AWS for Web3 BigData Project

Our selection of hashtag#AWS for hashtag#Ludo — hashtag#Web3 reputation platform and all other projects as a cloud computing provider is a choice polished by years of software development. We deploy our servers to AWS since they become available for wide usage. We have tried various popular SaaS platforms — Azure, Digital Ocean and others. But AWS is our choice for the most widely supported integration, simplicity of usage and tens of geographically distributed zones. You probably know that AWS is not the cheapest cloud provider in the world and that’s true. But if you know how to cook you can reduce your 15K invoice to around 3–4K. We dropped out all ready-to-use solutions like EKS or RDS and made hashtag#Kubernetes, databases, monitoring infra and message brokers run independently of the cloud provider manually tuned by our hashtag#DevOps engineers. You can ask — what’s the benefit of AWS if there are no SaaS integrations in your platform? Long story short — elastic scalability, high geographical availability and content delivery network of course.

A deployment solution for products we build is an automated Terraform scripts environment that does all things required to deploy the basic networking layer, Kubernetes infrastructure, all databases, microservice mesh (we use Istio) and even servers wrapped into Docker containers and after into pods. Automation of a cloud infrastructure is a must, not a feature. After Terraform scripts are finished the only thing we need to do to deploy into a region or multiple AWS regions is to simply run a single bash script that will run Terraform scripts through Terragrunt environments and here you go — a big beast like Ludo is deployed in 1 hour and ready to use with all its frontends and APIs.