metoo.io is the largest, most complex web service I have ever deployed. It’s a really cool app, and I’m not just saying that because I made it. If you have a chance you should absolutely check it out.

In deploying a stack, you want to be mostly certain of the way that you deploy it from the beginning, because certain containers begin to rely on the minutae of what its input from another API looks like and changing that is not as streamlined as one would like. If you are looking for a stack to replicate, you should be comfortable choosing the following applications for their current bleeding-egde reputations.

• Reverse Proxy: Nginx lets us use LetsEncrypt, a free and open Certificate Authority which also allows us to generate free TLS Certificates for each of our subdomains, all while still maintaining a SSL Labs A+ rating.

• Backend Framework: Django REST allows us to use the highly scalable Python Web framework while sending JSON data as response requests. This works perfectly in conjunction with our app’s frontend React Native which injests JSON as input.

• Frontend Framework: React Native allows us to deploy to androids and iPhones seemlessly all while using Javascript, a forgiving, highl level, weakly typed language that’s relatively easy to debug.

• Relational Database Management System: PostGreSQL with the PostGIS extension allows us to use geolocational data.

• Cache: Redis is our highly scalable, master-slave ready, in-memory cache. We chose redis over memcached due to more support in Django.

• Asynchronous task completion: Celery allows us to use run non-blocking tasks such as sending texts, emails, or creating notification objects outside of the user’s request.

• Task Message Broker: RabbitMQ - as opposed to using Redis as a message broker - allows us to persist tasks even in the off chance that RabbitMQ needs to be restarted. Redis does not allow for this.

• Containerization Strategy: Docker means we deploy each of the above strategies as microservices and then orchestrate them in a production environment using Kubernetes.

• Orchestration Strategy: Kubernetes allows for zero downtime of the service through deployment updates and potential rollbacks.

• Profiling: Django Silk Is an open source profiler for django which creates models in your applications database which can be updated on a variable scale and lets us see where bottlenecks in certain views occur, or where N+1 issues arise.

• Error Reporting: Sentry.io is an entirely open source service that allows us to setup our own sentry service as a container of one of our GKE nodes.

• Replicas: Due to the nature of microservices being extremely portable, it’s so easy to scale each of the above services to infinity based on the current required need. For example, say we need far more Asynchronous task workers deployed because we are currently undergoing a large amount of user signups and we need to be able to send a large amount of notifications to friends of the user signing up, emails, etc.

Now that we have our stack up and running, we would want in the most ideal circumstance to be able to access various data pertaining to each node, and pod container. For this, we deployed a stat stack.

First, we need a data aggregating tool. There are plenty of choices from StatsD to influxDB to Prometheus, but we decided to go with Prometheus.

• Prometheus allows us to aggregate data into a queryable format and also provides an API from which we use Grafana to scrape from.

• Grafana is originally a graphite extension that allows graphing a wide variety of data sources ranging from Prometheus, to a PostgreSQL or MySQL instance.

• Additionally we use Node-exporter, cAdvisor, and Alertmanager for Prometheus to scrape from.

I would absolutely recommend the same or similar stack to anyone who wants to create a reliable, highly scalable infrastructure for their webservice or similar application, the ease of knowing that everything just works is just another reason that living in 2018 is something to be appreciative of. It’s the most bleeding edge of technological advancement which we have available to us today, and it’s only going to get more mainstreamed from here.

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