You can proxy any call to AWS API from API Gateway. You can use to enrich your serverless solution and avoid introducing some fancy service to perform even basic operations. This is possible because AWS features this out-of-the-box feature, which performs HTTP calls and authentication with minimal configuration, but a lot of people don't know how to make it work right.

You are riding your bike or your car on a track. You have to get past a turn while speeding. Do traction and skills only matter to avoid crashing yourself into a barrier? What are the factors to consider?

This is a very short summary of my short experience on Liquibase. Take it as a note to be taken into consideration.

You must protect your K8S endpoint, but you cannot make changes to your service and/or your code. How can you add a layer on top of your services?

I was doing some algorithm exercises around the internet, to keep myself motivated and challenged. I came up on this question. The proposed solution was not really appealing to me, so I thought it could have been done better.

You have a piece of software which shows some signs of age, such as hard times adapting it to new technologies, extend it to be integrated with new components, port it over new infrastructures, and so on. You are considering if it's worth it to rewrite that piece of software.

You have a layer in your application which you require, but you have no control over it. So, you decide to put some security layer on top of it, to control access from the outside world.

You have just developed your microservice, but what resources do you have to assign to it? How do you put some real numbers there, instead of some "lottery" ones? Here I show you a very simple, yet powerful technique I use for production environments. Your horizontal autoscalers will benefit from this!

You tried to deploy a fully private EKS cluster in a VPC with a private endpoint, but you end up with a broken half installation of it. You waited almost 30 minutes without accomplishing your task. You are on a dead end. Other people on the internet had this issue. What to do to fix this?

You have setup an Autoscaling GitLab Runner on your AWS account, following the official guide, but you don't know which actions to grant to the IAM user requested during the setup of GitLab Runner. You also did NOT to end up with giving full access to that user.

If you ever tried to use AWS Canary with your own Python code, be it via CloudFormation template or manually via wizard, there is a chanche that you could not figure out how to correctly make it work, due to the restriction on the handler string used to call the Canary itself. You tried to find something already done to start with, but you found NodeJS examples only.