SBA_Docker_Kubernetes

Dockerfile

@@ -0,0 +1,5 @@
+FROM python:3.7
+COPY . .
+RUN pip install --no-cache-dir -r requirements.txt
+EXPOSE 5000
+CMD ["python","web.py"]

README.md

@@ -1,70 +1,22 @@
-# SBA Kubernetes Cluster
-* **Objective** - Create a CI/CD Pipeline that builds an image from github and deploys it to a kubernetes cluster
-* **Purpose** - To demonstrate container orchestration skillset
-
-
-
-##  Software Used in This Project
-*  Git CLI
-*  Docker
-*  minikube
-*  kubectl
-*  Python
- * Flask
- * Jenkins
-
-## Instructions
-* Fork and clone this project locally.
-* Create a respective `requirements.txt` to download any `pip` dependencies for this python project.
-  * Ensure you `push` the newly created file: `requirements.txt`
-* Create a `Dockerfile` to  build the image.  Push it to github
-* Build the image
-* Push image to one of your repos on  [Dockerhub](https://hub.docker.com/).
-* Create a `kubernetes.yml` which will pull the aforementioned Dockerhub image and create 3 running copies of it.
-* Use the `kubernetes.yml` to launch your application.  Push this file to your github repo as well.  If possible have jenkins start the app by this method.
-* Write and run a script to determine the state of your kubernetes cluster including the information about the services, pods, nodes, ip addresses, etc.
-  * upload script to github `kubernetes-cluster-information.sh`
-  * run script and  redirect the output of the `kuberenetes-cluster-information.sh` to `kuberenetes-cluster-information-output`
-  * push the script output to your github repo
-
-
-### How to Download
-
-#### Part 1 - Forking the Project
-* To _fork_ the project, click the `Fork` button located at the top right of the project.
-
-
-#### Part 2 - Navigating to _forked_ Repository
-* Navigate to your github profile to find the _newly forked repository_.
-* Copy the URL of the project to the clipboard.
-
-#### Part 3 - Cloning _forked_ repository
-* Clone the repository from **your account** into the directory where you keep projects e.g. ~/projects
-  * clone the project by executing the following command:
-    * `git clone https://github.com/MYUSERNAME/NAMEOFPROJECT`
-
-## How to run this
-* Upon executing `python web.py`, navigate to `localhost:8080` to view the webpage.
-
-<img src="./VIEWME.gif">
-
-
-## Grading SBA (1100 pts total)
-	Points Breakdown
-
-	* 150		 pushed a requirements.txt file to their repo
-	* 150		 built the new image w/jenkins
-	* 150		 pushed Dockerfile to repo
-	* 150		 Pushed built image to dockerhub
-	* 150		 deployed image to k8s cluster
-	* 150	 	 screenshot showing their browser with the spinning flasks
-	* 150		 script+output to show k8s cluster status, 400 points if output shows correct functioning(e.g. pods, nodes, deployments, etc... of app) output+script pushed to github
-	* 50		 submitted pull request with all their changes
-
-
-## How to Submit
-
-#### Submitting assignment
-* from the browser, navigate to the _forked_ project from **your** github account.
-* click the `Pull Requests` tab.
-* select `New Pull Request`
+# Components
+* Git CLI
+  * Used to commit and push code to remote code repository 
+* Docker
+  * Used to create image of the code build
+* DockerHub 
+  * Used to store docker image that is built   
+* minikube
+  * Used to spawn kubernetes nodes 
+* Python - Flask
+  * Used to run the web application
+* Jenkins
+  * Used to create continuous integration and delivery build pipeline. This runs the docker commands to build the image and upload to DockerHub
+* Terraform
+  * Used to deploy kubernetes cluster onto the cloud (ex. AWS)
+
+# Monitoring
+* Monitoring is done using the ELK stack and Metricbeat:
+  * Metricbeat - collects monitoring metrics such as CPU/Memory/Disk usage and feeds data to Logstash
+  * Elasticsearch - used to index log data and make it queryable
+  * Logstash - used for collect log data, enrich it, and send it to Elasticsearch. Sends email alerts if thresholds are breached for CPU usage
+  * Kibana - used to visualize log data and provide a front end graphical user interface for the user to search through logs

requirements.txt

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+Flask==0.12

steps.txt

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+docker build -t web .
+docker run --name mycontainer -p 5000:5000 -d web

web.py

@@ -6,4 +6,4 @@ def main():
     return render_template('index.html')
 
 if __name__ == "__main__":
-    app.run(host="localhost", port=8080, debug=True)
+    app.run(host='0.0.0.0')