In Google Cloud Next 2019, they introduced a new product called [Cloud Run] (https://cloud.google.com/run/). I’ve been using it from the EAP (Early Access Program) days. [As the name suggests, basically it runs your docker image. You might be familiar with other serverless products such as [Cloud Function] (https://cloud.google.com/functions/) or [lambda] (https://aws.amazon.com/lambda/) where you provide your source code instead of a docker image. In my opinion, Cloud Run is more flexible than functions. Let me explain why.

Step 1: Setting up HAProxy

I hope you gone through [Part1] (https://viggy28.dev/article/postgres-active-active-replication/) of this series. Perhaps, one thing you might have noticed is that I’ve to connect to the specific master database. In our case, since both the databases are running on docker, only the localhost port is different. (In a production environment, most likely you going to run the databases on a different host). The main reason for active-active replication is high availability. If one of the nodes goes down, you still want your application to behave normally. You don’t want to hard-code your DSN on the application or keep checking the health of the database every time before you make a connection. Fair enough. [HAProxy] (<www.haproxy.org>), an open source project solves this particular change.

Postgres doesn’t support active-active replication natively. As of this writing, we have to rely on 3rd party tools. I decided to go with [BDR] (https://www.2ndquadrant.com/en/resources/postgres-bdr-2ndquadrant/).

I didn’t want to spin up multiple VMs. So, the obvious choice is docker. Make sure you have docker on mac & docker compose.

Step1: Running 2 Postgres instances using docker container

Thanks to [jgiannuzzi] (https://github.com/jgiannuzzi), who created a docker [image] (https://hub.docker.com/r/jgiannuzzi/postgres-bdr) with Postgres and BDR.

In this article we will see how to convert a simple python application to a containerized (Docker) one

Go to the profile of vignesh ravichandran vignesh ravichandran Sep 23, 2017 TL;DR -> Containerize a python app. Push the image and execute from Google Cloud.

On a leisurely Saturday afternoon, I thought its nice to play with containers. I was fascinated with the idea of containerizing an app and running it across different environments. Its easier (for me) to understand something when I do, instead of just reading.