Skip to content

Latest commit

 

History

History
97 lines (74 loc) · 3.75 KB

README.md

File metadata and controls

97 lines (74 loc) · 3.75 KB

Movie Microservice

Implements Movie CRUD and Queries functionality using the Redis Enterprise Cloud with the RediSearch module and the Serverless Framework

Pre Requisites

  • Node.js
  • AWS account & Credentials Setup

Install Serverless framework

This service use the serverless framework, before running the application you must install the framework locally.

> npm install -g serverless

Once install the serverless command line is available

AWS - Config Credentials

Follow these steps to create an IAM user for the Serverless Framework:

  1. Login to your AWS account and go to the Identity & Access Management (IAM) page.

  2. Click on Users and then Add user. Enter a name in the first field to remind you this User is related to the Serverless Framework, like serverless-admin. Enable Programmatic access by clicking the checkbox. Click Next to go through to the Permissions page. Click on Attach existing policies directly. Search for and select AdministratorAccess then click Next: Review. Check to make sure everything looks good and click Create user.

  3. View and copy the API Key & Secret to a temporary place. You'll need it in the next step.

    $ serverless config credentials --provider provider --key key --secret secret

Install Dependencies

> cd movies-list-microservice
> npm install

Configuring serverless framework

All of the Lambda functions in your serverless service can be found in serverless.yml under the functions property.

Configure Redis Cloud database

  • Create an account on Redislabs
  • Create a subscription and database instance with the RediSearch Module enabled
  • In serverless.yml set the following environment variables: 
        REDIS_HOST: [REDIS_HOST]
    REDIS_PORT: [REDIS_PORT]
    REDIS_PASSWORD: [REDIS_PASSWORD]

Import the sample dataset and indices

  • Run the following command to load the dataset into your redis instance: 
    redis-cli -p [redislabsport]  -h [redislabshost]  -a [password] < import_movies.redis

Deploy the application to AWS

  • run   serverless deploy, you should get an output like this: 
    Service Information
service: movies-list-microservice
stage: dev
region: us-east-1
stack: movies-list-microservice-dev
resources: 24
api keys:
  None
endpoints:
  GET - https://XXXXXXXX.execute-api.us-east-1.amazonaws.com/api/movies/search
  GET - https://XXXXXXXX.execute-api.us-east-1.amazonaws.com/api/movies/group_by/{field}
  GET - https://XXXXXXXX.execute-api.us-east-1.amazonaws.com/api/movies/{id}
  POST - https://XXXXXXXX.execute-api.us-east-1.amazonaws.com/api/movies/{id}
functions:
  listMovies: movies-list-microservice-dev-listMovies
  searchMovies: movies-list-microservice-dev-searchMovies
  getMovie: movies-list-microservice-dev-getMovie
  saveMovie: movies-list-microservice-dev-saveMovie
layers:
  None
Serverless: Removing old service artifacts from S3...
Serverless: Run the "serverless" command to setup monitoring, troubleshooting and testing.
  • Copy this base https://XXXXXXXX.execute-api.us-east-1.amazonaws.com/api endpoint and paste into our frontend env url and paste in env.development
  • Follow the steps mentioned in the front-end folder for running the frontend

Working in Local mode

We have configured a plugin called serverless-offline inside our serverless application which allows us to run this lambda function in offline mode to enable faster development.

You can run it offline by running the command:

$ npm start