Using SQS as a queue to buffer tasks is probably the most common use case for the service. Things can get tricky if these tasks have a wide range of processing durations. Today, I will show you how to implement an SQS consumer that utilizes heartbeats to dynamically extend the visibility timeout to accommodate different processing durations.
This blog post was completely generated by ChatGPT and not modified in any way. As an AI language model, my purpose is to assist and empower users with diverse tasks, from answering questions to helping develop custom tools. Recently, an IT consultant approached me for help in creating a Python script to convert a CSV file from US decimal format to German decimal format.
Joining an AWS Training allows you to learn new things for your daily work. Attending a training commonly happens in groups of up to 13 people and has more of a frontal teaching character. An alternative event are workshops are more practical and done in a small group. And now, a third solution brings teams and people together and plays a competitive game: AWS GameDays.
When deploying AWS infrastructure via Terraform, the usage of long-term IAM credentials is often the go-to method. Even though convenient, long-term credentials and secrets can pose a serious security risk to your organization if leaked. This post will show you how you can leverage AWS IAM OpenID Connect identity providers in combination with GitHub Actions and identity federation to implement a secretless Terraform deployment pipeline…using Terraform.
While traditional Infrastructure as Code tools offer a multitude of benefits, they usually fail to meet the security and compliance requirements of modern security-focused organizations when managing infrastructure at scale. This post will show you how you can leverage Open Policy Agent and Policy as Code to automate security and compliance procedures as well as enforce custom policies across an organization at scale.
This is the story of how an undocumented API call became an official one.
Up to a few years back, writing Dockerfiles was easy. In many cases, it still is - unless you are working with a mixed fleet of Intel and ARM-based processors. Are you familiar with this situation and you do not want to maintain two almost identical Dockerfiles? There is a solution…
GitHub does not support any ARM GitHub Actions Runner. So what now? Build it within your AWS environment! The results are pretty cool: You have full control over the Runners and have no more time constraints like long-running workflows that consume Runners usage minutes. I will guide you through the basics of creating an AWS EC2 instance and installing the minimum requirements on the OS for having a running GitHub Actions Runner.
