Kubernetes Allocation

Rightsize K8s costs with actionable suggestions

Rightsize K8s costs with actionable suggestions

Rightsize K8s costs with actionable suggestions

TRUSTED BY
  • Lambdatest
  • Jiffy.ai
  • Metamap
  • Nanonets
  • RagaAI
  • Osfin.ai
  • Pay3
  • axio
  • Zolve
  • 56 Secure
  • Humanify

    humanify

TRUSTED BY
  • Lambdatest
  • Jiffy.ai
  • Metamap
  • Nanonets
  • RagaAI
  • Osfin.ai
  • Pay3
  • axio
  • Zolve
  • 56 Secure
  • Humanify

    humanify

TRUSTED BY
  • Lambdatest
  • Jiffy.ai
  • Metamap
  • Nanonets
  • RagaAI
  • Osfin.ai
  • Pay3
  • axio
  • Zolve
  • 56 Secure
  • Humanify

    humanify

Is there a way to determine the ideal node groups and instance types for your cluster?

Engineering managers and DevOps teams struggle with effectively allocating resources within Kubernetes clusters. Over-provisioning leads to unnecessary costs, while under-provisioning risks application performance and reliability. Without clear visibility into resource usage and costs, optimizing Kubernetes clusters becomes a complex and inefficient task.

Case Study

How cloud cost observability delivered recommendations
that lowered cluster costs by 50% for Jiffy.ai

Amnic proved instrumental in addressing the challenge of escalating Kubernetes cluster costs effectively for Jiffy.ai. Cloud cost observability was not only able to drive substantial cost savings, but also created a system of being able to continuously monitor costs and performance of their cloud infrastructure. 

Features

Contextual Recommendations

Contextual Recommendations

Contextual Recommendations

Optimize based on cluster type, adopting aggressive or conservative strategies as needed.

Optimize based on cluster type, adopting aggressive or conservative strategies as needed.

Evidence-Based Insights

Evidence-Based Insights

Evidence-Based Insights

Transparent, data-driven recommendations provide actionable evidence for optimization decisions.

Transparent, data-driven recommendations provide actionable evidence for optimization decisions.

Multi-Cluster Visibility

Multi-Cluster Visibility

Multi-Cluster Visibility

Organization-wide insights enable comprehensive management across all Kubernetes environments.

Organization-wide insights enable comprehensive management across all Kubernetes environments.

Efficiency Scoring

Efficiency Scoring

Efficiency Scoring

Understand and improve cluster efficiency with clear, actionable metrics.

Understand and improve cluster efficiency with clear, actionable metrics.

Cost & Usage Breakdown

Cost & Usage Breakdown

Cost & Usage Breakdown

Detailed views of resource allocation help identify areas for cost savings and efficiency gains.

Detailed views of resource allocation help identify areas for cost savings and efficiency gains.

Case Study

How cloud cost observability delivered recommendations that lowered cluster costs by 50% for Jiffy.ai

How cloud cost observability delivered recommendations that lowered cluster costs by 50% for Jiffy.ai

Amnic proved instrumental in addressing the challenge of escalating Kubernetes cluster costs effectively for Jiffy.ai. Cloud cost observability was not only able to drive substantial cost savings, but also created a system of being able to continuously monitor costs and performance of their cloud infrastructure. 

Customer Testimonial 

Customer Testimonial

Sekhar Prakash

Co-founder, Cloud Engineering and Ops, JIFFY.ai

The Amnic platform played a pivotal role in bringing visibility and reducing our Kubernetes cluster costs by 50% by providing precise recommendations for right-sizing instances and pods. The team at Amnic is exceptionally responsive and showcases robust problem-solving abilities when it comes to the technical challenges in Cloud.

Blogs
Customers
Blogs
Customers
Build a culture of cloud cost optimization

Build a culture of

cloud cost observability

Build a culture of cloud cost optimization

Build a culture of

cloud cost observability