From 232d96dee836ee9aa39ec9af447e71310b5fbed2 Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Sun, 17 Mar 2024 09:45:00 +0100 Subject: [PATCH 01/16] Update README.rst Updates the main readme with information on how to get started with FEDn Studio. --- README.rst | 38 +++++++++++++++----------------------- 1 file changed, 15 insertions(+), 23 deletions(-) diff --git a/README.rst b/README.rst index 1e3c42cb6..a77d53237 100644 --- a/README.rst +++ b/README.rst @@ -10,56 +10,48 @@ .. image:: https://readthedocs.org/projects/fedn/badge/?version=latest&style=flat :target: https://fedn.readthedocs.io -FEDn is a modular and model agnostic framework for -federated machine learning. FEDn is designed to scale from pseudo-distributed +FEDn is a highly scalable and resilient framework for +federated machine learning. It allows developers, researchers and data scientists to build federated learning systems that scale from local proof-of-concepts to real-world distributed deployments without code change. FEDn is designed to scale from pseudo-distributed development on your laptop to real-world production setups in geographically distributed environments. Core Features ============= -- **Scalable and resilient.** FEDn is scalable and resilient via a tiered - architecture where multiple aggregation servers (combiners) divide up the work to coordinate clients and aggregate models. - Benchmarks show high performance both for thousands of clients in a cross-device - setting and for large model updates in a cross-silo setting. - FEDn has the ability to recover from failure in all critical components. +- **Scalable and resilient.** FEDn enables multiple aggregation servers (combiners) to divide up the work to coordinate clients and aggregate models. This makes the framework able to scale to large numbers of clients in a cross-device setting, as well as handle large model updates in a cross-silo setting. + The server-side is able to seamlessly recover from failure, making for robust deployment in production scenarios. -- **Security**. FEDn is built using secure industry standard communication protocols (gRPC). A key feature is that - clients do not have to expose any ingress ports. +- **Security**. FL clients do not have to open any ingress ports. The framework is built using secure industry standard communication protocols and + supports token-based authentication for FL clients. -- **Track events and training progress in real-time**. FEDn tracks events for clients and aggregation servers, logging to MongoDB. This - helps developers monitor traning progress in real-time, and to troubleshoot the distributed computation. +- **Track events and training progress in real-time**. Extensive event logging and distributed tracing helps developers monitor experiments in real-time, facilitating troubleshooting and auditing. Tracking and model validation data can easily be retrieved using the API enabling development of custom dashboards and visualizations. -- **Flexible handling of asynchronous clients**. FEDn supports flexible experimentation - with clients coming in and dropping out during training sessions. Extend aggregators to experiment - with different strategies to handle so called stragglers. +- **Robust in asynchronous federated learning scenarios**. FEDn handles clients that connects and disconnects during training. -- **ML-framework agnostic**. Model updates are treated as black-box - computations. This means that it is possible to support any - ML model type or framework. Support for Keras and PyTorch is +- **Deploy your FL project on FEDn Studio for real-world scenarios**. Users can develop their FL use-case in a local development environment and then deploy it to production on FEDn Studio. FEDn Studio + provides the FEDn server-side as a managed service. A web application provides an intuitive UI for orchestrating runs, visualizing and downloading results, and manage FL client tokens. + +- **ML-framework agnostic**. FEDn is compatible with all major ML frameworks. Examples for Keras, PyTorch and scikit-learn are available out-of-the-box. Getting started =============== -The best way to get started is to take the quickstart tutorial: +The best way to get started with the FEDn SDK is to take the quickstart tutorial: - `Quickstart PyTorch `__ Documentation ============= -You will find more details about the architecture, compute package and how to deploy FEDn fully distributed in the documentation: +You find more details about the architecture, deployment and how to develop your own application in the documentation: - `Documentation `__ -- `Paper `__ FEDn Studio =============== -Scaleout also develops FEDn Studio, a web application that extends the FEDn SDK with a UI, production-grade deployment of the FEDn server side on Kubernetes, user authentication/authorization, client identity/API-token management, and project-based multitenancy for segmenting work and resources into collaboration workspaces. FEDn Studio is available as a fully managed service. -There is also additional tooling and charts for self-managed deployment on Kubernetes including integration with several projects from the cloud native landscape. -See `FEDn Framework `__ for more information. +You can deploy your FEDn projects to FEDn Studio. Studio provides a managed and production-grade deployment of the FEDn server-side on Kubernetes. With Studio you manage token-based authentication for clients, and are able to collaborate with other users in joint project workspaces. In addition to a REST API, Studio has an intuitive Dashboard that let's you manage FL exepriments and visualize and download logs and metrics. Follow this guide to `Deploy you project to FEDn Studio `__ . Making contributions From e5ecbfd992887cabf7f902de993b66b5304c7492 Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Sun, 17 Mar 2024 09:48:06 +0100 Subject: [PATCH 02/16] Update README.rst --- README.rst | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/README.rst b/README.rst index a77d53237..26febe159 100644 --- a/README.rst +++ b/README.rst @@ -11,8 +11,7 @@ :target: https://fedn.readthedocs.io FEDn is a highly scalable and resilient framework for -federated machine learning. It allows developers, researchers and data scientists to build federated learning systems that scale from local proof-of-concepts to real-world distributed deployments without code change. FEDn is designed to scale from pseudo-distributed -development on your laptop to real-world production setups in geographically distributed environments. +federated machine learning. It let's developers, researchers and data scientists build federated learning applications that scale from local proof-of-concepts to real-world distributed deployments without code change. Core Features ============= From 07a1498034989f45ea810fd88100558537bdd42d Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Sun, 17 Mar 2024 09:51:20 +0100 Subject: [PATCH 03/16] Update README.rst --- README.rst | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/README.rst b/README.rst index 26febe159..840f2c4fc 100644 --- a/README.rst +++ b/README.rst @@ -16,8 +16,9 @@ federated machine learning. It let's developers, researchers and data scientists Core Features ============= -- **Scalable and resilient.** FEDn enables multiple aggregation servers (combiners) to divide up the work to coordinate clients and aggregate models. This makes the framework able to scale to large numbers of clients in a cross-device setting, as well as handle large model updates in a cross-silo setting. - The server-side is able to seamlessly recover from failure, making for robust deployment in production scenarios. +- **Scalable and resilient.** FEDn enables multiple aggregation servers (combiners) to divide up the work to coordinate clients and aggregate models. This makes the framework able to scale to large numbers of clients. + The server-side is able to seamlessly recover from failure, making for robust deployment in production scenarios. FEDn is robust in asynchronous federated learning scenarios, seamlessly handling clients that connects + and drops out during training. - **Security**. FL clients do not have to open any ingress ports. The framework is built using secure industry standard communication protocols and supports token-based authentication for FL clients. @@ -27,12 +28,13 @@ Core Features - **Robust in asynchronous federated learning scenarios**. FEDn handles clients that connects and disconnects during training. -- **Deploy your FL project on FEDn Studio for real-world scenarios**. Users can develop their FL use-case in a local development environment and then deploy it to production on FEDn Studio. FEDn Studio - provides the FEDn server-side as a managed service. A web application provides an intuitive UI for orchestrating runs, visualizing and downloading results, and manage FL client tokens. - - **ML-framework agnostic**. FEDn is compatible with all major ML frameworks. Examples for Keras, PyTorch and scikit-learn are available out-of-the-box. +- **Deploy your FL project to production on FEDn Studio**. Users can develop their FL use-case in a local development environment and then deploy it to production on FEDn Studio. FEDn Studio + provides the FEDn server-side as a managed service. A web application provides an intuitive UI for orchestrating runs, visualizing and downloading results, and manage FL client tokens. + + Getting started =============== From b1d59f31136200376e7afbec72c83eb4b406495b Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Sun, 17 Mar 2024 09:51:33 +0100 Subject: [PATCH 04/16] Update README.rst --- README.rst | 2 -- 1 file changed, 2 deletions(-) diff --git a/README.rst b/README.rst index 840f2c4fc..71b501161 100644 --- a/README.rst +++ b/README.rst @@ -26,8 +26,6 @@ Core Features - **Track events and training progress in real-time**. Extensive event logging and distributed tracing helps developers monitor experiments in real-time, facilitating troubleshooting and auditing. Tracking and model validation data can easily be retrieved using the API enabling development of custom dashboards and visualizations. -- **Robust in asynchronous federated learning scenarios**. FEDn handles clients that connects and disconnects during training. - - **ML-framework agnostic**. FEDn is compatible with all major ML frameworks. Examples for Keras, PyTorch and scikit-learn are available out-of-the-box. From 7d753169e1aaff367e2e046e0edf8701cc26fbf1 Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Sun, 17 Mar 2024 09:52:38 +0100 Subject: [PATCH 05/16] Update README.rst --- README.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.rst b/README.rst index 71b501161..1edeb2edf 100644 --- a/README.rst +++ b/README.rst @@ -50,7 +50,7 @@ You find more details about the architecture, deployment and how to develop your FEDn Studio =============== -You can deploy your FEDn projects to FEDn Studio. Studio provides a managed and production-grade deployment of the FEDn server-side on Kubernetes. With Studio you manage token-based authentication for clients, and are able to collaborate with other users in joint project workspaces. In addition to a REST API, Studio has an intuitive Dashboard that let's you manage FL exepriments and visualize and download logs and metrics. Follow this guide to `Deploy you project to FEDn Studio `__ . +You can deploy your FEDn projects to FEDn Studio. Studio provides a managed, production-grade deployment of the FEDn server-side. With Studio you manage token-based authentication for clients, and are able to collaborate with other users in joint project workspaces. In addition to a REST API, Studio has an intuitive Dashboard that let's you manage FL exepriments and visualize and download logs and metrics. Follow this guide to `Deploy you project to FEDn Studio `__ . Making contributions From ece4ec460c4a0c5df1b0c826f6e3d9238b81654a Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Sun, 17 Mar 2024 11:38:46 +0100 Subject: [PATCH 06/16] Update README.rst --- README.rst | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/README.rst b/README.rst index 1edeb2edf..0bbac819a 100644 --- a/README.rst +++ b/README.rst @@ -10,8 +10,7 @@ .. image:: https://readthedocs.org/projects/fedn/badge/?version=latest&style=flat :target: https://fedn.readthedocs.io -FEDn is a highly scalable and resilient framework for -federated machine learning. It let's developers, researchers and data scientists build federated learning applications that scale from local proof-of-concepts to real-world distributed deployments without code change. +FEDn enables developers, researchers and data scientists to build federated learning applications that scale from local proof-of-concepts to real-world distributed deployments without code change. Core Features ============= From 6d7c31c3e499deef5df0e78f72bd7e6178257d39 Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Sun, 17 Mar 2024 11:47:32 +0100 Subject: [PATCH 07/16] Update README.rst --- README.rst | 24 +++++++++++------------- 1 file changed, 11 insertions(+), 13 deletions(-) diff --git a/README.rst b/README.rst index 0bbac819a..47e98883d 100644 --- a/README.rst +++ b/README.rst @@ -15,25 +15,25 @@ FEDn enables developers, researchers and data scientists to build federated lear Core Features ============= -- **Scalable and resilient.** FEDn enables multiple aggregation servers (combiners) to divide up the work to coordinate clients and aggregate models. This makes the framework able to scale to large numbers of clients. - The server-side is able to seamlessly recover from failure, making for robust deployment in production scenarios. FEDn is robust in asynchronous federated learning scenarios, seamlessly handling clients that connects - and drops out during training. +- **Scalable and resilient.** FEDn enables multiple aggregation servers to share the work to coordinate clients and aggregate models. This makes the framework scalable to large numbers of clients. + The system is able to seamlessly recover from failure, enabling robust deployment in production. FEDn also handles asynchronous federated learning scenarios, where clients connect + and drop out during training. -- **Security**. FL clients do not have to open any ingress ports. The framework is built using secure industry standard communication protocols and +- **Security**. FL clients do not have to open any ingress ports, enabling real-world deployments in a wide range of settigs. Further, FEDn is implemented using secure industry standard communication protocols and supports token-based authentication for FL clients. - **Track events and training progress in real-time**. Extensive event logging and distributed tracing helps developers monitor experiments in real-time, facilitating troubleshooting and auditing. - Tracking and model validation data can easily be retrieved using the API enabling development of custom dashboards and visualizations. + Machine learning validation metrics from clients can be retrieved using the API, enabling flexible analysis of federated experiments. - **ML-framework agnostic**. FEDn is compatible with all major ML frameworks. Examples for Keras, PyTorch and scikit-learn are available out-of-the-box. -- **Deploy your FL project to production on FEDn Studio**. Users can develop their FL use-case in a local development environment and then deploy it to production on FEDn Studio. FEDn Studio - provides the FEDn server-side as a managed service. A web application provides an intuitive UI for orchestrating runs, visualizing and downloading results, and manage FL client tokens. +- **Deploy your FL project to production on FEDn Studio**. Users can develop a FL use-case in a local development environment, and then deploy it to production on FEDn Studio. FEDn Studio + provides the FEDn server-side as a managed service on Kubernetes. A web application provides an intuitive UI for orchestrating runs, visualizing and downloading results, and manage FL client tokens. -Getting started +Getting started with the SDK =============== The best way to get started with the FEDn SDK is to take the quickstart tutorial: @@ -47,17 +47,15 @@ You find more details about the architecture, deployment and how to develop your - `Documentation `__ -FEDn Studio +Deploying a project to FEDn Studio =============== -You can deploy your FEDn projects to FEDn Studio. Studio provides a managed, production-grade deployment of the FEDn server-side. With Studio you manage token-based authentication for clients, and are able to collaborate with other users in joint project workspaces. In addition to a REST API, Studio has an intuitive Dashboard that let's you manage FL exepriments and visualize and download logs and metrics. Follow this guide to `Deploy you project to FEDn Studio `__ . +Studio provides a managed, production-grade deployment of the FEDn server-side. With Studio you manage token-based authentication for clients, and are able to collaborate with other users in joint project workspaces. In addition to a REST API, Studio has an intuitive Dashboard that let's you manage FL experiments and visualize and download logs and metrics. Follow this guide to `Deploy you project to FEDn Studio `__ . Making contributions ==================== -All pull requests will be considered and are much appreciated. Reach out -to one of the maintainers if you are interested in making contributions, -and we will help you find a good first issue to get you started. For +All pull requests will be considered and are much appreciated. For more details please refer to our `contribution guidelines `__. From 200197314b3c475670bbb937d2ab6294848df159 Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Mon, 18 Mar 2024 08:24:28 +0100 Subject: [PATCH 08/16] Update README.rst --- README.rst | 13 ++++++++++--- 1 file changed, 10 insertions(+), 3 deletions(-) diff --git a/README.rst b/README.rst index 47e98883d..164ead7d0 100644 --- a/README.rst +++ b/README.rst @@ -10,7 +10,8 @@ .. image:: https://readthedocs.org/projects/fedn/badge/?version=latest&style=flat :target: https://fedn.readthedocs.io -FEDn enables developers, researchers and data scientists to build federated learning applications that scale from local proof-of-concepts to real-world distributed deployments without code change. +FEDn enables developers, researchers and data scientists to build federated learning applications that scale from local proof-of-concepts to real-world distributed deployments. +Develop your FML use-case in a pseudo-local environment and then deploy to FEDn Studio for real-world FL without any code change. Core Features ============= @@ -28,10 +29,16 @@ Core Features - **ML-framework agnostic**. FEDn is compatible with all major ML frameworks. Examples for Keras, PyTorch and scikit-learn are available out-of-the-box. -- **Deploy your FL project to production on FEDn Studio**. Users can develop a FL use-case in a local development environment, and then deploy it to production on FEDn Studio. FEDn Studio - provides the FEDn server-side as a managed service on Kubernetes. A web application provides an intuitive UI for orchestrating runs, visualizing and downloading results, and manage FL client tokens. +**From development to real-world FL** +Users can develop a FL use-case in a local development environment, and then deploy it to FEDn Studio: +- The FEDn server-side as a managed, production-grade service on Kubernetes. +- Token-based authentication for FL clients +- Role-based access control (RBAC) +- Dashboard for orchestrating runs, visualizing and downloading results +- Admin dashboard for managing and scaling the FEDn network +- Collaborate with other data-scientists in a shared workspace. Getting started with the SDK =============== From efeb82a8ac2d28cde84c5d802b58360af79aaee3 Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Mon, 18 Mar 2024 08:39:39 +0100 Subject: [PATCH 09/16] Update README.rst --- README.rst | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/README.rst b/README.rst index 164ead7d0..1413e69c9 100644 --- a/README.rst +++ b/README.rst @@ -29,10 +29,9 @@ Core Features - **ML-framework agnostic**. FEDn is compatible with all major ML frameworks. Examples for Keras, PyTorch and scikit-learn are available out-of-the-box. -**From development to real-world FL** - -Users can develop a FL use-case in a local development environment, and then deploy it to FEDn Studio: +From development to real-world FL: +- Develop a FEDn project in a local development environment, and then deploy it to FEDn Studio - The FEDn server-side as a managed, production-grade service on Kubernetes. - Token-based authentication for FL clients - Role-based access control (RBAC) @@ -40,6 +39,8 @@ Users can develop a FL use-case in a local development environment, and then dep - Admin dashboard for managing and scaling the FEDn network - Collaborate with other data-scientists in a shared workspace. + + Getting started with the SDK =============== From b336fb2f5da79f920388a9195f283195909c9d5c Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Mon, 18 Mar 2024 08:43:35 +0100 Subject: [PATCH 10/16] Update README.rst --- README.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/README.rst b/README.rst index 1413e69c9..415f204df 100644 --- a/README.rst +++ b/README.rst @@ -35,6 +35,7 @@ From development to real-world FL: - The FEDn server-side as a managed, production-grade service on Kubernetes. - Token-based authentication for FL clients - Role-based access control (RBAC) +- REST API - Dashboard for orchestrating runs, visualizing and downloading results - Admin dashboard for managing and scaling the FEDn network - Collaborate with other data-scientists in a shared workspace. From 7933cf458508a5a86cd380cedaf493e34955c0d3 Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Mon, 18 Mar 2024 08:48:34 +0100 Subject: [PATCH 11/16] Update README.rst --- README.rst | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/README.rst b/README.rst index 415f204df..dd34ac373 100644 --- a/README.rst +++ b/README.rst @@ -10,8 +10,7 @@ .. image:: https://readthedocs.org/projects/fedn/badge/?version=latest&style=flat :target: https://fedn.readthedocs.io -FEDn enables developers, researchers and data scientists to build federated learning applications that scale from local proof-of-concepts to real-world distributed deployments. -Develop your FML use-case in a pseudo-local environment and then deploy to FEDn Studio for real-world FL without any code change. +FEDn empowers developers, researchers, and data scientists to create federated learning applications that seamlessly transition from local proofs-of-concept to real-world distributed deployments. Develop your Federated Machine Learning (FML) use case in a pseudo-local environment, then deploy it to FEDn Studio for real-world Federated Learning (FL) without any need for code changes. Core Features ============= From 1847d7fefbf7da28c80d7f6f68f4a3c84e0b1886 Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Mon, 18 Mar 2024 08:51:42 +0100 Subject: [PATCH 12/16] Update README.rst --- README.rst | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/README.rst b/README.rst index dd34ac373..3c6f2b626 100644 --- a/README.rst +++ b/README.rst @@ -15,15 +15,11 @@ FEDn empowers developers, researchers, and data scientists to create federated l Core Features ============= -- **Scalable and resilient.** FEDn enables multiple aggregation servers to share the work to coordinate clients and aggregate models. This makes the framework scalable to large numbers of clients. - The system is able to seamlessly recover from failure, enabling robust deployment in production. FEDn also handles asynchronous federated learning scenarios, where clients connect - and drop out during training. +- **Scalable and resilient.** FEDn facilitates the coordination of clients and model aggregation through multiple aggregation servers sharing the workload. This design makes the framework highly scalable, accommodating large numbers of clients. The system is engineered to seamlessly recover from failures, ensuring robust deployment in production environments. Furthermore, FEDn adeptly manages asynchronous federated learning scenarios, accommodating clients that may connect or drop out during training. -- **Security**. FL clients do not have to open any ingress ports, enabling real-world deployments in a wide range of settigs. Further, FEDn is implemented using secure industry standard communication protocols and - supports token-based authentication for FL clients. +- **Security**. FL clients do not need to open any ingress ports, facilitating real-world deployments across a wide variety of settings. Additionally, FEDn utilizes secure, industry-standard communication protocols and supports token-based authentication for FL clients, enhancing security and ease of integration in diverse environments. -- **Track events and training progress in real-time**. Extensive event logging and distributed tracing helps developers monitor experiments in real-time, facilitating troubleshooting and auditing. - Machine learning validation metrics from clients can be retrieved using the API, enabling flexible analysis of federated experiments. +- **Track events and training progress in real-time**. Extensive event logging and distributed tracing enable developers to monitor experiments in real-time, simplifying troubleshooting and auditing processes. Machine learning validation metrics from clients can be accessed via the API, allowing for flexible analysis of federated experiments. - **ML-framework agnostic**. FEDn is compatible with all major ML frameworks. Examples for Keras, PyTorch and scikit-learn are available out-of-the-box. @@ -57,7 +53,10 @@ You find more details about the architecture, deployment and how to develop your Deploying a project to FEDn Studio =============== -Studio provides a managed, production-grade deployment of the FEDn server-side. With Studio you manage token-based authentication for clients, and are able to collaborate with other users in joint project workspaces. In addition to a REST API, Studio has an intuitive Dashboard that let's you manage FL experiments and visualize and download logs and metrics. Follow this guide to `Deploy you project to FEDn Studio `__ . + +Studio offers a managed, production-grade deployment of the FEDn server-side infrastructure. With Studio, you can manage token-based authentication for clients and collaborate with other users in joint project workspaces. In addition to a REST API, Studio features an intuitive dashboard that allows you to manage FL experiments and visualize and download logs and metrics, enhancing your ability to monitor and analyze federated learning projects. + +Follow this guide to `Deploy you project to FEDn Studio `__ . Making contributions From 9a786b95f75c6dd08ac600095e20e05becbfc1aa Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Mon, 18 Mar 2024 09:00:56 +0100 Subject: [PATCH 13/16] Update README.rst --- README.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/README.rst b/README.rst index 3c6f2b626..0fb603796 100644 --- a/README.rst +++ b/README.rst @@ -34,6 +34,7 @@ From development to real-world FL: - Dashboard for orchestrating runs, visualizing and downloading results - Admin dashboard for managing and scaling the FEDn network - Collaborate with other data-scientists in a shared workspace. +- Cloud or on-premise deployment From 0d7ce1e3fdee94aaade990fb4c6faaad645df783 Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Tue, 19 Mar 2024 22:05:11 +0100 Subject: [PATCH 14/16] Update README.rst --- README.rst | 30 ++++++++++++++++++------------ 1 file changed, 18 insertions(+), 12 deletions(-) diff --git a/README.rst b/README.rst index 0fb603796..0711bb1bc 100644 --- a/README.rst +++ b/README.rst @@ -38,16 +38,17 @@ From development to real-world FL: -Getting started with the SDK +Getting started with FEDn =============== -The best way to get started with the FEDn SDK is to take the quickstart tutorial: +The best way to get started is to take the quickstart tutorial: -- `Quickstart PyTorch `__ +- `Quickstart `__ Documentation ============= -You find more details about the architecture, deployment and how to develop your own application in the documentation: + +More details about the architecture, deployment, and how to develop your own application and framework extensions (such as custom aggregators) are found in the documentation: - `Documentation `__ @@ -55,11 +56,22 @@ You find more details about the architecture, deployment and how to develop your Deploying a project to FEDn Studio =============== -Studio offers a managed, production-grade deployment of the FEDn server-side infrastructure. With Studio, you can manage token-based authentication for clients and collaborate with other users in joint project workspaces. In addition to a REST API, Studio features an intuitive dashboard that allows you to manage FL experiments and visualize and download logs and metrics, enhancing your ability to monitor and analyze federated learning projects. +Studio offers a production-grade deployment of the FEDn server-side infrastructure on Kubernetes. With Studio, you can also manage token-based authentication for clients and collaborate with other users in joint project workspaces. In addition to a REST API, Studio features intuitive dashboards that allows you to orchestrate FL experiments and visualize and manage global models, event logs and metrics. These features enhance your ability to monitor and analyze federated learning projects. Studio is available as-a service hosted by Scaleout and one project is provided for free for testing and research. + +- `Register for a project in Studio `__ +- `Deploy you project to FEDn Studio `__ -Follow this guide to `Deploy you project to FEDn Studio `__ . +Options and charts are also available for self-managed deployment of FEDn Studio, reach out to the Scaleout team for more information. +Support +================= + +Community support in available in our `Discord +server `__. + +Options are also available for `Enterprise support `__. + Making contributions ==================== @@ -67,12 +79,6 @@ All pull requests will be considered and are much appreciated. For more details please refer to our `contribution guidelines `__. -Community support -================= - -Community support in available in our `Discord -server `__. - Citation ======== From ebaa28525ee2101aec5c484f64c7c746e4cc5eef Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Tue, 19 Mar 2024 22:10:47 +0100 Subject: [PATCH 15/16] Update README.rst --- README.rst | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.rst b/README.rst index 0711bb1bc..6922b9487 100644 --- a/README.rst +++ b/README.rst @@ -1,5 +1,3 @@ -.. figure:: https://thumb.tildacdn.com/tild6637-3937-4565-b861-386330386132/-/resize/560x/-/format/webp/FEDn_logo.png - :alt: FEDn logo .. image:: https://github.com/scaleoutsystems/fedn/actions/workflows/integration-tests.yaml/badge.svg :target: https://github.com/scaleoutsystems/fedn/actions/workflows/integration-tests.yaml @@ -10,6 +8,9 @@ .. image:: https://readthedocs.org/projects/fedn/badge/?version=latest&style=flat :target: https://fedn.readthedocs.io +FEDn +-------- + FEDn empowers developers, researchers, and data scientists to create federated learning applications that seamlessly transition from local proofs-of-concept to real-world distributed deployments. Develop your Federated Machine Learning (FML) use case in a pseudo-local environment, then deploy it to FEDn Studio for real-world Federated Learning (FL) without any need for code changes. Core Features @@ -37,7 +38,6 @@ From development to real-world FL: - Cloud or on-premise deployment - Getting started with FEDn =============== From 444203aa5a36cb2e161d782b62b51ce3c1622149 Mon Sep 17 00:00:00 2001 From: Andreas Hellander Date: Tue, 19 Mar 2024 22:23:21 +0100 Subject: [PATCH 16/16] Update README.rst --- README.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.rst b/README.rst index 6922b9487..1076f317b 100644 --- a/README.rst +++ b/README.rst @@ -11,7 +11,7 @@ FEDn -------- -FEDn empowers developers, researchers, and data scientists to create federated learning applications that seamlessly transition from local proofs-of-concept to real-world distributed deployments. Develop your Federated Machine Learning (FML) use case in a pseudo-local environment, then deploy it to FEDn Studio for real-world Federated Learning (FL) without any need for code changes. +FEDn empowers developers, researchers, and data scientists to create federated learning applications that seamlessly transition from local proofs-of-concept to real-world distributed deployments. Develop your federated learning use case in a pseudo-local environment, and deploy it to FEDn Studio for real-world Federated Learning without any need for code changes. Core Features =============