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Valentin Prugnaud 🦊
Valentin Prugnaud 🦊

Posted on • Originally published at whatdafox.com on

Deploy NestJS with Fastify on Google Cloud Run

#gcp #devops #tutorials

Repository: WhatDaFox/nestjs-fastify-cloud-run-poc

Configure Google Cloud

To be able to build and deploy, you will need a Google Cloud project, with a billing account set up, as well as
the Google Cloud CLI installed.

Then you will need to create a configuration for your project:

$ gcloud config configurations create cloud-run $ gcloud auth login # and follow the steps $ gcloud config set project YOUR_PROJECT_ID
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Create the project

For this proof of concept, I will only use the default NestJS application, that contains a single endpoint /
returning Hello world!:

$ npm i -g @nestjs/cli $ nest new cloud-run
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Install the Fastify driver:

$ npm i --save @nestjs/platform-fastify
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We need to update main.ts to make use of the Fastify driver. Also, Cloud Run will decide the port of our application, so we have to update the main.ts file to reference
the PORT environment variable, like so:

import { NestFactory } from '@nestjs/core'; import { FastifyAdapter, NestFastifyApplication } from '@nestjs/platform-fastify'; import { AppModule } from './app.module'; async function bootstrap() { const app = await NestFactory.create<NestFastifyApplication>( AppModule, new FastifyAdapter({ logger: true }), ); app.enableCors(); await app.listen(parseInt(process.env.PORT) || 3000, '0.0.0.0'); } bootstrap();
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Now we are ready to create the Dockerfile.

Create the Dockerfile

We need to containerize our application to be able to run on Cloud Run. Create a Dockerfile at the root of your project
and copy/paste the following:

For better performance, I decided to build the app before hand and run the start:prod command.

# Use the official lightweight Node.js 12 image. # https://hub.docker.com/_/node FROM node:12-alpine # Create and change to the app directory. WORKDIR /usr/src/app # Copy application dependency manifests to the container image. # A wildcard is used to ensure both package.json AND package-lock.json are copied. # Copying this separately prevents re-running npm install on every code change. COPY package*.json ./ # Install dependencies RUN npm install # Copy local code to the container image. COPY . ./ # Build the application RUN npm run build # Run the web service on container startup. CMD [ "npm", "run", "start:prod" ]
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Build & Deploy

Now, we can use Cloud Build to build our docker image. Cloud Build will automatically detect our Dockerfile, build,
and push our image in Google Container Registry:

$ gcloud builds submit --tag gcr.io/YOUR_PROJECT/helloworld
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Once that's done, we can run the following command to deploy our new revision to Cloud Run:

$ gcloud run deploy --image gcr.io/YOUR_PROJECT/helloworld --platform managed
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Benchmark

When testing, I ran a small (to avoid crazy costs) benchmark with Apache Benchmark.

Here is the command I ran:

$ ab -n 1000 -c 80 https://cloud-run-url/
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Here are the results:

This is ApacheBench, Version 2.3 <$Revision: 1843412 $> Copyright 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/ Licensed to The Apache Software Foundation, http://www.apache.org/ Benchmarking cloud-run-url (be patient) Completed 100 requests Completed 200 requests Completed 300 requests Completed 400 requests Completed 500 requests Completed 600 requests Completed 700 requests Completed 800 requests Completed 900 requests Completed 1000 requests Finished 1000 requests Server Software: Google Server Hostname: cloud-run-url Server Port: 443 SSL/TLS Protocol: TLSv1.2,ECDHE-RSA-CHACHA20-POLY1305,2048,256 Server Temp Key: ECDH X25519 253 bits TLS Server Name: cloud-run-url Document Path: / Document Length: 12 bytes Concurrency Level: 80 Time taken for tests: 9.300 seconds Complete requests: 1000 Failed requests: 0 Total transferred: 437004 bytes HTML transferred: 12000 bytes Requests per second: 107.53 [#/sec] (mean) Time per request: 743.985 [ms] (mean) Time per request: 9.300 [ms] (mean, across all concurrent requests) Transfer rate: 45.89 [Kbytes/sec] received Connection Times (ms) min mean[+/-sd] median max Connect: 79 461 213.7 430 2633 Processing: 37 208 118.9 200 506 Waiting: 22 163 105.3 139 501 Total: 129 669 220.7 626 2739 Percentage of the requests served within a certain time (ms) 50% 626 66% 702 75% 768 80% 772 90% 862 95% 1161 98% 1371 99% 1576 100% 2739 (longest request)
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Conclusion

Compared to my previous experiment with the default installation of NestJS, I didn't observe any improvement in response time.

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