Rewrite the setup_playbook.yaml

Author: ema-pe

README.md

@@ -117,29 +117,32 @@ To test the inventory, you can try the [example
 playbook](https://docs.ansible.com/ansible/latest/getting_started/get_started_playbook.html)
 on the official Ansible documentation.
 
-Once you have the inventory file, run ansible-playbook:
+**Important:** on the control node you need to have the DFaaS Git repository and
+to build the DFaaS Agent. This can be done with the following:
 
 ```console
-$ ansible-playbook -i inventory.yaml setup_playbook.yaml
+$ git clone https://github.com/unimib-datAI/dfaas.git
+$ sudo apt install golang-go
+$ go build -C dfaas/dfaasagent
 ```
 
-**WIP**
-
-Run the `ansible-playbook` command on the control node to execute the tasks specified in the playbook with the following options:
-
-`-i` : path to an inventory file  
-`--extra-vars` : to specify the Sysbox version and shiftfs branch to be installed  
-`--tags` : to specify steps of the playbook to be executed
+Then you can run the playbook with ansible-playbook (make sure to be on the
+DFaaS directory!):
 
-```shell
-ansible-playbook -i inventory.yaml setup_playbook.yaml --tags "installation, deploy"
+```console
+$ ansible-playbook -i inventory.yaml setup_playbook.yaml
 ```
 
-**WIP**
+This deploys a basic, fully functional DFaaS node using the Node Margin
+Strategy. You can modify the `dfaasagent.env` file to configure the agent and
+replay the playbook to deploy it.
 
-This Ansible playbook installs the required software and executes the [docker-compose.yml](docker-compose.yml), deploying three DFaaS nodes containers, and a fourth container called [operator](operator), which deploys functions on DFaaS nodes and starts specified load tests.
+You can make automatic calls to the node with the **operator**. More information
+about it in the [dedicated directory](operator).
 
-If you have four different VMs it's recommended to deploy the entire system exploiting the playbook and configuration files in [test_environment](test_environment).
+If you have four different VMs it's recommended to deploy the entire system
+exploiting the playbook and configuration files in
+[test_environment](test_environment). This is still a work in progress.
 
 ### Manual deployment
 
@@ -163,7 +166,7 @@ root user.
     # apt install golang-go haproxy python3-pip python3-venv
     ```
 
-3. Clone this repository in the `/opt/dfaas-src` directory:
+3. Clone (or copy) this repository in the `/opt/dfaas-src` directory:
 
     ```console
     # mkdir --parents /opt/

dfaasagent.env

@@ -17,8 +17,8 @@ AGENT_PUBSUB_TOPIC="/dfaasagent/1.0.0"
 
 AGENT_RECALC_PERIOD=1m
 
-AGENT_HAPROXY_TEMPLATE_FILE_NMS="/agent/haproxycfgnms.tmpl"
-AGENT_HAPROXY_TEMPLATE_FILE_RECALC="/agent/haproxycfgrecalc.tmpl"
+AGENT_HAPROXY_TEMPLATE_FILE_NMS="/opt/dfaasagent/haproxycfgnms.tmpl"
+AGENT_HAPROXY_TEMPLATE_FILE_RECALC="/opt/dfaasagent/haproxycfgrecalc.tmpl"
 AGENT_HAPROXY_CONFIG_FILE="/etc/haproxy/haproxy.cfg"
 AGENT_HAPROXY_CONFIG_UPDATE_COMMAND="/usr/bin/systemctl reload haproxy.service"
 AGENT_HAPROXY_HOST=127.0.0.1
@@ -41,7 +41,7 @@ AGENT_FORECASTER_PORT=8000
 
 AGENT_STRATEGY="nodemarginstrategy"
 
-AGENT_GROUP_LIST_FILE_NAME="/agent/group_list.json"
+AGENT_GROUP_LIST_FILE_NAME="/opt/dfaasagent/group_list.json"
 
 AGENT_NODE_TYPE=1 # heavy=0 mid=1 light=2
 

dfaasagent/agent/agent.go

@@ -236,7 +236,8 @@ func Main() {
 	rand.Seed(int64(time.Now().Nanosecond()))
 
 	// Load configuration
-	_config, err := config.LoadConfig("/agent")
+    // FIXME: Do not write an hardcoded directory
+	_config, err := config.LoadConfig("/opt/dfaasagent")
 
 	// Setup logging engine
 	logger, err := logging.Initialize(_config.DateTime, _config.DebugMode, _config.LogColors)

docker/forecaster/model/config_constants.py

@@ -3,8 +3,9 @@
 # This file is licensed under the AGPL v3.0 or later license. See LICENSE and
 # AUTHORS file for more information.
 
-MODELS_BASE_PATH = "forecaster/models/"
-SCALERS_BASE_PATH = "forecaster/scalers/"
+# FIXME: Make the paths configurable.
+MODELS_BASE_PATH = "/opt/forecaster/models/"
+SCALERS_BASE_PATH = "/opt/forecaster/scalers/"
 GROUPS_COLUMNS_NAMES = ["rate_group_HIGH_USAGE", "rate_group_LOW_USAGE", "rate_group_HIGH_USAGE"]
 CPU_USAGE_METRIC = "cpu_usage_node"
 RAM_USAGE_METRIC = "ram_usage_node"