For those of you who aren’t familiar with AWS CodePipeline, it’s a continuous integration and continuous delivery (CI/CD) framework that enables application development teams to deliver code updates more frequently and reliably. You may have also heard it being called a CI/CD or DevOps pipeline. These pipelines have always traditionally been used to deploy the components of a certain application whenever new code in “checked-in”.

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.