Cloudride integrates ScaleOps to overcome the challenges of scaling and optimizing cloud-native workloads

Cloudride
4 min readMay 29

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In the ever-changing world of cloud-native workloads, organizations of all shapes and sizes strive to optimize their Kubernetes resources. All this while saving costs without compromising their service level agreements (SLAs).

We’ll delve into the innovative ScaleOps platform. This automatic cloud-native resource management platform provides DevOps teams with the ability to seamlessly optimize cloud-native resources, empowering organizations to achieve up to 80% cost savings and enhance workload performance and availability, while providing a hands-free experience for DevOps teams and freeing them from broken repeated manual work. The ScaleOps platform integrates with Karpenter to enhance its resource optimization capabilities, allowing organizations to optimize their cost and performance.

At Cloudride, we are continuously innovating and helping clients to seamlessly integrate cutting-edge technological solutions to elevate their cloud-native operational efficiency.

AWS Cluster Autoscaler?

Cluster Autoscaler is an integral part of the Kubernetes ecosystem, which was developed to support the ideal cluster size in tandem with the changing pod requests. Its primary role is to determine pending pods that cannot be scheduled because of resource constraints and then take proper measures to address them.

You don’t have to worry about pods sitting idle and twiddling their virtual thumbs. When these nodes feel underappreciated and underutilized, the autoscaler evolves into a master of resource optimization. It skillfully rearranges the workload, guaranteeing every pod finds its perfect spot and no precious resources go to waste.

However, Karpenter and ScaleOps take things a little further in terms of efficiency. Karpenter enables quicker node provisioning while eliminating the need for configurations. ScaleOps optimizes the containers’ compute resources in real-time and scales Kubernetes pods based on demand.

What is Karpenter?

This open-source autoscaler is designed to optimize cluster resource usage and slash costs in different clouds, including AWS. Karpenter is a custom controller, working behind the scenes to ensure your Kubernetes cluster perfectly harmonizes with your workload.

Using its advanced algorithms and the Kubernetes Horizontal Pod Autoscaler (HPA) and Cluster Autoscaler, Karpenter becomes a dynamic force for:

What is ScaleOps?

ScaleOps automatically adjust computing resources in real-time to enable companies to see significant cost savings of up to 80%, while providing a hands-free experience for scaling Kubernetes workloads, and freeing engineering teams from worrying about their cloud resources.

It intelligently analyzes your container’s needs and scales your pods dynamically and automatically to achieve the ever-growing demands of the real-time cloud.

The installation takes 2 min and immediately provides visibility to the potential value DevOps team can achieve from the automation using read-only permissions.

ScaleOps, in collaboration with Karpenter, empowers DevOps engineers to overcome the challenges of scaling and optimizing cloud-native workloads.

ScaleOps and Karpenter

In the ongoing expenses of cloud workloads, satisfying business objectives is the ultimate mission of any DevOps team.

The powerful combination of ScaleOps and Karpenter ensures smoother workload changes and optimized performance and costs. ScaleOps will help you update compute resource requests and ensure resource utilization matches demand in real-time. Karpenter will focus on eliminating waste by reducing the gap between resource capacity and recommendations. Karpenter enables faster node provisioning, accelerating response times. ScaleOps continuously optimizes HPA triggers to match SLAs, enforcing an optimal replica number for running workloads.

Automated scaling and provisioning: ScaleOps simplifies managing clusters and can help you significantly reduce the number of nodes per cluster. Karpenter tracks resource requests and needs and automatically provisions nodes. This combination of functions is highly recommendable for fluctuating workloads.

Cost cutting: ScaleOps gives insights into your cluster resource usage and patterns and identifies areas for automatic optimization. Karpenter quickly selects instance types and sizes in ways that minimize infrastructure and costs.

Better scheduling: Creating constraints is possible with Karpenter, including topology spread, tolerations, and node taints. ScaleOps helps you manage the constraints to control where pods go in your cluster for better performance and resource usage.

Cloudride to Success

At Cloudride, our team of professionals and experts have a profound understanding of the complex requirements for performance and cost optimization on AWS and other clouds. This knowledge and wealth of experience enable us to offer custom-made solutions, support, and integration for powerful cloud integrations like ScaleOps and Karpenter.

Starting with the initial assessment and crafting of the perfect architecture, all the way to the seamless deployment, monitoring, and optimization, we can help your cloud-native environment to hit its maximum potential in performance as well as cost efficiency.

Conclusion

In this age of rapid technological advancements, an organization’s ability to scale infrastructure with ease is critical. ScaleOps and Karpenter deliver robust solutions to this challenge.

Businesses now have the platform to automate resource allocation, maximize cost efficiency, and improve performance. The best cloud solution integrations can help you unleash your cloud-native initiatives with exceptional confidence, and at Cloudride, we have your back.

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Cloudride

Cloudride LTD, a professional services company for public cloud platform, specialized on MS-AZURE& AWS in order to provide solutions tailored to your needs