This year’s AWS Summits are more than a little different. Despite being virtual due to the COVID-19 pandemic, AWS is packing these events with lots of content. I’ve had a great time attending virtually, trying out hands-on labs, and sitting in on the technical sessions. As I work primarily with cost management and optimization for cloud compute services, this has been my main interest in attending the conferences. Here are my main takeaways around better managing your AWS cloud costs.

Assume you have a process to determine the optimal settings for CPU and memory for each container running in your environment. Since we know resource demand is continuously changing, let’s also assume these settings are being produced periodically by this process. How can you configure Ansible to implement these settings each time you run the associated playbook for the container in question?

An AWS Auto Scaling group (ASG) is a fleet of EC2 instances that can scale up or down depending on application demand. The elasticity of Auto Scaling groups makes them highly-attractive options for enterprises who do not want to invest in purchasing expensive hardware only to respond to sudden or temporary spikes in application demand.

If you are familiar with minikube, a lightweight implementation of the Kubernetes ecosystem, then you may have also heard of Minishift. Designed as a development platform and delivered through a utility, this is the Red Hat OKD (Origin Kubernetes Distribution—formerly called OpenShift Origin) all-in-one implementation of Red Hat OpenShift. Being highly versatile, it can be deployed on varying platforms.

If you have discovered that your application demand changes over time, you’re probably wondering how you can continuously adjust your cloud capacity in accordance to application demand. If you use CloudFormation, then you’re in luck! This article walks through how you can update your template code to automatically implement infrastructure adjustments, periodically.