tldr: source code and deployment instructions Motivation If you’ve worked for a software company, you’re probably familiar with build servers. When code is built and merged into production, it is usually done so in a standardized environment on dedicated servers called build servers (think tools like Jenkins, CircleCI, etc). There are lots of reasons to use them. Lately, and have been gaining popularity because they allow developers to think more about code and less about servers while paying strictly for the memory and time that they consume. Google recently announced very generous , including a hefty allowance of Cloud Functions usage per month. AWS Lambda Google Cloud Functions free offerings for most of their cloud products Since Cloud Functions execute code in Node.js environments, it should be possible to build applications that build in Node.js environments (think all frontends, like React and Angular apps to name a few). So I decided to build a Cloud Function that could build frontends built in Node.js. Webpack How It Works The Cloud Function is triggered via HTTP call (think: ). At a high level, the steps are pretty simple: Github webhooks — simply clone a Github repo. Download source code — execute a build command that you would execute on the command line, like Run the build npm run build. — since the build might output multiple files, it is easiest to package all those results into a tarball and compress it so it can be pushed somewhere else… Package the build results — Cloud Functions execute in temporary environments, so the build results must be pushed somewhere persistent to be utilized later. Having them packaged and compressed makes this easier and saves on network egress. I chose to push the packaged build to , but it can really be pushed anywhere. Push the results GCS The Numbers I tested building a basic app created by . I could only get this to run with the 2GB of RAM, 2.4 GHz configuration. Every run took less than 2 minutes. Thus, according to the , CPU resources would run out long before RAM. Create React App Google Cloud Functions always free limits 200000 free GHz-seconds / (2.4 GHz * 120 seconds per run) = ~ 694 This means it is very possible to run ~694 front-end builds for free on Google Cloud Functions every month. Given the pricing model of Cloud Functions, I’m not sure how many builds would make it worth running a dedicated build server. Challenges with Cloud Functions This was my first time building anything on Cloud Functions, and anything serverless in general. Given that Cloud Functions is in beta, I’m sure it will continue to evolve in great ways. Here were some of my biggest challenges building this project: No Filesystem Unfortunately, Cloud Functions does not really give you access to a filesystem. They do give you access to , but it seems to count against your allocated RAM which maxes out at 2GB. This is an issue when downloading a compressed tarball from Github, unzipping it, untarring it, writing to disk, and installing all Node.js build dependencies for that project. I’m not sure how much RAM this actually takes, but naively it could upper bound at ~4x the codebase size + build deps. /tmp Emulator vs. Production There are some differences between the and Cloud Functions production environment that made development difficult. While the emulator is developed by Google, they do give a disclaimer about it not being an official Google product so this is fair. Cloud Functions emulator One example is executing commands using Node.js’ . Since the emulator does not seem to run an isolated environment, depending on executables being in $PATH can work on the emulator but not in production. child processes I ended up mimicking using because I could not get the top few Node.js git packages to work on production even though they worked on the emulator. Common issues included needing basic crypto libraries installed and needing git installed. git clone Github Contents API Deployments are Slow Deployments always took a few minutes, even to deploy simple cloud functions. This made debugging emulator vs. production issues very time-consuming, because I had to redeploy for every little change (and I had a lot of them). No Node.js Executables Being able to build Node.js applications requires access to the and executables. Given that Cloud Functions are executed in a Node.js environment, I figured executing node code would be trivial — I was wrong (kind of). While I could node commands in the emulator, production could not find or executables. My first course of action was to see if I had any executables — — yep, that worked. — seems there were a few directories in $PATH — good. — for some reason this didn’t return anything (not sure why), but I had other ideas. I knew that C allows you to see the calling command via , and turns out . Excellent, I found the executable (/nodejs/bin/node)! I , and sure enough was in there too. I added that directory to $PATH and was back on track. node npm execSync node npm which ls echo $PATH find / -name node -executable argv node does as well node listed the contents of the containing directory npm Future Ideas Cache node_modules for the project being built. Every build currently runs , which takes ~60% of the build time. Cutting down on this time would greatly decrease the cost of each build. npm install Switch from to . tar-fs can apparently be faster than node-tar, but unfortunately requires . is not in $PATH by default on Cloud Functions, so I assume it is not available. It would be nice to get tar-fs working in the future. node-tar tar-fs 10x chmod chmod is how hackers start their afternoons. We’re a part of the family. We are now and happy to opportunities. Hacker Noon @AMI accepting submissions discuss advertising & sponsorship To learn more, , , or simply, read our about page like/message us on Facebook tweet/DM @HackerNoon. If you enjoyed this story, we recommend reading our and . Until next time, don’t take the realities of the world for granted! latest tech stories trending tech stories

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