Cost Optimization

Higher cloud usage doesn’t have to lead to high cloud costs

Centrally define cost management policy and automatically
ensure applications and the infrastructure on which they run
are always right sized.

Why optimize cloud costs?

Today’s economic reality means that every enterprise is experiencing budget cuts in IT. At the
same time, cloud costs are growing due to higher usage, duplicate tooling/licenses and 30% cloud
wastage on average.

Granular Cost Visibility & Chargebacks

Ensure precise budget allocations and minimize waste by attributing cloud costs to specific applications and teams using chargeback models.

Rafay’s cost visibility solution provides detailed metrics on Kubernetes resource consumption down to the namespace,  cluster, and pod levels. This granular visibility enables organizations to implement effective chargeback mechanisms,  ensuring each team is billed for exactly what they use.

Accurate
Billing

Enables better financial management and prevents overspending by accurately allocating costs to teams or projects.

Enhanced Accountability

Teams are more aware of their cloud usage, driving better resource optimization.

Optimize Kubernetes Resources for
Cost and Performance

Maximize resource utilization while minimizing cloud costs by dynamically scaling Kubernetes clusters.  

AWS Karpenter is integrated into Rafay’s platform to enable dynamic right-sizing of Kubernetes clusters. Karpenter automatically scales cluster size based on real-time application demand, ensuring that resources are neither over-provisioned nor under-utilized.

Cost
Reduction

Dynamically scale cluster size to ensure that resources are only used when needed, minimizing wastage.

Operational
Efficiency

Reduce manual intervention in cluster scaling, allowing teams to focus on more strategic tasks.

Align Application Resources for
Optimal Efficiency

Improve application performance and minimize resource waste by optimizing resource requests.  

Rafay’s proprietary tool continuously monitors resource consumption by applications. This tool adjusts the resource requests (CPU and memory) dynamically to ensure that applications are neither over-provisioned nor under-provisioned.

Performance Optimization

Ensure applications have just the right amount of resources for optimal performance.

Cost
Efficiency

Minimize cloud costs by preventing over-allocation of resources.

Automatically optimize cloud costs while you sleep

Continuously analyze spending and automatically
adjust resources, eliminating manual toil of cost management

Cost Optimization Suite

Customer Results

66%

Reduction in
infrastructure costs

45%

Reduction in tooling
and add-on licensing costs

Latest Blogs from the Kubernetes Current

Optimizing AI Workloads for Multi-Cloud Environments with Rafay and GPU PaaS

November 27, 2024 / by Mohan Atreya

Rafay’s platform enables you build a GPU PaaS for AI workloads so you can confidently operate machine learning models, generative AI, and neural networks at scale. It orchestrates your hybrid and multi-cloud computing resources, improves operational flexibility, and… Read More

Operationalizing AI: Solutions to Machine Learning Workflow Automation Challenges

November 15, 2024 / by Mohan Atreya

Machine learning (ML) has emerged as a transformative force, enabling organizations to derive critical insights, enhance customer experiences, and make data-driven predictions. However, operationalizing machine learning workflows presents significant challenges, especially for enterprises with complex, cloud-based infrastructures. Machine… Read More

Achieving Optimal AI Performance with Tuning-as-a-Service

November 12, 2024 / by Mohan Atreya

Tuning-as-a-Service (another TaaS but not to be confused with Training-as-a-service) is a cloud-based solution that optimizes AI models by automating the adjustment of hyperparameters to enhance model accuracy, efficiency, and overall performance. By leveraging advanced algorithms and scalable… Read More

Download the Inaugural Survey - The Pulse of Enterprise Platform Teams: Cloud, Kubernetes, and AI

Cost Optimization

Higher cloud usage doesn’t have to lead to high cloud costs

Why optimize cloud costs?