Gaining visibility into cloud cost and driving greater overall efficiency is an ongoing journey where you need a solid understanding of your organization’s cloud consumption before taking the necessary steps to optimize their spend.

In 2009 AWS (Amazon Web Services) introduced a new EC2 pricing model known as reserved instances. In exchange for an upfront commitment of 1 or 3 years, reserved instances offer significant cost savings (anywhere from ~29% up to 72%) on cloud compute resources compared with on demand instances. Today, other cloud providers such as Microsoft Azure and Google Cloud Platform also offer similar pricing constructs. In this article you will learn.

Many of Spot’s AWS customers are using Kubernetes Operations (kops) to self-manage their Kubernetes clusters. The tool significantly simplifies cluster set up, lifecycle management via instance groups, Kubernetes Day 2 operations and generates Terraform configurations, making it a popular tool for deploying production-grade k8s clusters.

When it comes to modern container orchestration, there are a variety of control plane solutions for managing your applications in a containerized environment. Users can opt for managed services (i.e. Amazon EKS and ECS, Google GKE and Azure AKS) or run their own orchestration with Kubernetes. However, the dynamic nature of containers introduces operational complexities that can make your cloud infrastructure difficult to manage.

There are different tools and mechanisms for autoscaling in Kubernetes at both the application and infrastructure layers to help users manage their cluster resources. In this article, we’ll explore two infrastructure autoscaling tools for Kubernetes — Ocean by Spot and open source Cluster Autoscaler.

AWS Fargate is a managed service that enables you to run containers in Amazon Elastic Kubernetes Service (EKS) or Elastic Container Service (ECS). Since Fargate is serverless, you don’t need to provision or manage servers or clusters. However, you do need to set up package containers, define resource requirements, and configure permissions and networking policies. Fargate pricing is determined according to virtual CPUs (vCPUs) requirements, as well as usage of GBs of RAM for running services.

One of the key features of Ocean by Spot is a “headroom” feature, the ability to maintain a dynamic buffer of spare capacity for immediate scale-up. Ocean continuously predicts which workloads are most likely to require scale-up and adjusts headroom in line with this prediction to enable immediate scheduling of new tasks, without waiting for infrastructure provisioning. This shortens the time to execution for these workloads and dramatically speeds up the scale-up process.