Feature/SK-658 | Add gRPC healthchecking

Dockerfile

@@ -2,6 +2,8 @@
 ARG BASE_IMG=python:3.10-slim
 FROM $BASE_IMG
 
+ARG GRPC_HEALTH_PROBE_VERSION=""
+
 # Requirements (use MNIST Keras as default)
 ARG REQUIREMENTS=""
 
@@ -15,6 +17,17 @@ COPY $REQUIREMENTS /app/config/requirements.txt
 # Install developer tools (needed for psutil)
 RUN apt-get update && apt-get install -y python3-dev gcc
 
+# Install grpc health probe checker
+RUN if [ ! -z "$GRPC_HEALTH_PROBE_VERSION" ]; then \
+  apt-get install -y wget && \
+  wget -qO/bin/grpc_health_probe https://github.com/grpc-ecosystem/grpc-health-probe/releases/download/${GRPC_HEALTH_PROBE_VERSION}/grpc_health_probe-linux-amd64 && \
+  chmod +x /bin/grpc_health_probe && \
+  apt-get remove -y wget && apt autoremove -y; \
+  else \
+  echo "No grpc_health_probe version specified, skipping installation"; \
+  fi
+
+
 # Create FEDn app directory
 SHELL ["/bin/bash", "-c"]
 RUN mkdir -p /app \

docker-compose.yaml

@@ -91,6 +91,7 @@ services:
       context: .
       args:
         BASE_IMG: ${BASE_IMG:-python:3.10-slim}
+        GRPC_HEALTH_PROBE_VERSION: v0.4.24
     working_dir: /app
     volumes:
       - ${HOST_REPO_DIR:-.}/fedn:/app/fedn
@@ -99,6 +100,16 @@ services:
       - "/venv/bin/pip install --no-cache-dir -e /app/fedn && /venv/bin/fedn run combiner --init config/settings-combiner.yaml"
     ports:
       - 12080:12080
+    healthcheck:
+      test:
+        [
+          "CMD",
+          "/bin/grpc_health_probe",
+          "-addr=localhost:12080"
+        ]
+      interval: 2s
+      timeout: 10s
+      retries: 5
     depends_on:
       - api-server
 
@@ -119,5 +130,5 @@ services:
     deploy:
       replicas: 0
     depends_on:
-      - api-server
-      - combiner
+      combiner:
+        condition: service_healthy

docs/quickstart.rst

@@ -1,6 +1,11 @@
 Quickstart Tutorial PyTorch (MNIST)
 ===================================
 
+.. note::
+   This tutorial is a quickstart guide to FEDn where the federated learning project has been defined
+   using an already implemented ``compute package``. This turorial is a good starting point for developers, however,
+   head over to :ref:`tutorial-label` when you are ready to define your own federated learning projects.
+
 This classic example of hand-written text recognition is well suited as a lightweight test when developing on FEDn in pseudo-distributed mode. 
 A normal high-end laptop or a workstation should be able to sustain a few clients. 
 The example automates the partitioning of data and deployment of a variable number of clients on a single host. 

examples/mnist-pytorch/API_Example.ipynb

@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "743dfe47",
    "metadata": {},
    "outputs": [],
@@ -38,7 +38,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "1061722d",
    "metadata": {},
    "outputs": [],
@@ -58,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "5107f6f9",
    "metadata": {},
    "outputs": [],
@@ -78,7 +78,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "f0380d35",
    "metadata": {},
    "outputs": [],
@@ -90,7 +90,7 @@
     "                    \"session_id\": session_id,\n",
     "                    \"aggregator\": \"fedavg\",\n",
     "                    \"model_id\": seed_model['model_id'],\n",
-    "                    \"rounds\": 10\n",
+    "                    \"rounds\": 2\n",
     "                 }\n",
     "\n",
     "result_fedavg = client.start_session(**session_config_fedavg)"

fedn/fedn/network/combiner/combiner.py

@@ -398,7 +398,7 @@ def _flush_model_update_queue(self):
 
     #####################################################################################################################
 
-    # Control Service
+    # Controller Service
 
     def Start(self, control: fedn.ControlRequest, context):
         """ Start a round of federated learning"

fedn/fedn/network/grpc/server.py

@@ -1,6 +1,7 @@
 from concurrent import futures
 
 import grpc
+from grpc_health.v1 import health, health_pb2_grpc
 
 import fedn.network.grpc.fedn_pb2_grpc as rpc
 from fedn.common.log_config import (logger, set_log_level_from_string,
@@ -17,6 +18,7 @@ def __init__(self, servicer, modelservicer, config):
 
         self.server = grpc.server(futures.ThreadPoolExecutor(max_workers=350))
         self.certificate = None
+        self.health_servicer = health.HealthServicer()
 
         if isinstance(servicer, rpc.CombinerServicer):
             rpc.add_CombinerServicer_to_server(servicer, self.server)
@@ -29,6 +31,8 @@ def __init__(self, servicer, modelservicer, config):
         if isinstance(servicer, rpc.CombinerServicer):
             rpc.add_ControlServicer_to_server(servicer, self.server)
 
+        health_pb2_grpc.add_HealthServicer_to_server(self.health_servicer, self.server)
+
         if config['secure']:
             logger.info(f'Creating secure gRPCS server using certificate: {config["certificate"]}')
             server_credentials = grpc.ssl_server_credentials(

fedn/setup.py

@@ -2,13 +2,13 @@
 
 setup(
     name='fedn',
-    version='0.7.2',
+    version='0.8.0',
     description="""Scaleout Federated Learning""",
     author='Scaleout Systems AB',
     author_email='[email protected]',
     url='https://www.scaleoutsystems.com',
     py_modules=['fedn'],
-    python_requires='>=3.7,<3.11',
+    python_requires='>=3.8,<3.11',
     install_requires=[
         "PyYAML>=5.4",
         "requests",
@@ -31,7 +31,8 @@
         "plotly",
         "pandas",
         "bokeh<3.0.0",
-        "networkx"
+        "networkx",
+        "grpcio-health-checking"
     ],
     license='Apache 2.0',
     zip_safe=False,
@@ -42,7 +43,6 @@
     packages=find_packages(exclude=["tests", "tests.*"]),
     classifiers=[
         'Natural Language :: English',
-        'Programming Language :: Python :: 3.7',
         'Programming Language :: Python :: 3.8',
         'Programming Language :: Python :: 3.9',
         'Programming Language :: Python :: 3.10',