Amnic vs Cast.AI

Learn how Amnic differs from CAST AI to understand which tool may best serve you at each stage of your cloud cost observability journey.

Amnic vs Cast.AI

Learn how Amnic differs from CAST AI to understand which tool may best serve you at each stage of your cloud cost observability journey.

Amnic vs Cast.AI

Learn how Amnic differs from CAST AI to understand which tool may best serve you at each stage of your cloud cost observability journey.

What is Amnic?

Amnic allows you to measure, analyze and optimize your cloud costs, continuously. Amnic’s cloud cost observability platform provides 360-degree instrumentation and observability of cloud workloads, driving leaner and more efficient cloud infrastructure. Amnic connects with every major cloud provider (AWS, GCP and Azure) while delivering a wide range of cost observability features including recommendations, anomaly detection, alerts, Kubernetes visibility, a deep-dive cost analyzer, reporting, and more.

Read on to learn how Amnic differs from CAST AI to provide a complete cloud cost observability solution that works seamlessly across DevOps, FinOps, and leadership teams:

Features & Benefits Comparison

Complete cloud provider support

Out-of-the-box, Amnic supports integration with and ingestion of cloud cost data from your entire AWS, Azure, GCP, and Kubernetes environments.

CAST AI connects to all major cloud providers but is focused on Kubernetes only, not all other costs associated with AWS, GCP, or Azure.

APIs, Webhooks, and SaaS tool integrations

Amnic offers dedicated integrations with Datadog, Slack, and MS Teams. However, with Amnic’s flexible architecture, you can also integrate with 40+ other SaaS tools via API and webhooks.

A swath of APIs and webhooks allow for manual integration with tools like PagerDuty or Slack. Cast AI does not appear to have any pre-built integrations with notification or other SaaS tools besides Terraform.

Kubernetes Support

Full support, connection to, and tracking of all managed Kubernetes service costs: Amazon EKS, Google Cloud GKE, and Azure AKS.

Supports Amazon EKS, Google Cloud GKE, and Azure AKS. As CAST AI’s sole focus is managing Kubernetes services and resources, this is supported.


Connects with AWS, Azure, and GCP, as well as providing recommendations through Amnic’s own recommendations engine.

Yes, but CAST AI only tracks Kubernetes-specific resources across AWS, GCP, and Azure but does offer rightsizing and recommendations to drive cloud cost improvements.

Cost Optimization

Enables teams to run lean cloud workloads by providing AI and ML-based prescriptive insights, without an agent, into storage, data transfer, and compute costs.

Offers workload optimization recommendations via the WorkloadOptimizationAPI but is of course only specific to Kubernetes environments.

Anomaly Detection

Amnic learns from your cloud providers to understand typical cost patterns and determine when your cloud costs may be an anomaly from the norm.

Provides both built-in pre-defined rules and the ability to set user-defined rules in the CAST AI Anomaly Rules Engine.

Alerts and Notifications

Amnic connects with Slack, MS Teams, and more to send alerts and notify the appropriate people when anomalous cloud spend is identified.

CAST AI currently only supports notifications and alerts via the CAST AI console as a webhook for Pagerduty or Slack.

Dashboards and Reports

Reports are saveable and can be shared with other users. Filterable, customizable bar charts, line graphs, and data tables are provided out-of-the-box.

Dashboards and reports show where cloud costs are being generated in a Kubernetes environment at the organization and the cluster level.

Cost Allocation and Unit Economics

Users can organize costs by tags, filters, and more to allocate costs to specific teams, Kubernetes clusters, applications, or other customizable criteria. Amnic reports and dashboards can help determine unit economics, but not directly in the UI.

Allows users to create allocation groups via the AllocationGroupAPI to assign costs of clusters based on team, application, or other criteria. Does not specifically track or report on granular unit economics.

Filtration and Customization

Amnic allows for granular filtration by resource, node, container, namespace, and more, alongside customization of reports and dashboards.

CAST AI allows you to filter and identify which workloads are resulting in higher cloud costs. Cluster and organizational level data is available but only works for Kubernetes environments.

Cost Analysis

Cost Analyzer helps users drill down into their costs, providing a nuanced picture of cloud costs at a resource, node, or namespace level, and gives users an understanding of all spend across granular datasets and timeframes.

CAST AI provides reports for Kubernetes clusters and can help you monitor cost trends over time. However, CAST AI only supports Kubernetes and analysis is not very customizable with current reporting capabilities.

Budgeting and Forecasting

Amnic’s cost analyzer and reporting allow FinOps teams to build more accurate budgets and forecasts (although these must be separately maintained outside of Amnic).

CAST AI does not provide financial forecasting or budgeting tools out of the box. Via cost monitoring, you can back into these numbers but it is not built out by default.

Tags and Categorization

Tags can be applied to nearly any data source within Amnic to help you break down datasets and categorize and report on cloud costs based on team, product line, cloud resource, and more.

CAST AI offers tagging at the cluster and organizational level to allow you to organize your spend by team, product line, resource, and more.

Amnic CoPilot (Generative AI assistant)

Amnic CoPilot is an AI assistant to help you navigate challenges with scaling, modernizing, and managing efficiency across Kubernetes (K8s)

CAST AI provides an API for users to register an LLM provider and connect it to CAST AI to help identify cost optimization opportunities. Requires manual configuration.


Kubecost has been built with just Kubernetes in mind. Amnic operates across all cloud providers and with complete capabilities for Docker, Kubernetes, or cloud environments, in general, to help you analyze, optimize, and rightsize infrastructure at all levels. With anomaly detection, recommendations, and a deep-dive cost analyzer view, engineers can determine exactly why cloud costs are surging and how to mitigate high cloud spend in the future. Amnic’s real-time alerting and notifications based on anomalies can reduce the amount of unnecessary cloud expenses and the time to resolve incidents, increasing the performance and efficiency of existing applications and services.

Filtration, categorization, and customizable dashboards can help FinOps, DevOps, and leadership teams collaborate, report on progress, and understand how to drive more operational efficiency in the future. With Amnic’s unified view of cloud costs, your team can create more accurate budgets, forecast future financial performance more efficiently, and organize costs by team, resource, or category to more appropriately measure your unit economics and allocation of spend.

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