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name: "build containers" | ||
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on: | ||
workflow_dispatch: | ||
push: | ||
branches: | ||
- master | ||
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.. _architecture-label: | ||
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Architecture overview | ||
===================== | ||
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.. _developer-label: | ||
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Local development | ||
================= | ||
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.. note:: | ||
These instructions are for users wanting to set up a local development deployment of FEDn (i.e. without FEDn Studio). | ||
This requires practical knowledge of Docker and docker-compose. | ||
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Running the FEDn development sandbox (docker-compose) | ||
===================================================== | ||
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During development on FEDn, and when working on own aggregators/helpers, it is | ||
useful to have a local development setup of the core FEDn services (controller, combiner, database, object store). | ||
For this, we provide Dockerfiles and docker-compose template. | ||
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To start a development sandbox for FEDn using docker-compose: | ||
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.. code-block:: | ||
docker compose \ | ||
-f ../../docker-compose.yaml \ | ||
-f docker-compose.override.yaml \ | ||
up | ||
This starts up local services for MongoDB, Minio, the API Server, one Combiner and two clients. | ||
You can verify the deployment using these urls: | ||
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- API Server: http://localhost:8092/get_controller_status | ||
- Minio: http://localhost:9000 | ||
- Mongo Express: http://localhost:8081 | ||
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This setup does not include the security features of Studio, and thus will not require authentication of clients. | ||
To use the APIClient to test a compute package and seed model against a local FEDn deployment: | ||
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.. code-block:: | ||
from fedn import APIClient | ||
client = APIClient(host="localhost", port=8092) | ||
client.set_active_package("package.tgz", helper="numpyhelper") | ||
client.set_active_model("seed.npz") | ||
To connect a native FEDn client, you need to make sure that the combiner service can be resolved using the name "combiner". | ||
One way to achieve this is to edit your '/etc/hosts' and add a line '127.0.0.1 combiner'. | ||
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Access message logs and validation data from MongoDB | ||
==================================================== | ||
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You can access and download event logs and validation data via the API, and you can also as a developer obtain | ||
the MongoDB backend data using pymongo or via the MongoExpress interface: | ||
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- http://localhost:8081/db/fedn-network/ | ||
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Username and password are found in 'docker-compose.yaml'. | ||
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Access global models | ||
==================== | ||
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You can obtain global model updates from the 'fedn-models' bucket in Minio: | ||
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- http://localhost:9000 | ||
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Username and password are found in 'docker-compose.yaml'. | ||
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Reset the FEDn deployment | ||
========================= | ||
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To purge all data from a deployment incuding all session and round data, access the MongoExpress UI interface and | ||
delete the entire ``fedn-network`` collection. Then restart all services. | ||
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Clean up | ||
======== | ||
You can clean up by running | ||
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.. code-block:: | ||
docker-compose -f ../../docker-compose.yaml -f docker-compose.override.yaml down -v | ||
Connecting clients using Docker: | ||
================================ | ||
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For convenience, we distribute a Docker image hosted on ghrc.io with FEDn preinstalled. For example, to start a client for the MNIST PyTorch example using Docker | ||
and FEDN 0.10.0, run this from the example folder: | ||
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.. code-block:: | ||
docker run \ | ||
-v $PWD/client.yaml:/app/client.yaml \ | ||
-e FEDN_PACKAGE_EXTRACT_DIR=package \ | ||
-e FEDN_NUM_DATA_SPLITS=2 \ | ||
-e FEDN_DATA_PATH=/app/package/data/clients/1/mnist.pt \ | ||
ghcr.io/scaleoutsystems/fedn/fedn:0.10.0 run client -in client.yaml --force-ssl --secure=True | ||
Self-managed distributed deployment | ||
=================================== | ||
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You can use different hosts for the various FEDn services. These instructions shows how to set up FEDn on a **local network** using a single workstation or laptop as | ||
the host for the servier-side components, and other hosts or devices as clients. | ||
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.. note:: | ||
For a secure and production-grade deployment solution over **public networks**, explore the FEDn Studio service at | ||
**fedn.scaleoutsystems.com**. | ||
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Alternatively follow this tutorial substituting the hosts local IP with your public IP, open the neccesary | ||
ports (see which ports are used in docker-compose.yaml), and ensure you have taken additional neccesary security | ||
precautions. | ||
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**Prerequisites** | ||
- `One host workstation and atleast one client device` | ||
- `Python 3.8, 3.9, 3.10 or 3.11 <https://www.python.org/downloads>`__ | ||
- `Docker <https://docs.docker.com/get-docker>`__ | ||
- `Docker Compose <https://docs.docker.com/compose/install>`__ | ||
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Launch a distributed FEDn Network | ||
--------------------------------- | ||
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Start by noting your host's local IP address, used within your network. Discover it by running ifconfig on UNIX or | ||
ipconfig on Windows, typically listed under inet for Unix and IPv4 for Windows. | ||
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Continue by following the standard procedure to initiate a FEDn network, for example using the provided docker-compose template. | ||
Once the network is active, upload your compute package and seed (for comprehensive details, see the quickstart tutorials). | ||
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.. note:: | ||
This guide covers general local networks where server and client may be on different hosts but able to communicate on their private IPs. | ||
A common scenario is also to run fedn and the clients on **localhost** on a single machine. In that case, you can replace <host local ip> | ||
by "127.0.0.1" below. | ||
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Configuring and Attaching Clients | ||
--------------------------------- | ||
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On your client device, continue with initializing your client. To connect to the host machine we need to ensure we are | ||
routing the correct DNS to our hosts local IP address. We can do this using the standard FEDn `client.yaml`: | ||
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.. code-block:: | ||
network_id: fedn-network | ||
discover_host: api-server | ||
discover_port: 8092 | ||
We can then run a client using docker by adding the hostname:ip mapping in the docker run command: | ||
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.. code-block:: | ||
docker run \ | ||
-v $PWD/client.yaml:<client.yaml file location> \ | ||
<potentiel data pointers> | ||
—add-host=api-server:<host local ip> \ | ||
—add-host=combiner:<host local ip> \ | ||
<image name> run client -in client.yaml --name client1 | ||
Alternatively updating the `/etc/hosts` file, appending the following lines for running naitively: | ||
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.. code-block:: | ||
<host local ip> api-server | ||
<host local ip> combiner | ||
Start a training session | ||
------------------------ | ||
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After connecting with your clients, you are ready to start training sessions from the host machine. |
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