Alternatives to Amazon CloudFront

For inboxkitten.com, an opensource disposable email service;

We migrated our serverless workload from Cloud Functions for Firebase to CloudFlare workers, taking advantage of the lower cost and faster-performing edge computing of Cloudflare network. Made possible due to our extremely low CPU and RAM overhead of our serverless functions.

If I were to summarize the limitation of Cloudflare (as oppose to firebase/gcp functions), it would be ...

1. <5ms CPU time limit
2. Incompatible with express.js
3. one script limitation per domain

Limitations our workload is able to conform with (YMMV)

For hosting of static files, we migrated from Firebase to CommonsHost

More details on the trade-off in between both serverless providers is in the article

I use Laravel because it's the most advances PHP framework out there, easy to maintain, easy to upgrade and most of all : easy to get a handle on, and to follow every new technology ! PhpStorm is our main software to code, as of simplicity and full range of tools for a modern application.

Google Analytics Analytics of course for a tailored analytics, Bulma as an innovative CSS framework, coupled with our Sass (Scss) pre-processor.

As of more basic stuff, we use HTML5, JavaScript (but with Vue.js too) and Webpack to handle the generation of all this.

To deploy, we set up Buddy to easily send the updates on our nginx / Ubuntu server, where it will connect to our GitHub Git private repository, pull and do all the operations needed with Deployer .

CloudFlare ensure the rapidity of distribution of our content, and Let's Encrypt the https certificate that is more than necessary when we'll want to sell some products with our Stripe api calls.

Asana is here to let us list all the functionalities, possibilities and ideas we want to implement.

Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.

Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!

Check Out My Architecture: CLICK ME

Check out the GitHub repo attached

In #Aliadoc, we're exploring the crowdfunding option to get traction before launch. We are building a SaaS platform for website design customization.

For the Admin UI and website editor we use React and we're currently transitioning from a Create React App setup to a custom one because our needs have become more specific. We use CloudFlare as much as possible, it's a great service.

For routing dynamic resources and proxy tasks to feed websites to the editor we leverage CloudFlare Workers for improved responsiveness. We use Firebase for our hosting needs and user authentication while also using several Cloud Functions for Firebase to interact with other services along with Google App Engine and Google Cloud Storage, but also the Real Time Database is on the radar for collaborative website editing.

We generally hate configuration but honestly because of the stage of our project we lack resources for doing heavy sysops work. So we are basically just relying on Serverless technologies as much as we can to do all server side processing.

Visual Studio Code definitively makes programming a much easier and enjoyable task, we just love it. We combine it with Bitbucket for our source code control needs.

I'm building most projects using: Server: either Fastify (all projects going forward) or ExpressJS on Node.js (existing, previously) on the server side, and Client app: either Vuetify (currently) or Quasar Framework (going forward) on Vue.js with vuex on Electron for the UI to deliver both web-based and desktop applications for multiple platforms.

The direct support for Android and iOS in Quasar Framework will make it my go-to client UI platform for any new client-side or web work. On the server, I'll probably use Fastly for all my server work, unless I get into Go more in the future.

Update: The mobile support in Quasar is not a sufficiently compelling reason to move me from Vuetify. I have decided to stick with Vuetify for a UI for Vue, as it is richer in components and enables a really great-looking professional result. For mobile platforms, I will just use Cordova to wrap the Vue+Vuetify app for mobile, and Electron to wrap it for desktop platforms.

When my SSL cert MaxCDN was expiring on my personal site I decided it was a good time to revamp some things. Since GitHub Services is depreciated I can no longer have #CDN cache purges automated among other things. So I decided on the following: GitHub Pages, Netlify, Let's Encrypt and Jekyll. Staying the same was Bootstrap, jQuery, Grunt & #GoogleFonts.

What's awesome about GitHub Pages is that it has a #CDN (Fastly) built-in and anytime you push to master, it purges the cache instantaneously without you have to do anything special. Netlify is magic, I highly recommend it to anyone using #StaticSiteGenerators.

For the most part, everything went smoothly. The only things I had issues with were the following:

• If you want to point www to GitHub Pages you need to rename the repo to www
• If you edit something in the _config.yml you need to restart bundle exec jekyll s or changes won't show
• I had to disable the Grunt htmlmin module. I replaced it with Jekyll layout that compresses HTML for #webperf

Last but certainly not least, I made a donation to Let's Encrypt. If you use their service consider doing it too: https://letsencrypt.org/donate/

The following will be a series of decisions we made that took BootstrapCDN from 0 to over 74 billion requests a month (and growing).

Initially, I didn’t want to do BootstrapCDN. I have attempted a few projects like it before and they always failed to gain any traction. In June of 2012, my boss at the time (and good friend today), David Henzel got a BuzzSumo Alert coming from an #OpenSource project on GitHub called Bootstrap and someone mentioned that MaxCDN was always looking for projects to sponsor. Long story short, David registered the domain and told me to get to work.

The first version of the site was written in PHP. It was quick and dirty but met the scope. We beta tested it for a month then people started to use it after searching for “bootstrap cdn” on Google.

I was still skeptical until, well, that’s for the next decision.

AMA below. 👇

This is the second Stack Decision of this series. You can read the last one to catch up (link below). Bootstrap, Jacob Thornton aka @fat tweeted about #BootstrapCDN and according to Google Analytics, that sent 10k uniques to the site in 24 hours. Now I was pumped but I knew I was way over my head and needed help. Fortunately, I met my co-maintainer Josh Mervine at the 2013 O’Reilly Velocity Conference and we hit it off immediately. I showed him the MaxCDN and Amazon S3 stats and his eyebrows went up. When I showed him the code, he was very polite, “well, I mean it works but I really want to try Node.js out so I’m just going to rewrite everything in Node and Ruby for the S3 scripts.

I didn’t know what to expect from Josh, to be honest. In the next decision (part 3), I will go over how he completely transformed the project.

AMA below 👇

To provide employees with the critical need of interactive querying, we’ve worked with Presto, an open-source distributed SQL query engine, over the years. Operating Presto at Pinterest’s scale has involved resolving quite a few challenges like, supporting deeply nested and huge thrift schemas, slow/ bad worker detection and remediation, auto-scaling cluster, graceful cluster shutdown and impersonation support for ldap authenticator.

Our infrastructure is built on top of Amazon EC2 and we leverage Amazon S3 for storing our data. This separates compute and storage layers, and allows multiple compute clusters to share the S3 data.

We have hundreds of petabytes of data and tens of thousands of Apache Hive tables. Our Presto clusters are comprised of a fleet of 450 r4.8xl EC2 instances. Presto clusters together have over 100 TBs of memory and 14K vcpu cores. Within Pinterest, we have close to more than 1,000 monthly active users (out of total 1,600+ Pinterest employees) using Presto, who run about 400K queries on these clusters per month.

Each query submitted to Presto cluster is logged to a Kafka topic via Singer. Singer is a logging agent built at Pinterest and we talked about it in a previous post. Each query is logged when it is submitted and when it finishes. When a Presto cluster crashes, we will have query submitted events without corresponding query finished events. These events enable us to capture the effect of cluster crashes over time.

Each Presto cluster at Pinterest has workers on a mix of dedicated AWS EC2 instances and Kubernetes pods. Kubernetes platform provides us with the capability to add and remove workers from a Presto cluster very quickly. The best-case latency on bringing up a new worker on Kubernetes is less than a minute. However, when the Kubernetes cluster itself is out of resources and needs to scale up, it can take up to ten minutes. Some other advantages of deploying on Kubernetes platform is that our Presto deployment becomes agnostic of cloud vendor, instance types, OS, etc.

#BigData #AWS #DataScience #DataEngineering

StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.

Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!

#StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit