This post summarizes the programming logic behind our products Ripple and Wave on how we analyze and calculate AWS usages and cost.
In order to get insight and collect data of an AWS account usages, the best way is to enable AWS Cost & Usage Report (CUR) and a trunk of big data in CSV format will be dumped into an S3 bucket under the payer AWS account. These data contains all of the usage details and service dimensions, such as AmazonEC2 Running Hours, Instance Type, Reserved Instance (RI) record, CPU utilization, Storage I/O, etc.
Hello there again. It’s been a while. Last time, I wrote about ouchan, our monorepo for Go-based code. In that article, I briefly mentioned mochi*, which is what we call our Kubernetes clusters where most of our backend services are running on. We use GKE to run these clusters across three zones in Tokyo region. At the moment, we have three clusters, each for development, staging, and production. Each environment is mapped to a specific branch: master, qa, and production, respectively.
At Mobingi, we’ve been using a single repository (monorepo) to organize mainly our Go-based code, which we fondly call ouchan, for about a year now. I actually uploaded a stripped down version of this repository here as reference. It is stripped down in a sense that it uses a more straightforward script compared to our build tool which, over the months, has been customized for our CI/CD pipeline.
This is a repost of Mobingi CEO @wayland’s Qiita post. You can find the original post here. A Japanese version of the post can also be found here.
Welcome to Mobingi Tech Blog, english edition! We actually have a separate blog in Japanese but we wanted to have an english blog as well.