Amazon Kubernetes Service (EKS) has rapidly become the de facto solution for organizations seeking to deploy, manage, and scale containerized applications using Kubernetes. EKS simplifies the complexities associated with Kubernetes, allowing teams to focus on developing and deploying applications more efficiently. However, as organizations scale their Kubernetes environments, managing and optimizing costs can quickly become a significant concern.

Naturally, our own platform forms the backbone of our cloud cost savings strategy. And before releasing any new feature, we try it out ourselves to see how well it helps us manage our own SaaS costs. If it works well for us, that means there’s already one satisfied user in the world — and there will likely be more!

Most people still remember the days when software applications were distributed mostly through CD-ROMs and floppy disks. While some companies still maintain CD distribution methods, it’s safe to say that the SaaS distribution or “SaaS revenue model” has taken over. In this guide, we’ll explore what this SaaS Revenue Model is, why it’s so popular now, and some tips to help you make the most of it.

As you’ve probably realized by now, cloud computing isn’t the future. It is here and now. According to Gartner, global spending on public cloud services alone will surpass $725 billion by 2024. This rise in cloud computing is a great career opportunity for you. And what better way to immensely benefit from this shift than becoming a cloud engineer?

Microsoft Azure offers over 150 cloud products and services. In addition to Infrastructure-as-a-Service (IaaS), Software-as-a-Service (SaaS), and Platform-as-a-Service (PaaS), Azure Cloud also supports multiple use cases. Yet, Azure can be complex, expensive, and a lot to figure out — let alone optimize for your specific cloud computing needs. Maybe you’ve looked into the cloud service provider.

The promise of cloud computing has always been about flexibility and cost-effectiveness. Yet many organizations find themselves trapped in a cycle of unpredictable costs and underutilized/overutilized resources. The culprit? A lack of understanding about the power of scaling within platforms like Amazon’s Elastic Kubernetes Service (EKS).

Cost optimization in cloud environments is no longer a luxury — it’s a necessity. As businesses increasingly migrate to AWS, they are met with the difficult task of ensuring robust performance and scalability, all while keeping an eagle eye on costs. How does one achieve this delicate balance? How can organizations ensure that their AWS architectures are both high-performing and cost-efficient?

Amazon Elastic Kubernetes Service (EKS) has revolutionized the way organizations deploy, manage, and scale containerized applications using Kubernetes. However, optimizing costs on EKS infrastructure remains a challenge for many. Enter Karpenter, a Kubernetes-native node autoscaler designed to improve resource efficiency.

Essentially, cloud infrastructure consists of a set of virtual tools and resources that help deliver cloud-based services and products. For companies, cloud infrastructure liberates them from building their own physical data centers. Instead, they rent computing capacity on a need-by-need basis. But let’s not get ahead of ourselves. In this post, we’ll define cloud infrastructure, examine cloud computing types, delivery models, and more.

Cloud computing offers many advantages over on-premises environments, including scalability, flexibility, and cost-efficiency. Yet, simply using a “lift and shift” strategy — where you move your application as-is from an on-premise environment to the cloud with minimal, if any, modification — can lead to several issues (such as inefficient design, bloated costs, etc.).