/ECE422-Proj2-StartKit

Primary LanguagePython

ECE 422 Project

Members: Owen Stadlwieser and Martin Rudolf

Below is the original README from the fork that we based our project on.

Steps:

Note the first 7 steps can be performed by bash.sh in autoscaler directory Download the code submission on to your swarm manager Cd autoscaler sudo docker stack rm app_name sleep 5 sudo docker build -t auto:1 . cd ../ sudo docker stack deploy --compose-file docker-compose.yml app_name

User Guide:

Prerequisites: Wait for deployment to complete To send request to workers:

  1. Send requests to “http://” + SWARM_MASTER_IP + “:8000/” To generate number of workers plot: Get id of container using docker container ls docker cp CONTAINER_ID:/code/replicas.png ./code.png

ECE 422: Reliable and Secure Systems Design

This repository provides the starter kit for the Reliability project. The docker-images folder contains the Dockerfile, a simple application in Python and a requirement file including dependencies for the application. This directory is for your information and reference as the image (simpleweb) has already been built and pushed to Docker Hub repository.

The following steps show how you can prepare the deployment environment on Cybera Cloud; briefly, you need to a) provision Virtual Machines (VMs) on Cybera b) install Docker on VMs c) create a Swarm cluster of at least two of VMs and d) deploy a web application on the Swarm cluster as microservices.

Also, this repository contains a base implementation of an HTTP client program that may be customized or extended according to your needs.

Initial steps for accomplishing your project:

  1. Create 3 VMs on Cybera cloud with the following specifications:

    1. Use `Ubuntu 18.04` or `Ubuntu 20.04` as the image for all VMs.

2. You need one of these VMs to run the client program for which you may use `m1.small` flavor. Let's call this VM as

    the Client_VM.

    3. For the other two VMs, please still consider `m1.small` flavor. These two VMs will construct your Swarm cluster.

4. You need to open the following TCP ports in the `default security group` in Cybera:
    - 22 (ssh), 2376 and 2377 (Swarm), 5000 (Visualization), 8000 (webapp), 6379 (Redis)
    - You can do this on Cybera by going to `Network` menu and `Security Groups`. ([See Here](./figures/sg.png))

  2. On the Client_VM run

    $ sudo apt -y install python-pip
$ pip install requests

  3. Then, you need to install Docker on VMs that constitute your Swarm Cluster. Run the following on each node.

    $ sudo apt update
$ sudo apt -y install docker.io

  4. Now that Docker is installed on the two VMs, you will create the Swarm cluster.

    1. For the VM that you want to be your Swarm Manger run:
    $ sudo docker swarm init
    1. The above init command will produce something like the bellow command that you need to run on all worker nodes.
    $ docker swarm join \
    --token xxxxxxxxxxxxxxxxxx \
    swarm_manager_ip:2377
    1. Above command attaches your worker to the Swarm cluster.

  5. On your Swarm manager, download the docker-compose.yml file:

    $ wget https://raw.githubusercontent.com/zhijiewang22/ECE422-Proj2-StartKit/master/docker-compose.yml

  6. Run the following to deploy your application:

    $ sudo docker stack deploy --compose-file docker-compose.yml app_name

  7. Your deployed application should include three microservices:

    1. A visualization microservice that is used to visualize the Swarm cluster nodes and the running microservices. - Open http://swarm_manager_ip:5000 in your browser. Note that you should have the Cybera VPN client running in order to see the page. (Sample)
    2. A web application that is linked to a Redis datastore. This simple application shows the number that it has been visited and the period that took it to solve a hard problem. - Open http://swarm_manager_ip:8000 to see the web application. Try to refresh the page. You should see the hitting number increase one by one and also the computation time change each time. (Sample)
    3. A Redis microservice which in fact doesn't do anything fancy but return the number of hitting.

  8. Now, login into your Client_VM and download the http client program:

    $ wget https://raw.githubusercontent.com/zhijiewang22/ECE422-Proj2-StartKit/master/http_client.py

  9. Then run the http_client.py program with one user who sends a request, waits for response, when received the response would think for one second, and then send another request. This cycle goes on as long as the client program is running.

    $ python3.5 http_client.py swarm_manager_ip 1 1
    1. The program should print the response time for each request.
    2. Generally, this client program creates a number of users that send requests to the server and after receiving the response thinks for the amount of think_time and then sends a new request.
    3. If you increase the number of users or decrease the think time, ie increasing the workload, the response time should increase.
    4. Important Note: for development and testing purposes you may run the client program on your laptop which is a reasonable strategy. However, running the client program for a long time on your laptop might appear as a DoS attack to Cybera firewall which may result in unexpected outcomes for your VMs. Therefore, try to run the http client program on the Client_VM.

Good Luck!