In this organization you will find a microservices application that is a Postojna photo gallery and service.
Image of the application:
-
gallery-service-upload-get-deleting-photos |
-
get-photo-info |
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gallery-authentication |
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gallery-frontend |
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AI-service |
A user first needs to register and then login to the application. After that, they can upload photos to the application and view them. The user can also delete their photos. The application additionally retrieves all photo metadata such as the camera used, location, and other details. One of the standout features is the ability to view these photos on a map, showcasing all the landmarks. Users have the flexibility to edit their profile, including changing their username and password. Moreover, the application integrates AI technology to enhance the colors of the photos, making them visually more appealing.
Here is an example of the scheme of the application.
The current schema of the app:
Old schema of the app not in use anymore
The database we will use here is elephantsql. Just log in to the database and then you can access the database using dbeaver(IMPORTANT NOTE the URL must be in the JDBC URL format so converte the URL this jdbc:postgresql://[HOST]:[PORT]/[DATABASE]). If we will use all of the memory on the database we can migrate the database to fly.io or some other database service.
Link to the elephantsql docs for node and go.
Docker hub links
For the docker configuration we will use the dockerfile. Here is an example of the dockerfile for GO:
FROM golang:1.21.3 as builder
WORKDIR /app
COPY . .
RUN go mod download
RUN CGO_ENABLED=0 GOOS=linux go build -o server .
FROM alpine:latest
RUN apk --no-cache add ca-certificates
COPY --from=builder /app/server /server
EXPOSE 8080
CMD ["/server"]For the docker configuration we will use the dockerfile. Here is an example of the dockerfile for nodeJS:
FROM node:20-alpine
WORKDIR /app
COPY package*.json ./
RUN npm install
COPY . .
ENV PORT=5000
EXPOSE 5000
CMD [ "npm", "start" ]We also need to add the build image to the docker hub. The CI/CD will buld the image and push it to the docker hub. But we need to add the docker hub username and password to the CircleCI environment variables. So hre are the steps to set this up:
- Create a docker hub account here
- Create a repository on the docker hub (give it a name and set it to public)
- Get the docker hub username and password(token)
- Create a CircleCI account here
- Add the project to the CircleCI
- Go to the project settings and then go to the environment variables
- Add the DOCKERHUB_USERNAME and DOCKERHUB_ACCESS_TOKEN variables (Name == DOCKERHUB_USERNAME and Value == docker hub username and Name == DOCKERHUB_ACCESS_TOKEN and Value == docker hub password)
For the CI/CD we will use CircleCI. To configure the CI/CD we need to add the following files to the root of the project add the following files: .circleci/config.yml. You can setup your CircleCI account here or we can use my account.
here is the example of the config.yml file for GO:
# Use the latest 2.1 version of CircleCI pipeline process engine.
# See: https://circleci.com/docs/configuration-reference
version: 2.1
# Define a job to be invoked later in a workflow.
# See: https://circleci.com/docs/configuration-reference/#jobs
jobs:
build:
working_directory: ~/repo
# Specify the execution environment. You can specify an image from Dockerhub or use one of our Convenience Images from CircleCI's Developer Hub.
# See: https://circleci.com/docs/configuration-reference/#docker-machine-macos-windows-executor
docker:
- image: cimg/go:1.21.3
# Add steps to the job
# See: https://circleci.com/docs/configuration-reference/#steps
steps:
- checkout
- setup_remote_docker:
version: 20.10.6
- restore_cache:
keys:
- go-mod-v4-{{ checksum "go.sum" }}
- run:
name: Install Dependencies
command: go mod download
- save_cache:
key: go-mod-v4-{{ checksum "go.sum" }}
paths:
- "/go/pkg/mod"
- run:
name: Run tests
command: |
mkdir -p /tmp/test-reports
gotestsum --junitfile /tmp/test-reports/unit-tests.xml
- store_test_results:
path: /tmp/test-reports
- run:
name: Build Docker Image
command: docker build -t jabok123458/rso_prepih:${CIRCLE_SHA1} .
- run:
name: Push Docker Image
command: |
echo "$DOCKERHUB_ACCESS_TOKEN" | docker login --username $DOCKERHUB_USERNAME --password-stdin
docker push jabok123458/rso_prepih:${CIRCLE_SHA1}
- run:
name: Update Helm Chart
command: |
git clone git@github.com:RSO-project-Prepih/kubernetis-GKE.git
cd kubernetis-GKE/gallery-service
echo "Before sed command:"
cat ./values.yaml
sed -i 's|tag: .*|tag: '${CIRCLE_SHA1}'|' ./values.yaml
echo "After sed command:"
cat ./values.yaml
git config user.name "lovc21"
git config user.email "jakob.dekleva@gmail.com"
git add ./values.yaml
git commit -am "Update image tag to ${CIRCLE_SHA1}" || echo "No changes to commit"
git push origin main
# Invoke jobs via workflows
# See: https://circleci.com/docs/configuration-reference/#workflows
workflows:
sample: # This is the name of the workflow, feel free to change it to better match your workflow.
# Inside the workflow, you define the jobs you want to run.
jobs:
- buildFor the Kubernetes deployment, we will utilize GKE (Google Kubernetes Engine). The application will be deployed using helm, a powerful tool for managing Kubernetes applications. To expose the application to the internet, we will configure ingress, which efficiently manages external access to the services in a cluster.
For monitoring and metrics collection, prometheus will be employed, offering a robust solution for gathering and processing real-time metrics. These metrics will be visualized using grafana, a platform for observability and data visualization.
Lastly, log aggregation and analysis will be handled by loki, a horizontally-scalable, highly-available, multi-tenant log aggregation system.
You can finde the helm chart in this repo here. The helm chart is used to deploy the application to the kubernetis cluster. The helm chart is also used to configure the kubernetis cluster.
ArgoCD is used to deploy the application to the kubernetis cluster. You can find the ArgoCD here.
Here you can see the deployd services on argoCD:
The metrics will be collected using prometheus, grafana and kubernetis cluster. You need to set this up in the code. You will need to expose the metrics endpoint in the code so that prometheus can collect the metrics.
grafana ip http://34.78.218.192/login
Here you can see the grafana dashboard:
prometheus ip http://35.187.39.50:9090/
Here you can see the prometheus dashboard:
