The rapid dynamics of K8s require the ability to rapidly scale up infrastructure and then tear it down just as quickly when you’re done processing data. Any unnecessary bottleneck that you experience throughout this process can be stressful to the team managing your Kubernetes environments. Your autoscaler’s controller could result in such bottlenecks – unless it’s well-architected.

Spot by NetApp is once again thrilled to be named a leader and outperformer in FinOps by tech industry analyst firm GigaOm – for the third year in a row!

In the world of Kubernetes, scale-down operations are crucial for optimizing resource usage and reducing costs. The scale-down process involves identifying underutilized nodes and efficiently bin-packing the pods to minimize the number of nodes required.

As a recovering practitioner, one of the things I was always less than thrilled to do was patching. I dreaded having to run updates, ensure everything was configured correctly, and finding windows of time to reboot without knocking an application offline. Just like your cloud workloads — everything changes when it has to be done at scale. Kubernetes has always been built around the DevOps concepts of rapid development, delivery, and iteration.

One significant challenge that every dynamic, fast-paced business in the cloud faces is efficiently managing their clusters’ workloads while minimizing unnecessary expenses. But it’s not just overages that these businesses must worry about. Especially common is the underutilization of resources, which can lead to unnecessary costs and inefficiencies.

Did you know that companies typically waste as much as 35% of their budgets on unused compute resources? And, oftentimes, these idle resources are commitment waste — reserved commitments purchased at a discount but with the financial lock-in of one or three years. Commitments, such as Azure Compute Reservations (VM RIs), offer significant savings when compared to on-demand.

Developing a successful Azure cloud operations (CloudOps) practice is the key to unlocking the full benefits of Microsoft’s Azure cloud platform. But Azure users often struggle to take full advantage of Azure’s benefits once they’ve made the move to the cloud. While it might be easy to build infrastructure inside of Azure and start spending money, ensuring your cloud infrastructure continues to support your organization’s business objectives as you scale is hard work.

Managing application updates in production and ensuring the reliability of software releases in Kubernetes environments can be challenging. Small changes can sometimes lead to unforeseen issues in production. These unexpected problems, combined with the lack of scalability and the high costs associated with managing complex solutions, can be daunting.

Last week in Paris, at KubeCon EU 2024, platform engineering was the talk of the event. The topic had a full-day co-located event and also a dedicated track during KubeCon itself. Here’s what I’ve learned from sitting in keynote rooms and then standing at the Spot and NetApp booth till my knees hurt. (Spoiler: It was well worth it.)

Many businesses operating in the cloud are looking for ways to reduce cloud costs, and enterprises using Google Cloud are no exception. One of the pricing models Google Cloud is offering to users is Committed Use Discounts (CUDs). This pricing model allows customers to commit either to a minimum amount of resource usage or to a minimum amount of spend for a specified term of one or three years. In return for this commitment, customers receive significant discounts compared to on-demand pricing.