@gapi/starter-serverless
v1.8.23
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Serverless amazon lambda GraphQL
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@Gapi starter Serverless
@Nginx, @Rabbitmq, @Postgres, @Docker, @Graphql
This is basic example serverless project related with GAPI to check advanced example project go to advanced-example
To start developing clone repository
git clone https://github.com/Stradivario/gapi-starter-serverless
Better use command line utility(gapi) to install it type following command:
npm i -g @gapi/cli
Type the following command to create new project from scratch via CLI
gapi new my-project --serverless
To start project for "development" type:
npm start
To deploy to staging or production type:
This will run ParcelJS and will Bundle your lambdas to single file inside dist
folder
example2 src/auth/main.ts
will be bundled inside dist/auth/main.js
with main.map
example: src/user/main.ts
will be bundled inside dist/user/main.js
with main.map
Then the lambdas will be deployed based on your serverless.yml
configuration
staging
npm run deploy:serverless
production
npm run deploy:serverless:prod
To understand how this system works please take a look the following example:
1.We Bootstrap our application with only AppModule
present like that
Filename: main.ts
import { AppModule } from './app/app.module';
import { BootstrapFramework } from '@rxdi/core';
import { FrameworkImports } from './framework-imports';
BootstrapFramework(AppModule, [FrameworkImports], { init: true })
.subscribe(
() => console.log('Started!'),
(e) => console.error(e)
);
2.Lets create AppModule
Filename: src/app/app.module.ts
import { Module } from '@gapi/core';
import { AuthMicroserviceModule } from './auth/auth.module';
import { CoreModule } from './core/core.module';
@Module({
imports: [
CoreModule,
AuthMicroserviceModule
]
})
export class AppModule { }
3.Lets create our AuthMicroserviceModule which is just regular module named for convinience
Filename: src/app/auth/auth.module.ts
import { Module } from '@gapi/core';
import { AuthQueriesController } from './auth.queries.controller';
import { CoreModule } from '../core/core.module';
@Module({
imports: [CoreModule],
controllers: [AuthQueriesController],
})
export class AuthMicroserviceModule {}
4.And here is a Tricky
part you may say 'why i import double CoreModule ?' let me explain:
'Our application is separated on Microservices called Lambdas, so our AuthMicroserviceModule should have independent injection for CoreModule
when we use this module as a Microservice.Here is a so called Tricky
part you can start all created microservices as one because UserMicroserviceModule
is a regular module which can be imported inside AppModule like we did.This techinique lets you to reuse the same logic inside lambdas instead separate modules to different repositories and to manage version for it.Here our application is presented as a Single application can be tested as a single application and every component of it can be unit tested as a separate modules and services.That way we can scale this application to many Microservices so called Lambdas
and to merge Schema from all of them and to serve it as a Single endpoint API `http://localhost:9000/graphql'.This can help you when you have Client and this client is requesting the same API no metter what you do inside of the architecture logic.This cannot be done if our Lambda is hardcoded somewhere inside client.
5.Create AuthQueriesController
Filename: src/app/auth/auth.queries.controller.ts
import { Controller, Type, Query, GraphQLNonNull, GraphQLString, Public } from '@gapi/core';
import { UserTokenType } from './auth.type';
@Controller()
export class AuthQueriesController {
@Type(UserTokenType)
@Public()
@Query({
email: {
type: new GraphQLNonNull(GraphQLString)
},
password: {
type: new GraphQLNonNull(GraphQLString)
}
})
login(root, { email, password }, context) {
....
return {};
}
}
6.Now we have our app configurated and when we execute npm run start
we should see the login
query presented inside http://localhost:9000/graphiql
http://0.0.0.0:9000/graphiql?query=%7B%0A%20%20login(email%3A%20%22dada%22%2C%20password%3A%20%22dada%22)%20%7B%0A%20%20%20%20token%0A%20%20%20%20user%20%7B%0A%20%20%20%20%20%20id%0A%20%20%20%20%20%20username%0A%20%20%20%20%7D%0A%20%20%7D%0A%7D%0A
7.Now when we have our HelloWorld app lets deploy it to Amazon Serverless architecture
Lets configurate one last thing which is our Microservice main.ts
, since AuthMicroserviceModule can be independent application and we need to inject customer
request to our generated Webserver aka Lambda.
Lets create main.ts
file looking almost the same like src/main.ts
but we have our exported handler
async function.
Filename: src/app/auth/main.ts
import { BootstrapFramework, Container, HAPI_SERVER } from '@gapi/core';
import { format } from 'url';
import { AuthMicroserviceModule } from './auth.module';
import { Server } from 'hapi';
import { FrameworkImports } from '../../framework-imports';
const App = BootstrapFramework(AuthMicroserviceModule, [FrameworkImports], { init: true }).toPromise();
export const handler = async (event, context, callback) => {
// Bootstrapp main application and make lambda hot
await App;
let url = format({
pathname: event.path,
query: event.queryStringParameters
});
// Since we can have multiple lambdas but they are running as a single server inside Gapi architecture we need to remove auth/ microservice path
// example: https://x2kwj8rcjh.execute-api.us-east-2.amazonaws.com/staging/auth/graphql=query....
// our API is not responding to this address internally instead
// http://localhost:9000/graphql not http://localhost:9000/auth/graphql
// So lets remove this auth/ ;)
url = url.replace('auth/', '');
const options = {
method: event.httpMethod,
url,
payload: event.body,
headers: event.headers,
validate: false
};
let res = {
statusCode: 502,
result: null
};
// Get HAPI_SERVER instance and inject request comming from lambda path
try {
res = await Container.get<Server>(HAPI_SERVER).inject(options);
} catch (e) {
console.error('ERROR', JSON.stringify(e));
}
const headers = Object.assign({
'Access-Control-Allow-Origin': '*',
'Access-Control-Allow-Methods': 'DELETE,GET,HEAD,OPTIONS,PATCH,POST,PUT'
});
return {
statusCode: res.statusCode,
body: res.result,
headers
};
};
8.Now we need to deploy
This command will bundle auth microservice in particular main.ts and will TreeShake everything then will be transferred to dist/auth/main.js
This feature is included inside Parcel and internally we run this command parcel build src/app/auth/main.ts --target node --out-dir dist/auth
npm run deploy:serverless
9.Lets wait till Lambda is deployed and see what if the lambda is working by running our Proxy Server configurated to getSchemaIntrospection to our newly generated lambda microservice
npm run start-proxy-staging
You will have APP Running on http://localhost:9000/graphiql and this Schema is introspected from your Lambda Microservice.
10.If you want to simulate Proxy architecture you need to start AUTH service as a separate app by running:
npm run start-auth
Then execute your proxy local server:
npm run start-proxy
Testing shows that Gapi is using 85 MB lambda memory so i decided to limit them to 128 mb if you use it well it will treat you well :)
Bundle will be somewhere between 18-20 mb.The basic concept is that you can create many functions related with same project run them as SingleServer but when you deploy them every module is independent microservice.In the end you create PROXY server with Microservices which MERGES Both Microservices Lambdas as a Single Endpoint GraphQL
Njoy! :)
Adding microservices inside src/app/app-proxy.module.ts
import { Module } from '@gapi/core';
import { CoreModule } from './core/core.module';
import { GapiMicroserviceModule } from '@gapi/microservices';
@Module({
imports: [
CoreModule,
GapiMicroserviceModule.forRoot([
{
name: 'auth-microservice',
link: `${process.env.AWS_CLOUD_LINK}/auth/graphql`
}
])
]
})
export class AppProxyModule { }
Environment AWS_CLOUD_LINK you can set inside gapi-cli.conf.yml for specific environment
lambda-proxy-production:
AWS_CLOUD_LINK: 'https://lpsm25eo1k.execute-api.us-east-2.amazonaws.com/prod'
lambda-proxy-staging:
AWS_CLOUD_LINK: 'https://aiey6imalh.execute-api.us-east-2.amazonaws.com/staging'
To start @gapi as a proxy server using 2 created lambda microservices
More info inside gapi-cli.conf.yml
It will run environment lambda-proxy-staging
from gapi-cli.conf.yml
gapi proxy staging
It will run environment lambda-proxy-production
from gapi-cli.conf.yml
gapi proxy prod
Serverless.yml configuration
service: gapi-sequelize-serverless
provider:
name: aws
runtime: nodejs8.10
stage: staging
profile: default
region: us-east-2
functions:
auth:
handler: src/app/auth/main.handler
events:
- http:
path: "/auth/{proxy+}"
method: any
cors: true
integration: lambda-proxy
memorySize: 128
timeout: 10
plugins:
- serverless-offline
Testing
To start developing with testing GAPI uses JEST and gapi-cli is preconfigurated for your needs! :)
To run single test type:
gapi test
Testing watch mode
Note: You need to start server before running tests
Note: Everytime you make change to server it will restart server and execute tests
Note: To add more tests just create e2e.spec.ts or unit.spec.ts somewhere inside the application
Start the application
gapi start
Execute test with --watch argument
gapi test --watch
You will end up with something like this
Custom logic before testing ( for example creating MOCK users to database before testing)
Create file test.ts inside root/src/test.ts with this content
Everytime you run test with --before argument it will set environment variable BEFORE_HOOK
if (process.env.BEFORE_HOOK) {
// do something here
}
Then execute tests with --before
gapi test --before
This command will start root/src/test.ts file and will wait for process.exit(0) so you can customize your before logic check this link for reference
Following commands will start RabbitMQ, PostgreSQL, API, NGINX as a services you need DOCKER for them
API will be served on https://localhost:80 and https://localhost:80/subscriptions
Docker
To build project with Docker type:
gapi app build
To start project with Docker type:
gapi app start
To stop project type:
gapi app stop
Workers
All workers will be mapped as Proxy and will be reverted to https://localhost:80 and https://localhost:80/subscriptions
So you don't have to worry about if some of your workers stopped responding
TODO: Create monitoring APP for all workers and main API
To start workers type:
gapi workers start
To stop workers type:
gapi workers stop
To add more workers
By default there are 4 workers with 4 processes with "exec_mode: cluster" of the original process inside single docker container
You can control Processes inside single docker container from "root/process.yml" file.
apps:
- script : './src/main.ts'
name : 'APP'
exec_mode: 'cluster'
instances: 4
To map new worker as a stream open root/nginx/config/private/default
upstream app_servers {
server 182.10.0.3:9000; # Main process
server 182.10.0.21:9000; # Worker 1
server 182.10.0.22:9000; # Worker 2
server 182.10.0.23:9000; # Worker 3
server 182.10.0.24:9000; # Worker 4
# Add more workers here
# server 182.10.0.25:9000; # Worker 5
}
server {
listen 80;
server_name api.yourdomain.com;
access_log api-yourdomain.access.log;
location / {
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "upgrade";
client_max_body_size 50M;
proxy_set_header Host $http_host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
proxy_set_header X-Frame-Options SAMEORIGIN;
proxy_buffers 256 16k;
proxy_buffering off;
proxy_buffer_size 16k;
proxy_read_timeout 600s;
proxy_pass http://app_servers;
}
location /subscriptions {
# prevents 502 bad gateway error
proxy_buffers 8 32k;
proxy_buffer_size 64k;
# redirect all HTTP traffic to localhost:9000;
proxy_pass http://app_servers/subscriptions;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header Host $http_host;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
#proxy_set_header X-NginX-Proxy true;
# enables WS support
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "upgrade";
proxy_buffering off;
proxy_read_timeout 999999999;
}
if ($scheme = http) {
return 301 https://$server_name$request_uri;
}
listen 443;
ssl on;
ssl_certificate /usr/share/certs/cert.pem;
ssl_certificate_key /usr/share/certs/cert.key;
}
When you add another worker it should be on different IP with same port 9000
Open root/gapi.conf.yml file you will find this file:
config:
# Application configuration
app:
local:
API_PORT: 9000
API_CERT: ./cert.key
NODE_ENV: local
AMQP_HOST: ec2-18-221-238-251.us-east-2.compute.amazonaws.com
AMQP_PORT: 5672
DB_PORT: 5432
DB_NAME: postgres
DB_HOST: phoneumdev.cobu7srvrp5s.us-east-2.rds.amazonaws.com
DB_USERNAME: phoneumdev
DB_PASSWORD: Phoneum!123456
GRAPHIQL: true
ENDPOINT_TESTING: http://localhost:9000/graphql
TOKEN_TESTING: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJlbWFpbCI6ImtyaXN0aXFuLnRhY2hldkBnbWFpbC5jb20iLCJzY29wZSI6WyJBRE1JTiJdLCJpZCI6MSwiaWF0IjoxNTE2OTk2MzYxfQ.7ANr5VHrViD3NkCaDr0nSWYwk46UAEbOwB52pqye4AM
GRAPHIQL_TOKEN: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJlbWFpbCI6ImtyaXN0aXFuLnRhY2hldkBnbWFpbC5jb20iLCJpZCI6MSwic2NvcGUiOlsiQURNSU4iXSwiaWF0IjoxNTIwMjkxMzkyfQ.9hpIDPkSiGvjTmUEyg_R_izW-ra2RzzLbe3Uh3IFsZg
prod:
API_PORT: 9000
API_CERT: ./cert.key
NODE_ENV: production
AMQP_HOST: 182.10.0.5
AMQP_PORT: 5672
DB_PORT: 5432
DB_HOST: 182.10.0.4
DB_USERNAME: dbuser
DB_PASSWORD: dbuserpass
DB_NAME: postgres
ENDPOINT_TESTING: http://localhost:9000/graphql
TOKEN_TESTING: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJlbWFpbCI6ImtyaXN0aXFuLnRhY2hldkBnbWFpbC5jb20iLCJzY29wZSI6WyJBRE1JTiJdLCJpZCI6MSwiaWF0IjoxNTE2OTk2MzYxfQ.7ANr5VHrViD3NkCaDr0nSWYwk46UAEbOwB52pqye4AM
lambda-proxy-local:
AWS_CLOUD_LINK: 'http://localhost:9000'
DISABLE_EFFECTS: 'true'
API_PORT: 9001
API_CERT: ./cert.key
NODE_ENV: production
AMQP_HOST: 182.10.0.5
AMQP_PORT: 5672
DB_PORT: 5432
DB_HOST: yourenvironemnt.cobu1srvrp5s.us-east-2.rds.amazonaws.com
DB_USERNAME: dbuser
DB_PASSWORD: dbuserpass
DB_NAME: postgres
ENDPOINT_TESTING: http://localhost:9000/graphql
GRAPHIQL_TOKEN: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJlbWFpbCI6ImtyaXN0aXFuLnRhY2hldkBnbWFpbC5jb20iLCJpZCI6MSwic2NvcGUiOlsiQURNSU4iXSwiaWF0IjoxNTIwMjkxMzkyfQ.9hpIDPkSiGvjTmUEyg_R_izW-ra2RzzLbe3Uh3IFsZg
lambda-proxy-production:
AWS_CLOUD_LINK: 'https://lpsm25eo1k.execute-api.us-east-2.amazonaws.com/prod'
DISABLE_EFFECTS: 'true'
API_PORT: 9000
API_CERT: ./cert.key
NODE_ENV: production
AMQP_HOST: 182.10.0.5
AMQP_PORT: 5672
DB_PORT: 5432
DB_HOST: yourenvironemnt.cobu1srvrp5s.us-east-2.rds.amazonaws.com
DB_USERNAME: dbuser
DB_PASSWORD: dbuserpass
DB_NAME: postgres
ENDPOINT_TESTING: http://localhost:9000/graphql
GRAPHIQL_TOKEN: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJlbWFpbCI6ImtyaXN0aXFuLnRhY2hldkBnbWFpbC5jb20iLCJpZCI6MSwic2NvcGUiOlsiQURNSU4iXSwiaWF0IjoxNTIwMjkxMzkyfQ.9hpIDPkSiGvjTmUEyg_R_izW-ra2RzzLbe3Uh3IFsZg
lambda-proxy-staging:
AWS_CLOUD_LINK: 'https://x2kwj8rcjh.execute-api.us-east-2.amazonaws.com/staging'
DISABLE_EFFECTS: 'true'
API_PORT: 9000
API_CERT: ./cert.key
NODE_ENV: production
AMQP_HOST: 182.10.0.5
AMQP_PORT: 5672
DB_PORT: 5432
DB_HOST: yourenvironemnt.cobu1srvrp5s.us-east-2.rds.amazonaws.com
DB_USERNAME: dbuser
DB_PASSWORD: dbuserpass
DB_NAME: postgres
ENDPOINT_TESTING: http://localhost:9000/graphql
GRAPHIQL_TOKEN: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJlbWFpbCI6ImtyaXN0aXFuLnRhY2hldkBnbWFpbC5jb20iLCJpZCI6MSwic2NvcGUiOlsiQURNSU4iXSwiaWF0IjoxNTIwMjkxMzkyfQ.9hpIDPkSiGvjTmUEyg_R_izW-ra2RzzLbe3Uh3IFsZg
# Testing configuration for local(dev) or worker(running tests as a separate worker with separate database)
test:
local: extends app/local
prod: extends app/prod
worker:
API_PORT: 9000
API_CERT: ./cert.key
NODE_ENV: production
DB_PORT: 5432
DB_HOST: 182.10.0.99
AMQP_HOST: 182.10.0.5
AMQP_PORT: 5672
DB_USERNAME: dbuser
DB_PASSWORD: dbuserpass
DB_NAME: postgres
ENDPOINT_TESTING: http://182.10.0.101:9000/graphql
TOKEN_TESTING: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJlbWFpbCI6ImtyaXN0aXFuLnRhY2hldkBnbWFpbC5jb20iLCJzY29wZSI6WyJBRE1JTiJdLCJpZCI6MSwiaWF0IjoxNTE2OTk2MzYxfQ.7ANr5VHrViD3NkCaDr0nSWYwk46UAEbOwB52pqye4AM
schema:
introspectionEndpoint: http://localhost:9000/graphql
introspectionOutputFolder: ./src/app/core/api-introspection
commands:
testing:
stop:
- docker rm -f gapi-api-prod-worker-tests-executor
- docker rm -f gapi-api-prod-worker-tests-provider
start:
- gapi testing start-provider
- sleep 10
- gapi testing start-executor
- echo Cleaning...
- gapi testing stop
start-executor:
- docker run -d --network=gapiapiprod_gapi --ip=182.10.0.100 --name gapi-api-prod-worker-tests-executor gapi/api/prod
- docker exec gapi-api-prod-worker-tests-provider npm -v
- gapi test --worker --before
start-provider: docker run -d --network=gapiapiprod_gapi --ip=182.10.0.101 --name gapi-api-prod-worker-tests-provider gapi/api/prod
workers:
start:
- gapi workers start-1
- gapi workers start-2
- gapi workers start-3
- gapi workers start-4
stop:
- docker rm -f gapi-api-prod-worker-1
- docker rm -f gapi-api-prod-worker-2
- docker rm -f gapi-api-prod-worker-3
- docker rm -f gapi-api-prod-worker-4
start-1: docker run -d --network=gapiapiprod_gapi --ip=182.10.0.21 --name gapi-api-prod-worker-1 gapi/api/prod
start-2: docker run -d --network=gapiapiprod_gapi --ip=182.10.0.22 --name gapi-api-prod-worker-2 gapi/api/prod
start-3: docker run -d --network=gapiapiprod_gapi --ip=182.10.0.23 --name gapi-api-prod-worker-3 gapi/api/prod
start-4: docker run -d --network=gapiapiprod_gapi --ip=182.10.0.24 --name gapi-api-prod-worker-4 gapi/api/prod
example-worker-with-port: docker run -d --network=gapiapiprod_gapi --ip=182.10.0.25 --name gapi-api-prod-worker-5 -p 9001:9000 gapi/api/prod
app:
start:
- docker-compose -p gapi-api-prod up --force-recreate -d
- gapi rabbitmq enable-dashboard
stop:
- gapi nginx stop
- gapi api stop
- gapi rabbitmq stop
- gapi postgres stop
- gapi postgres stop-testing
build: docker build -t gapi/api/prod .
api:
stop: docker rm -f gapi-api-prod
nginx:
stop: docker rm -f gapi-api-nginx
postgres:
stop: docker rm -f gapi-api-postgres
stop-testing: docker rm -f gapi-api-postgres-testing
rabbitmq:
stop: docker rm -f gapi-api-rabbitmq
restart: docker restart gapi-api-rabbitmq
enable-dashboard: docker exec gapi-api-rabbitmq rabbitmq-plugins enable rabbitmq_management
pgAdmin:
stop: docker rm -f gapi-api-pg-admin
proxy:
local: gapi start --lambda-proxy-local --path=src/main-proxy.ts
staging: gapi start --lambda-proxy-staging --path=src/main-proxy.ts
prod: gapi start --lambda-proxy-production --path=src/main-proxy.ts
build:
lambdas: parcel build src/main.ts --target node --out-dir dist/main
lambdas-auth: parcel build src/app/auth/main.ts --target node --out-dir dist/auth
# You can define your custom commands for example
# commands:
# your-cli:
# my-command: 'npm -v'
# This command can be executed as "gapi your-cli my-command"
Adding one more worker:
start-5: 'docker run -d --network=gapiapiprod_gapi --ip=182.10.0.25 --name gapi-api-prod-worker-5 -p 9005:9000 gapi/api/prod'
Then edit start task inside workers to start new worker 5
start: 'gapi workers start-1 && gapi workers start-2 && gapi workers start-3 && gapi workers start-4 & gapi workers start-5'
Thats' it!! Now you have 4 processes like CLUSTERS inside 1 docker container with ip 182.10.0.25 and external port(optional) 9005;
You can specify worker also without port because all workers are inside internal network called "gapiapiprod_gapi"
182.10.0.21/22/23/24/25:9000
start-5: 'docker run -d --network=gapiapiprod_gapi --ip=182.10.0.25 --name gapi-api-prod-worker-5 gapi/api/prod'
If you want to change port forwarding to another port you need to set just nginx configuration:
nginx:
image: sameersbn/nginx:1.10.1-5
ports:
- "81:80"
- "443:443"
Now you can find your API served onto https://localhost:81/ and https://localhost:81/subscriptions
All workers don't care about that because they will be served and mapped from nginx to port 80.
You can check docker-compose file to configurate environment variables
version: '2'
services:
nginx:
image: sameersbn/nginx:1.10.1-5
ports:
- "80:80"
# - "443"
volumes:
- ./nginx/config:/etc/nginx
- ./nginx/html:/usr/share/nginx/html/
- ./nginx/certs:/usr/share/certs
restart: always
container_name: gapi-api-nginx
networks:
gapi:
ipv4_address: 182.10.0.2
api:
image: gapi/api/prod:latest
ports:
- "9000"
restart: always
mem_limit: 1000000000
cpu_shares: 73
container_name: gapi-api-prod
depends_on:
- nginx
- rabbitMq
- PostgreSQLDev
networks:
gapi:
ipv4_address: 182.10.0.3
PostgreSQLDev:
image: sameersbn/postgresql:9.5-3
ports:
- "5432"
environment:
- DEBUG=false
- TIMEZONE=Europe/Sofia
- LOCALE=bg_BG.UTF-8
- DB_USER=dbuser
- DB_PASS=dbuserpass
- DB_NAME=postgres
- DB_TEMPLATE=
- DB_EXTENSION=
- REPLICATION_MODE=
- REPLICATION_USER=
- REPLICATION_PASS=
- REPLICATION_SSLMODE=
restart: always
container_name: gapi-api-postgres
networks:
gapi:
ipv4_address: 182.10.0.4
PostgreSQLDevTesting:
image: sameersbn/postgresql:9.5-3
ports:
- "5432"
environment:
- DEBUG=false
- TIMEZONE=Europe/Sofia
- LOCALE=bg_BG.UTF-8
- DB_USER=dbuser
- DB_PASS=dbuserpass
- DB_NAME=postgres
- DB_TEMPLATE=
- DB_EXTENSION=
- REPLICATION_MODE=
- REPLICATION_USER=
- REPLICATION_PASS=
- REPLICATION_SSLMODE=
restart: always
container_name: gapi-api-postgres-testing
networks:
gapi:
ipv4_address: 182.10.0.99
rabbitMq:
image: rabbitmq:3.7.2
ports:
- "15672:15672"
- "5672:5672"
- "5671:5671"
- "4369:4369"
restart: always
container_name: gapi-api-rabbitmq
networks:
gapi:
ipv4_address: 182.10.0.5
pgadmin:
image: thajeztah/pgadmin4
ports:
- "5050"
volumes:
- /usr/bin/:/usr/pg
- /usr/database/:/usr/database
- /tmp/:/tmp
restart: always
container_name: gapi-api-pg-admin
networks:
gapi:
ipv4_address: 182.10.0.6
networks:
gapi:
driver: bridge
ipam:
config:
- subnet: 182.10.0.0/16
gateway: 182.10.0.1
After successfully started project you can open your browser to localhost:80 or 182.10.0.3:9000 the api will be served there
TODO: Better documentation...
Enjoy ! :)