Kubernetes Recommendations

Rightsize K8s costs with actionable suggestions

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Rightsize K8s costs with actionable suggestions

Get started

Request a demo

TRUSTED BY

humanify

TRUSTED BY

humanify

TRUSTED BY

humanify

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

Engineering managers and DevOps teams often face challenges in running Kubernetes (K8s) clusters efficiently. Balancing between cost optimization and operational reliability requires clear, actionable insights tailored to the specific context of their clusters. Without these, teams struggle to manage budgets, understand cluster efficiency, and communicate effectively with stakeholders.

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

Context-Driven Recommendations

Tailored insights based on cluster type (production or non-production), allowing for customized strategies.

Container, Node, PVC Recommendations

Provides actionable recommendations at multiple levels of the Kubernetes stack, enabling granular optimization.

Transparent, Evidence-Based Insights

Recommendations are backed by usage data, providing clear and justifiable actions for optimization.

Unified Cluster Cost View

Delivers a comprehensive view of cluster costs across AWS, Azure, and GCP in a single platform, simplifying cost management.

Efficiency Score

A proprietary score that evaluates how efficiently your clusters are running, helping to identify areas for improvement.

Comprehensive Reporting

Generate detailed reports with recommendations that can be shared with stakeholders, facilitating informed decision-making across the organization.

Case Study

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

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.