To allocate costs or maximize savings? That’s the question many AWS customers will have to answer when formulating their FinOps strategy relating to Savings Plans. If part of your daily routine is finding ways to cut cloud costs, then you know exactly what I’m talking about. Appropriate chargeback reporting is an undeniable necessity for any business, but in this world of uncontrolled rising cloud costs, so is capitalizing on any savings opportunities!

A few years ago, we realized that spending in our AWS product test environment had jumped significantly from one month to the next. We drilled down into the issue and traced it to some RDS database instances that had been spun up to test new product features. No one realized that these expensive instances were left running after the tests were complete, and subsequently racking up charges for several months.

For many years after the inception of Compute Engine on June 28, 2012 (GA December 2, 2013), N1 was the only Google Cloud machine type family offered.

Cloud is a driving force that is reshaping organizations to adapt their people and processes in embracing this game-changing technology. Recently, Mike Fonseca of HashiCorp published a Guide to Cloud Cost Optimization with HashiCorp Terraform, in which he details how Densify can seamlessly integrate with Terraform in to help ensure your enterprise infrastructure is always cost optimized.

Toronto, Ontario – October 10, 2020 – Densify, a leader in cloud and container cost management, today announced that its product has been Red Hat Operator Certified and can be purchased in the Red Hat Marketplace. The Marketplace is a one-stop shop to find, try, buy, and manage enterprise applications across an organization’s hybrid IT infrastructure.

I’ve been writing about continuous cloud optimization for a while now, and recently, I’ve spoken with several organizations to understand any challenges they’re currently facing in their automation journey. Their insights would help us understand how we can improve our technology to better support them. I discovered two fundamental themes behind their challenges.

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.