docs(examples) Add link to how-to guide for running with Deployment E…

…ngine (#4733)

Co-authored-by: jafermarq <[email protected]>

examples/advanced-pytorch/README.md

@@ -63,7 +63,7 @@ By default, the metrics: {`centralized_accuracy`, `centralized_loss`, `federated
 With default parameters, 25% of the total 50 nodes (see `num-supernodes` in `pyproject.toml`) will be sampled for `fit` and 50% for an `evaluate` round. By default `ClientApp` objects will run on CPU.
 
 > \[!TIP\]
-> To run your `ClientApps` on GPU or to adjust the degree or parallelism of your simulation, edit the `[tool.flwr.federations.local-simulation]` section in the `pyproject.tom`.
+> To run your `ClientApps` on GPU or to adjust the degree or parallelism of your simulation, edit the `[tool.flwr.federations.local-simulation]` section in the `pyproject.tom`. Check the [Simulation Engine documentation](https://flower.ai/docs/framework/how-to-run-simulations.html) to learn more about Flower simulations and how to optimize them.
 
 ```bash
 flwr run .
@@ -86,5 +86,6 @@ flwr run . --run-config "num-server-rounds=5 fraction-fit=0.5"
 
 ### Run with the Deployment Engine
 
-> \[!NOTE\]
-> An update to this example will show how to run this Flower application with the Deployment Engine and TLS certificates, or with Docker.
+Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.
+
+If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.

examples/advanced-tensorflow/README.md

@@ -63,7 +63,7 @@ By default, the metrics: {`centralized_accuracy`, `centralized_loss`, `federated
 With default parameters, 25% of the total 50 nodes (see `num-supernodes` in `pyproject.toml`) will be sampled for `fit` and 50% for an `evaluate` round. By default `ClientApp` objects will run on CPU.
 
 > \[!TIP\]
-> To run your `ClientApps` on GPU or to adjust the degree or parallelism of your simulation, edit the `[tool.flwr.federations.local-simulation]` section in the `pyproject.toml`.
+> To run your `ClientApps` on GPU or to adjust the degree or parallelism of your simulation, edit the `[tool.flwr.federations.local-simulation]` section in the `pyproject.toml`. Check the [Simulation Engine documentation](https://flower.ai/docs/framework/how-to-run-simulations.html) to learn more about Flower simulations and how to optimize them.
 
 ```bash
 flwr run .
@@ -90,5 +90,6 @@ flwr run . --run-config "num-server-rounds=10 fraction-fit=0.5"
 
 ### Run with the Deployment Engine
 
-> \[!NOTE\]
-> An update to this example will show how to run this Flower application with the Deployment Engine and TLS certificates, or with Docker.
+Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.
+
+If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.

examples/custom-metrics/README.md

@@ -71,5 +71,6 @@ flwr run . --run-config num-server-rounds=5
 
 ### Run with the Deployment Engine
 
-> \[!NOTE\]
-> An update to this example will show how to run this Flower application with the Deployment Engine and TLS certificates, or with Docker.
+Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.
+
+If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.

examples/embedded-devices/README.md

@@ -81,6 +81,9 @@ pip install -e .
 
 ## Embedded Federated AI
 
+> \[!TIP\]
+> Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to learn more about Flower's Deployment Engine, how setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) works. If you are already familiar with how the Deployment Engine works, you may want to learn how to run this same example using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.
+
 For this demo, we'll be using [Fashion-MNIST](https://huggingface.co/datasets/zalando-datasets/fashion_mnist), a popular dataset for image classification comprised of 10 classes (e.g. boot, dress, trouser) and a total of 70K `28x28` greyscale images. The training set contains 60K images.
 
 > \[!TIP\]

examples/federated-kaplan-meier-fitter/README.md

@@ -80,5 +80,6 @@ $ python3 centralized.py
 
 ### Run with the Deployment Engine
 
-> \[!NOTE\]
-> An update to this example will show how to run this Flower application with the Deployment Engine and TLS certificates, or with Docker.
+Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.
+
+If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.

examples/fl-dp-sa/README.md

@@ -47,6 +47,9 @@ You can run your Flower project in both _simulation_ and _deployment_ mode witho
 
 ### Run with the Simulation Engine
 
+> \[!NOTE\]
+> Check the [Simulation Engine documentation](https://flower.ai/docs/framework/how-to-run-simulations.html) to learn more about Flower simulations and how to optimize them.
+
 ```bash
 flwr run .
 ```
@@ -59,5 +62,6 @@ flwr run . --run-config "noise-multiplier=0.1 clipping-norm=5"
 
 ### Run with the Deployment Engine
 
-> \[!NOTE\]
-> An update to this example will show how to run this Flower project with the Deployment Engine and TLS certificates, or with Docker.
+Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.
+
+If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.

examples/fl-tabular/README.md

@@ -50,6 +50,9 @@ fewer components to be launched manually. By default, `flwr run` will make use o
 
 ### Run with the Simulation Engine
 
+> \[!NOTE\]
+> Check the [Simulation Engine documentation](https://flower.ai/docs/framework/how-to-run-simulations.html) to learn more about Flower simulations and how to optimize them.
+
 ```bash
 flwr run .
 ```
@@ -62,5 +65,6 @@ flwr run . --run-config num-server-rounds=10
 
 ### Run with the Deployment Engine
 
-> \[!NOTE\]
-> An update to this example will show how to run this Flower application with the Deployment Engine and TLS certificates, or with Docker.
+Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.
+
+If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.

examples/flower-authentication/README.md

@@ -12,6 +12,9 @@ framework: [torch, torchvision]
 
 The following steps describe how to start a long-running Flower server (SuperLink) and a long-running Flower clients (SuperNode) with authentication enabled. The task is to train a simple CNN for image classification using PyTorch.
 
+> \[!TIP\]
+> Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to learn more about Flower's Deployment Engine, how setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) works. If you are already familiar with how the Deployment Engine works, you may want to learn how to run this same example using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.
+
 ## Project Setup
 
 Start by cloning the example project. We prepared a single-line command that you can copy into your shell which will checkout the example for you:

examples/flower-secure-aggregation/README.md

@@ -50,6 +50,9 @@ You can run your Flower project in both _simulation_ and _deployment_ mode witho
 
 ### Run with the Simulation Engine
 
+> \[!NOTE\]
+> Check the [Simulation Engine documentation](https://flower.ai/docs/framework/how-to-run-simulations.html) to learn more about Flower simulations and how to optimize them.
+
 ```bash
 flwr run .
 ```
@@ -68,5 +71,6 @@ flwr run . --run-config is-demo=false
 
 ### Run with the Deployment Engine
 
-> \[!NOTE\]
-> An update to this example will show how to run this Flower project with the Deployment Engine and TLS certificates, or with Docker.
+Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.
+
+If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.

examples/flowertune-llm/README.md

@@ -55,6 +55,9 @@ You can run your Flower project in both _simulation_ and _deployment_ mode witho
 
 ### Run with the Simulation Engine
 
+> \[!NOTE\]
+> Check the [Simulation Engine documentation](https://flower.ai/docs/framework/how-to-run-simulations.html) to learn more about Flower simulations and how to optimize them.
+
 ```bash
 flwr run .
 ```
@@ -71,8 +74,9 @@ flwr run . --run-config "num-server-rounds=50 strategy.fraction-fit=0.25"
 
 ### Run with the Deployment Engine
 
-> \[!NOTE\]
-> An update to this example will show how to run this Flower application with the Deployment Engine and TLS certificates, or with Docker.
+Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.
+
+If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.
 
 ## Expected results
 

examples/flowertune-vit/README.md

@@ -49,7 +49,7 @@ You can run your Flower project in both _simulation_ and _deployment_ mode witho
 ### Run with the Simulation Engine
 
 > \[!TIP\]
-> This example runs faster when the `ClientApp`s have access to a GPU. If your system has one, you can make use of it by configuring the `backend.client-resources` component in `pyproject.toml`. If you want to try running the example with GPU right away, use the `local-simulation-gpu` federation as shown below.
+> This example runs faster when the `ClientApp`s have access to a GPU. If your system has one, you can make use of it by configuring the `backend.client-resources` component in `pyproject.toml`. If you want to try running the example with GPU right away, use the `local-simulation-gpu` federation as shown below. Check the [Simulation Engine documentation](https://flower.ai/docs/framework/how-to-run-simulations.html) to learn more about Flower simulations and how to optimize them.
 
 ```bash
 # Run with the default federation (CPU only)
@@ -102,5 +102,6 @@ Running the example as-is on an RTX 3090Ti should take ~15s/round running 5 clie
 
 ### Run with the Deployment Engine
 
-> \[!NOTE\]
-> An update to this example will show how to run this Flower project with the Deployment Engine and TLS certificates, or with Docker.
+Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.
+
+If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.

examples/opacus/README.md

@@ -49,6 +49,9 @@ You can run your Flower project in both _simulation_ and _deployment_ mode witho
 
 ### Run with the Simulation Engine
 
+> \[!NOTE\]
+> Check the [Simulation Engine documentation](https://flower.ai/docs/framework/how-to-run-simulations.html) to learn more about Flower simulations and how to optimize them.
+
 ```bash
 flwr run .
 ```

examples/pytorch-federated-variational-autoencoder/README.md

@@ -47,6 +47,9 @@ You can run your Flower project in both _simulation_ and _deployment_ mode witho
 
 ### Run with the Simulation Engine
 
+> \[!NOTE\]
+> Check the [Simulation Engine documentation](https://flower.ai/docs/framework/how-to-run-simulations.html) to learn more about Flower simulations and how to optimize them.
+
 ```bash
 flwr run .
 ```
@@ -59,5 +62,6 @@ flwr run . --run-config num-server-rounds=5
 
 ### Run with the Deployment Engine
 
-> \[!NOTE\]
-> An update to this example will show how to run this Flower application with the Deployment Engine and TLS certificates, or with Docker.
+Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.
+
+If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.

examples/quickstart-fastai/README.md

@@ -48,6 +48,9 @@ You can run your Flower project in both _simulation_ and _deployment_ mode witho
 
 ### Run with the Simulation Engine
 
+> \[!NOTE\]
+> Check the [Simulation Engine documentation](https://flower.ai/docs/framework/how-to-run-simulations.html) to learn more about Flower simulations and how to optimize them.
+
 ```bash
 flwr run .
 ```
@@ -60,5 +63,6 @@ flwr run . --run-config num-server-rounds=5
 
 ### Run with the Deployment Engine
 
-> \[!NOTE\]
-> An update to this example will show how to run this Flower application with the Deployment Engine and TLS certificates, or with Docker.
+Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.
+
+If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.

examples/quickstart-huggingface/README.md

@@ -50,7 +50,7 @@ You can run your Flower project in both _simulation_ and _deployment_ mode witho
 ### Run with the Simulation Engine
 
 > \[!TIP\]
-> This example runs faster when the `ClientApp`s have access to a GPU. If your system has one, you can make use of it by configuring the `backend.client-resources` component in `pyproject.toml`. If you want to try running the example with GPU right away, use the `local-simulation-gpu` federation as shown below.
+> This example runs faster when the `ClientApp`s have access to a GPU. If your system has one, you can make use of it by configuring the `backend.client-resources` component in `pyproject.toml`. If you want to try running the example with GPU right away, use the `local-simulation-gpu` federation as shown below. Check the [Simulation Engine documentation](https://flower.ai/docs/framework/how-to-run-simulations.html) to learn more about Flower simulations and how to optimize them.
 
 ```bash
 # Run with the default federation (CPU only)
@@ -75,5 +75,6 @@ flwr run --run-config "num-server-rounds=5 fraction-fit=0.1"
 
 ### Run with the Deployment Engine
 
-> \[!NOTE\]
-> An update to this example will show how to run this Flower project with the Deployment Engine and TLS certificates, or with Docker.
+Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.
+
+If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.