on_work_init(self)
         self._cloud_build_config.on_work_init(self, self._cloud_compute)
diff --git a/src/lightning/app/utilities/proxies.py b/src/lightning/app/utilities/proxies.py
index 9c5a53f2b98e6..39d33785068ac 100644
--- a/src/lightning/app/utilities/proxies.py
+++ b/src/lightning/app/utilities/proxies.py
@@ -494,7 +494,8 @@ def run_once(self):
         # Set this here after the state observer is initialized, since it needs to record it as a change and send
         # it back to the flow
         default_internal_ip = "127.0.0.1" if constants.LIGHTNING_CLOUDSPACE_HOST is None else "0.0.0.0"  # noqa: S104
-        self.work._internal_ip = os.environ.get("LIGHTNING_NODE_IP", default_internal_ip)
+        self.work._internal_ip = os.environ.get("LIGHTNING_NODE_PRIVATE_IP", default_internal_ip)
+        self.work._public_ip = os.environ.get("LIGHTNING_NODE_IP", "")
 
         # 8. Patch the setattr method of the work. This needs to be done after step 4, so we don't
         # send delta while calling `set_state`.
diff --git a/src/lightning/fabric/CHANGELOG.md b/src/lightning/fabric/CHANGELOG.md
index 043ae2aab61e3..04215ccb8289a 100644
--- a/src/lightning/fabric/CHANGELOG.md
+++ b/src/lightning/fabric/CHANGELOG.md
@@ -7,9 +7,18 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ## [UnReleased] - 2023-04-DD
 
+- Added support for `Callback` registration through entry points ([#17756](https://github.com/Lightning-AI/lightning/pull/17756))
+
+
+- Add Fabric internal hooks ([#17759](https://github.com/Lightning-AI/lightning/pull/17759))
+
+
 ### Changed
 
--
+- Made type hints public ([#17100](https://github.com/Lightning-AI/lightning/pull/17100))
+
+
+- Support compiling a module after it was set up by Fabric ([#17529](https://github.com/Lightning-AI/lightning/pull/17529))
 
 
 ### Fixed
diff --git a/src/lightning/fabric/fabric.py b/src/lightning/fabric/fabric.py
index f12dc56ce707e..1167a92358d8c 100644
--- a/src/lightning/fabric/fabric.py
+++ b/src/lightning/fabric/fabric.py
@@ -43,6 +43,7 @@
     has_iterable_dataset,
 )
 from lightning.fabric.utilities.distributed import DistributedSamplerWrapper
+from lightning.fabric.utilities.registry import _load_external_callbacks
 from lightning.fabric.utilities.seed import seed_everything
 from lightning.fabric.utilities.types import ReduceOp
 from lightning.fabric.utilities.warnings import PossibleUserWarning
@@ -105,8 +106,7 @@ def __init__(
         self._strategy: Strategy = self._connector.strategy
         self._accelerator: Accelerator = self._connector.accelerator
         self._precision: Precision = self._strategy.precision
-        callbacks = callbacks if callbacks is not None else []
-        self._callbacks = callbacks if isinstance(callbacks, list) else [callbacks]
+        self._callbacks = self._configure_callbacks(callbacks)
         loggers = loggers if loggers is not None else []
         self._loggers = loggers if isinstance(loggers, list) else [loggers]
         self._models_setup: int = 0
@@ -212,7 +212,10 @@ def setup(
         # Update the _DeviceDtypeModuleMixin's device parameter
         module.to(self.device if move_to_device else next(module.parameters(), torch.tensor(0)).device)
 
-        optimizers = [_FabricOptimizer(optimizer=optimizer, strategy=self._strategy) for optimizer in optimizers]
+        optimizers = [
+            _FabricOptimizer(optimizer=optimizer, strategy=self._strategy, callbacks=self._callbacks)
+            for optimizer in optimizers
+        ]
 
         self._models_setup += 1
 
@@ -220,6 +223,8 @@ def setup(
             original_module._fabric = self  # type: ignore[assignment]
             original_module._fabric_optimizers = optimizers  # type: ignore[assignment]
 
+        self.call("on_after_setup", fabric=self, module=module)
+
         if optimizers:
             # join both types in a tuple for API convenience
             return (module, *optimizers)
@@ -276,7 +281,10 @@ def setup_optimizers(self, *optimizers: Optimizer) -> Union[_FabricOptimizer, Tu
         """
         self._validate_setup_optimizers(optimizers)
         optimizers = [self._strategy.setup_optimizer(optimizer) for optimizer in optimizers]
-        optimizers = [_FabricOptimizer(optimizer=optimizer, strategy=self._strategy) for optimizer in optimizers]
+        optimizers = [
+            _FabricOptimizer(optimizer=optimizer, strategy=self._strategy, callbacks=self._callbacks)
+            for optimizer in optimizers
+        ]
         return optimizers[0] if len(optimizers) == 1 else tuple(optimizers)
 
     def setup_dataloaders(
@@ -838,6 +846,13 @@ def _validate_setup_dataloaders(dataloaders: Sequence[DataLoader]) -> None:
         if any(not isinstance(dl, DataLoader) for dl in dataloaders):
             raise TypeError("Only PyTorch DataLoader are currently supported in `setup_dataloaders`.")
 
+    @staticmethod
+    def _configure_callbacks(callbacks: Optional[Union[List[Any], Any]]) -> List[Any]:
+        callbacks = callbacks if callbacks is not None else []
+        callbacks = callbacks if isinstance(callbacks, list) else [callbacks]
+        callbacks.extend(_load_external_callbacks("lightning.fabric.callbacks_factory"))
+        return callbacks
+
 
 def _is_using_cli() -> bool:
     return bool(int(os.environ.get("LT_CLI_USED", "0")))
diff --git a/src/lightning/fabric/utilities/imports.py b/src/lightning/fabric/utilities/imports.py
index bdf3d6f3b34c6..6c63ecaa1eeb1 100644
--- a/src/lightning/fabric/utilities/imports.py
+++ b/src/lightning/fabric/utilities/imports.py
@@ -30,3 +30,6 @@
 _TORCH_GREATER_EQUAL_2_0 = compare_version("torch", operator.ge, "2.0.0", use_base_version=True)
 _TORCH_GREATER_EQUAL_2_1 = compare_version("torch", operator.ge, "2.1.0", use_base_version=True)
 _TORCH_EQUAL_2_0 = _TORCH_GREATER_EQUAL_2_0 and not _TORCH_GREATER_EQUAL_2_1
+
+_PYTHON_GREATER_EQUAL_3_8_0 = (sys.version_info.major, sys.version_info.minor) >= (3, 8)
+_PYTHON_GREATER_EQUAL_3_10_0 = (sys.version_info.major, sys.version_info.minor) >= (3, 10)
diff --git a/src/lightning/fabric/utilities/registry.py b/src/lightning/fabric/utilities/registry.py
index 10903d039ec7d..4c3c96dc5803e 100644
--- a/src/lightning/fabric/utilities/registry.py
+++ b/src/lightning/fabric/utilities/registry.py
@@ -12,7 +12,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import inspect
-from typing import Any
+import logging
+from typing import Any, List, Union
+
+from lightning.fabric.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0, _PYTHON_GREATER_EQUAL_3_10_0
+
+_log = logging.getLogger(__name__)
 
 
 def _is_register_method_overridden(mod: type, base_cls: Any, method: str) -> bool:
@@ -25,3 +30,40 @@ def _is_register_method_overridden(mod: type, base_cls: Any, method: str) -> boo
         return False
 
     return mod_attr.__code__ is not super_attr.__code__
+
+
+def _load_external_callbacks(group: str) -> List[Any]:
+    """Collect external callbacks registered through entry points.
+
+    The entry points are expected to be functions returning a list of callbacks.
+
+    Args:
+        group: The entry point group name to load callbacks from.
+
+    Return:
+        A list of all callbacks collected from external factories.
+    """
+    if _PYTHON_GREATER_EQUAL_3_8_0:
+        from importlib.metadata import entry_points
+
+        factories = (
+            entry_points(group=group)
+            if _PYTHON_GREATER_EQUAL_3_10_0
+            else entry_points().get(group, {})  # type: ignore[arg-type]
+        )
+    else:
+        from pkg_resources import iter_entry_points
+
+        factories = iter_entry_points(group)  # type: ignore[assignment]
+
+    external_callbacks: List[Any] = []
+    for factory in factories:
+        callback_factory = factory.load()
+        callbacks_list: Union[List[Any], Any] = callback_factory()
+        callbacks_list = [callbacks_list] if not isinstance(callbacks_list, list) else callbacks_list
+        _log.info(
+            f"Adding {len(callbacks_list)} callbacks from entry point '{factory.name}':"
+            f" {', '.join(type(cb).__name__ for cb in callbacks_list)}"
+        )
+        external_callbacks.extend(callbacks_list)
+    return external_callbacks
diff --git a/src/lightning/fabric/wrappers.py b/src/lightning/fabric/wrappers.py
index 947510244d0df..8ed10f00c5511 100644
--- a/src/lightning/fabric/wrappers.py
+++ b/src/lightning/fabric/wrappers.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import inspect
-from typing import Any, Callable, Dict, Generator, Iterator, Mapping, Optional, overload, TypeVar, Union
+from typing import Any, Callable, Dict, Generator, Iterator, List, Mapping, Optional, overload, TypeVar, Union
 
 import torch
 from lightning_utilities import WarningCache
@@ -38,7 +38,7 @@
 
 
 class _FabricOptimizer:
-    def __init__(self, optimizer: Optimizer, strategy: Strategy) -> None:
+    def __init__(self, optimizer: Optimizer, strategy: Strategy, callbacks: Optional[List[Callable]] = None) -> None:
         """FabricOptimizer is a thin wrapper around the :class:`~torch.optim.Optimizer` that delegates the
         optimizer step calls to the strategy plugin.
 
@@ -54,6 +54,7 @@ def __init__(self, optimizer: Optimizer, strategy: Strategy) -> None:
         self.__class__ = type("Fabric" + optimizer.__class__.__name__, (self.__class__, optimizer.__class__), {})
         self._optimizer = optimizer
         self._strategy = strategy
+        self._callbacks = callbacks or []
 
     @property
     def optimizer(self) -> Optimizer:
@@ -69,10 +70,15 @@ def step(self, closure: Optional[Callable] = None) -> Any:
             optimizer = self._strategy.model
         else:
             optimizer = self.optimizer
-        return self._strategy.optimizer_step(
+        output = self._strategy.optimizer_step(
             optimizer,
             **kwargs,
         )
+        for callback in self._callbacks:
+            hook = getattr(callback, "on_after_optimizer_step", None)
+            if callable(hook):
+                hook(strategy=self._strategy, optimizer=optimizer)
+        return output
 
 
 class _FabricModule(_DeviceDtypeModuleMixin):
diff --git a/src/lightning/pytorch/CHANGELOG.md b/src/lightning/pytorch/CHANGELOG.md
index 0500e336f2268..5f7ed4645d847 100644
--- a/src/lightning/pytorch/CHANGELOG.md
+++ b/src/lightning/pytorch/CHANGELOG.md
@@ -9,6 +9,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Changed
 
+- Made type hints public ([#17100](https://github.com/Lightning-AI/lightning/pull/17100))
+
+
 -
 
 
@@ -41,6 +44,15 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed an edge case causing overlapping samples in DDP when no global seed is set ([#17713](https://github.com/Lightning-AI/lightning/pull/17713))
 
 
+- Fallback to module available check for mlflow ([#17467](https://github.com/Lightning-AI/lightning/pull/17467))
+
+
+- Fixed LR finder max val batches ([#17636](https://github.com/Lightning-AI/lightning/pull/17636))
+
+
+- Fixed multithreading checkpoint loading ([#17678](https://github.com/Lightning-AI/lightning/pull/17678))
+
+
 ## [2.0.2] - 2023-04-24
 
 ### Fixed
diff --git a/src/lightning/pytorch/trainer/connectors/callback_connector.py b/src/lightning/pytorch/trainer/connectors/callback_connector.py
index 8195a5c4a3b52..d649755172658 100644
--- a/src/lightning/pytorch/trainer/connectors/callback_connector.py
+++ b/src/lightning/pytorch/trainer/connectors/callback_connector.py
@@ -18,6 +18,7 @@
 from typing import Dict, List, Optional, Sequence, Union
 
 import lightning.pytorch as pl
+from lightning.fabric.utilities.registry import _load_external_callbacks
 from lightning.pytorch.callbacks import (
     Callback,
     Checkpoint,
@@ -33,7 +34,6 @@
 from lightning.pytorch.callbacks.timer import Timer
 from lightning.pytorch.trainer import call
 from lightning.pytorch.utilities.exceptions import MisconfigurationException
-from lightning.pytorch.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0, _PYTHON_GREATER_EQUAL_3_10_0
 from lightning.pytorch.utilities.model_helpers import is_overridden
 from lightning.pytorch.utilities.rank_zero import rank_zero_info
 
@@ -75,7 +75,7 @@ def on_trainer_init(
         # configure the ModelSummary callback
         self._configure_model_summary_callback(enable_model_summary)
 
-        self.trainer.callbacks.extend(_configure_external_callbacks())
+        self.trainer.callbacks.extend(_load_external_callbacks("lightning.pytorch.callbacks_factory"))
         _validate_callbacks_list(self.trainer.callbacks)
 
         # push all model checkpoint callbacks to the end
@@ -213,42 +213,6 @@ def _reorder_callbacks(callbacks: List[Callback]) -> List[Callback]:
         return tuner_callbacks + other_callbacks + checkpoint_callbacks
 
 
-def _configure_external_callbacks() -> List[Callback]:
-    """Collect external callbacks registered through entry points.
-
-    The entry points are expected to be functions returning a list of callbacks.
-
-    Return:
-        A list of all callbacks collected from external factories.
-    """
-    group = "lightning.pytorch.callbacks_factory"
-
-    if _PYTHON_GREATER_EQUAL_3_8_0:
-        from importlib.metadata import entry_points
-
-        factories = (
-            entry_points(group=group)
-            if _PYTHON_GREATER_EQUAL_3_10_0
-            else entry_points().get(group, {})  # type: ignore[arg-type]
-        )
-    else:
-        from pkg_resources import iter_entry_points
-
-        factories = iter_entry_points(group)  # type: ignore[assignment]
-
-    external_callbacks: List[Callback] = []
-    for factory in factories:
-        callback_factory = factory.load()
-        callbacks_list: Union[List[Callback], Callback] = callback_factory()
-        callbacks_list = [callbacks_list] if isinstance(callbacks_list, Callback) else callbacks_list
-        _log.info(
-            f"Adding {len(callbacks_list)} callbacks from entry point '{factory.name}':"
-            f" {', '.join(type(cb).__name__ for cb in callbacks_list)}"
-        )
-        external_callbacks.extend(callbacks_list)
-    return external_callbacks
-
-
 def _validate_callbacks_list(callbacks: List[Callback]) -> None:
     stateful_callbacks = [cb for cb in callbacks if is_overridden("state_dict", instance=cb)]
     seen_callbacks = set()
diff --git a/src/lightning/pytorch/trainer/connectors/signal_connector.py b/src/lightning/pytorch/trainer/connectors/signal_connector.py
index 1f48386e3ff86..7e6b7cd0c5e91 100644
--- a/src/lightning/pytorch/trainer/connectors/signal_connector.py
+++ b/src/lightning/pytorch/trainer/connectors/signal_connector.py
@@ -11,8 +11,7 @@
 
 import lightning.pytorch as pl
 from lightning.fabric.plugins.environments import SLURMEnvironment
-from lightning.fabric.utilities.imports import _IS_WINDOWS
-from lightning.pytorch.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0
+from lightning.fabric.utilities.imports import _IS_WINDOWS, _PYTHON_GREATER_EQUAL_3_8_0
 from lightning.pytorch.utilities.rank_zero import rank_zero_info
 
 # copied from signal.pyi
diff --git a/src/lightning/pytorch/utilities/imports.py b/src/lightning/pytorch/utilities/imports.py
index 259f18070362b..bfb1eeb5c5174 100644
--- a/src/lightning/pytorch/utilities/imports.py
+++ b/src/lightning/pytorch/utilities/imports.py
@@ -17,8 +17,6 @@
 import torch
 from lightning_utilities.core.imports import package_available, RequirementCache
 
-_PYTHON_GREATER_EQUAL_3_8_0 = (sys.version_info.major, sys.version_info.minor) >= (3, 8)
-_PYTHON_GREATER_EQUAL_3_10_0 = (sys.version_info.major, sys.version_info.minor) >= (3, 10)
 _PYTHON_GREATER_EQUAL_3_11_0 = (sys.version_info.major, sys.version_info.minor) >= (3, 11)
 _TORCHMETRICS_GREATER_EQUAL_0_9_1 = RequirementCache("torchmetrics>=0.9.1")
 _TORCHMETRICS_GREATER_EQUAL_0_11 = RequirementCache("torchmetrics>=0.11.0")  # using new API with task
diff --git a/src/version.info b/src/version.info
index e9307ca5751b2..50ffc5aa7f69f 100644
--- a/src/version.info
+++ b/src/version.info
@@ -1 +1 @@
-2.0.2
+2.0.3
diff --git a/tests/tests_app/core/test_lightning_app.py b/tests/tests_app/core/test_lightning_app.py
index f5933747293e6..ed451475b5e80 100644
--- a/tests/tests_app/core/test_lightning_app.py
+++ b/tests/tests_app/core/test_lightning_app.py
@@ -119,6 +119,7 @@ def test_simple_app(tmpdir):
                     "_url": "",
                     "_future_url": "",
                     "_internal_ip": "",
+                    "_public_ip": "",
                     "_paths": {},
                     "_port": None,
                     "_restarting": False,
@@ -136,6 +137,7 @@ def test_simple_app(tmpdir):
                     "_url": "",
                     "_future_url": "",
                     "_internal_ip": "",
+                    "_public_ip": "",
                     "_paths": {},
                     "_port": None,
                     "_restarting": False,
@@ -982,7 +984,7 @@ def run(self):
 def test_state_size_constant_growth():
     app = LightningApp(SizeFlow())
     MultiProcessRuntime(app, start_server=False).dispatch()
-    assert app.root._state_sizes[0] <= 7965
+    assert app.root._state_sizes[0] <= 8304
     assert app.root._state_sizes[20] <= 26550
 
 
diff --git a/tests/tests_app/core/test_lightning_flow.py b/tests/tests_app/core/test_lightning_flow.py
index 9b174f5a3af8a..fe66a9bb10124 100644
--- a/tests/tests_app/core/test_lightning_flow.py
+++ b/tests/tests_app/core/test_lightning_flow.py
@@ -324,6 +324,7 @@ def run(self):
                     "_paths": {},
                     "_restarting": False,
                     "_internal_ip": "",
+                    "_public_ip": "",
                     "_display_name": "",
                     "_cloud_compute": {
                         "type": "__cloud_compute__",
@@ -349,6 +350,7 @@ def run(self):
                     "_paths": {},
                     "_restarting": False,
                     "_internal_ip": "",
+                    "_public_ip": "",
                     "_display_name": "",
                     "_cloud_compute": {
                         "type": "__cloud_compute__",
@@ -388,6 +390,7 @@ def run(self):
                     "_paths": {},
                     "_restarting": False,
                     "_internal_ip": "",
+                    "_public_ip": "",
                     "_display_name": "",
                     "_cloud_compute": {
                         "type": "__cloud_compute__",
@@ -413,6 +416,7 @@ def run(self):
                     "_paths": {},
                     "_restarting": False,
                     "_internal_ip": "",
+                    "_public_ip": "",
                     "_display_name": "",
                     "_cloud_compute": {
                         "type": "__cloud_compute__",
diff --git a/tests/tests_app/structures/test_structures.py b/tests/tests_app/structures/test_structures.py
index f921607a50734..4cbe391027d8a 100644
--- a/tests/tests_app/structures/test_structures.py
+++ b/tests/tests_app/structures/test_structures.py
@@ -46,6 +46,7 @@ def run(self):
             "_restarting": False,
             "_display_name": "",
             "_internal_ip": "",
+            "_public_ip": "",
             "_cloud_compute": {
                 "type": "__cloud_compute__",
                 "name": "cpu-small",
@@ -80,6 +81,7 @@ def run(self):
             "_restarting": False,
             "_display_name": "",
             "_internal_ip": "",
+            "_public_ip": "",
             "_cloud_compute": {
                 "type": "__cloud_compute__",
                 "name": "cpu-small",
@@ -114,6 +116,7 @@ def run(self):
             "_restarting": False,
             "_display_name": "",
             "_internal_ip": "",
+            "_public_ip": "",
             "_cloud_compute": {
                 "type": "__cloud_compute__",
                 "name": "cpu-small",
@@ -199,6 +202,7 @@ def run(self):
             "_paths": {},
             "_restarting": False,
             "_internal_ip": "",
+            "_public_ip": "",
             "_display_name": "",
             "_cloud_compute": {
                 "type": "__cloud_compute__",
@@ -233,6 +237,7 @@ def run(self):
             "_paths": {},
             "_restarting": False,
             "_internal_ip": "",
+            "_public_ip": "",
             "_display_name": "",
             "_cloud_compute": {
                 "type": "__cloud_compute__",
@@ -262,6 +267,7 @@ def run(self):
             "_paths": {},
             "_restarting": False,
             "_internal_ip": "",
+            "_public_ip": "",
             "_display_name": "",
             "_cloud_compute": {
                 "type": "__cloud_compute__",
diff --git a/tests/tests_app/utilities/test_proxies.py b/tests/tests_app/utilities/test_proxies.py
index a4661e2736aaa..8dbfe1b06b871 100644
--- a/tests/tests_app/utilities/test_proxies.py
+++ b/tests/tests_app/utilities/test_proxies.py
@@ -641,16 +641,21 @@ def test_state_observer():
 
 
 @pytest.mark.parametrize(
-    ("patch_constants", "environment", "expected_ip_addr"),
+    ("patch_constants", "environment", "expected_public_ip", "expected_private_ip"),
     [
-        ({}, {}, "127.0.0.1"),
-        ({"LIGHTNING_CLOUDSPACE_HOST": "any"}, {}, "0.0.0.0"),  # noqa: S104
-        ({}, {"LIGHTNING_NODE_IP": "10.10.10.5"}, "10.10.10.5"),
+        ({}, {}, "", "127.0.0.1"),
+        ({"LIGHTNING_CLOUDSPACE_HOST": "any"}, {}, "", "0.0.0.0"),  # noqa: S104
+        (
+            {},
+            {"LIGHTNING_NODE_IP": "85.44.2.25", "LIGHTNING_NODE_PRIVATE_IP": "10.10.10.5"},
+            "85.44.2.25",
+            "10.10.10.5",
+        ),
     ],
     indirect=["patch_constants"],
 )
-def test_work_runner_sets_internal_ip(patch_constants, environment, expected_ip_addr):
-    """Test that the WorkRunner updates the internal ip address as soon as the Work starts running."""
+def test_work_runner_sets_public_and_private_ip(patch_constants, environment, expected_public_ip, expected_private_ip):
+    """Test that the WorkRunner updates the public and private address as soon as the Work starts running."""
 
     class Work(LightningWork):
         def run(self):
@@ -690,11 +695,13 @@ def run(self):
 
     with mock.patch.dict(os.environ, environment, clear=True):
         work_runner.setup()
-        # The internal ip address only becomes available once the hardware is up / the work is running.
+        # The public ip address only becomes available once the hardware is up / the work is running.
+        assert work.public_ip == ""
         assert work.internal_ip == ""
         with contextlib.suppress(Empty):
             work_runner.run_once()
-        assert work.internal_ip == expected_ip_addr
+        assert work.public_ip == expected_public_ip
+        assert work.internal_ip == expected_private_ip
 
 
 class WorkBi(LightningWork):
diff --git a/tests/tests_fabric/test_fabric.py b/tests/tests_fabric/test_fabric.py
index 58ab0e34166ed..015d1aba41359 100644
--- a/tests/tests_fabric/test_fabric.py
+++ b/tests/tests_fabric/test_fabric.py
@@ -753,6 +753,29 @@ def test_call():
     assert not callback1.mock_calls
 
 
+def test_special_callbacks():
+    """Tests special callbacks that have hooks for internal Fabric events."""
+
+    class SpecialCallback:
+        def on_after_optimizer_step(self, strategy, optimizer):
+            pass
+
+        def on_after_setup(self, fabric, module):
+            pass
+
+    callback = Mock(wraps=SpecialCallback())
+    fabric = Fabric(accelerator="cpu", callbacks=[callback])
+
+    model = torch.nn.Linear(2, 2)
+    optimizer = torch.optim.SGD(model.parameters(), lr=0.1)
+    fabric_model, fabric_optimizer = fabric.setup(model, optimizer)
+    callback.on_after_setup.assert_called_once_with(fabric=fabric, module=fabric_model)
+
+    model(torch.randn(2, 2)).sum().backward()
+    fabric_optimizer.step()
+    callback.on_after_optimizer_step.assert_called_once_with(strategy=fabric._strategy, optimizer=optimizer)
+
+
 def test_loggers_input():
     """Test the various ways in which loggers can be registered with Fabric."""
     logger0 = Mock()
diff --git a/tests/tests_fabric/utilities/test_registry.py b/tests/tests_fabric/utilities/test_registry.py
new file mode 100644
index 0000000000000..75e6e12f5abff
--- /dev/null
+++ b/tests/tests_fabric/utilities/test_registry.py
@@ -0,0 +1,64 @@
+import contextlib
+from unittest import mock
+from unittest.mock import Mock
+
+from lightning.fabric.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0, _PYTHON_GREATER_EQUAL_3_10_0
+from lightning.fabric.utilities.registry import _load_external_callbacks
+
+
+class ExternalCallback:
+    """A callback in another library that gets registered through entry points."""
+
+    pass
+
+
+def test_load_external_callbacks():
+    """Test that the connector collects Callback instances from factories registered through entry points."""
+
+    def factory_no_callback():
+        return []
+
+    def factory_one_callback():
+        return ExternalCallback()
+
+    def factory_one_callback_list():
+        return [ExternalCallback()]
+
+    def factory_multiple_callbacks_list():
+        return [ExternalCallback(), ExternalCallback()]
+
+    with _make_entry_point_query_mock(factory_no_callback):
+        callbacks = _load_external_callbacks("lightning.pytorch.callbacks_factory")
+    assert callbacks == []
+
+    with _make_entry_point_query_mock(factory_one_callback):
+        callbacks = _load_external_callbacks("lightning.pytorch.callbacks_factory")
+    assert isinstance(callbacks[0], ExternalCallback)
+
+    with _make_entry_point_query_mock(factory_one_callback_list):
+        callbacks = _load_external_callbacks("lightning.pytorch.callbacks_factory")
+    assert isinstance(callbacks[0], ExternalCallback)
+
+    with _make_entry_point_query_mock(factory_multiple_callbacks_list):
+        callbacks = _load_external_callbacks("lightning.pytorch.callbacks_factory")
+    assert isinstance(callbacks[0], ExternalCallback)
+    assert isinstance(callbacks[1], ExternalCallback)
+
+
+@contextlib.contextmanager
+def _make_entry_point_query_mock(callback_factory):
+    query_mock = Mock()
+    entry_point = Mock()
+    entry_point.name = "mocked"
+    entry_point.load.return_value = callback_factory
+    if _PYTHON_GREATER_EQUAL_3_10_0:
+        query_mock.return_value = [entry_point]
+        import_path = "importlib.metadata.entry_points"
+    elif _PYTHON_GREATER_EQUAL_3_8_0:
+        query_mock().get.return_value = [entry_point]
+        import_path = "importlib.metadata.entry_points"
+    else:
+        query_mock.return_value = [entry_point]
+        import_path = "pkg_resources.iter_entry_points"
+    with mock.patch(import_path, query_mock):
+        yield
diff --git a/tests/tests_pytorch/trainer/connectors/test_callback_connector.py b/tests/tests_pytorch/trainer/connectors/test_callback_connector.py
index 71262df9179e8..58f59ad760763 100644
--- a/tests/tests_pytorch/trainer/connectors/test_callback_connector.py
+++ b/tests/tests_pytorch/trainer/connectors/test_callback_connector.py
@@ -19,6 +19,7 @@
 import pytest
 import torch
 
+from lightning.fabric.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0, _PYTHON_GREATER_EQUAL_3_10_0
 from lightning.pytorch import Callback, LightningModule, Trainer
 from lightning.pytorch.callbacks import (
     EarlyStopping,
@@ -32,7 +33,6 @@
 from lightning.pytorch.callbacks.batch_size_finder import BatchSizeFinder
 from lightning.pytorch.demos.boring_classes import BoringModel
 from lightning.pytorch.trainer.connectors.callback_connector import _CallbackConnector
-from lightning.pytorch.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0, _PYTHON_GREATER_EQUAL_3_10_0
 
 
 def test_checkpoint_callbacks_are_last(tmpdir):
diff --git a/tests/tests_pytorch/trainer/logging_/test_eval_loop_logging.py b/tests/tests_pytorch/trainer/logging_/test_eval_loop_logging.py
index 36f6356f995cb..cea40b921e1a5 100644
--- a/tests/tests_pytorch/trainer/logging_/test_eval_loop_logging.py
+++ b/tests/tests_pytorch/trainer/logging_/test_eval_loop_logging.py
@@ -25,6 +25,7 @@
 import torch
 from torch import Tensor
 
+from lightning.fabric.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0
 from lightning.pytorch import callbacks, Trainer
 from lightning.pytorch.callbacks.progress.rich_progress import _RICH_AVAILABLE
 from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
@@ -32,7 +33,6 @@
 from lightning.pytorch.loops import _EvaluationLoop
 from lightning.pytorch.trainer.states import RunningStage
 from lightning.pytorch.utilities.exceptions import MisconfigurationException
-from lightning.pytorch.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0
 from tests_pytorch.helpers.runif import RunIf
 
 if _RICH_AVAILABLE: