Overview

Discover how CloudZero helps engineering and finance get on the same team — and unlock cloud cost intelligence to power cloud profitability

Learn more Arrow Arrow

Explore CloudZero

Discover the power of cloud cost intelligence


Why Change Icon
Why Change?

Give your team a better cost platform

Services Icon
Services

Give engineering a cloud cost coach

About Icon
About

Learn more about CloudZero and who we are

Pricing Icon
Pricing

Learn more about CloudZero's pricing

Tour Icon
Tour

Take a customized tour of CloudZero

Features

Explore CloudZero by feature


Cost Anomaly Detection Icon
Cost Anomaly Detection

Build fast with cost guardrails

Budgeting Icon
Budgeting And Forecasting

Drive accountability and stay on budget

Discount Dashboard Icon
Discount Optimization Dashboard

Manage all your discounts in one place

Dimensions Icon
CloudZero Dimensions

Organize spend to match your business

By Use Case


Cost Per Customer
Cost Per Customer Analysis

Understand your cloud unit economics and measure cost per customer on AWS

Kubernetes Cost Analysis
Kubernetes Cost Analysis

Discover and monitor your real Kubernetes and container costs

Unit Cost Analysis
Unit Cost Analysis

Measure and monitor the unit metrics that matter most to your business

Cost Allocation
Tagging And Cost Allocation

Allocate cost and gain cost visibility even if your tagging isn’t perfect

SaaS COGS
SaaS COGS Measurement

Identify and measure your software COGS

Engineering Cost Awareness
Engineering Cost Awareness

Decentralize cost decisions to your engineering teams

Cloud Cost Optimization
Cloud Cost Optimization

Automatically identify wasted spend, then proactively build cost-effective infrastructure

Migration Cost Monitoring
Migration Cost Monitoring

Monitor your AWS cost and track progress in real-time as you move to the cloud

By Role


All Your Cloud Spend, In One View

CloudZero ingests data from AWS, GCP, Azure, Snowflake, Kubernetes, and more

View all cost sources Arrow Arrow

Learn

Discover the best cloud cost intelligence resources


Resources Icon Resources

Browse helpful webinars, ebooks, and other useful resources

Blog Icon Blog

Discover the best cloud cost intelligence content

Case Study Icon Case Studies

Learn how we’ve helped happy customers like SeatGeek, Drift, Remitly, and more

Events Icon Events

Check out our best upcoming and past events

Cost Assessment Icon Free Cloud Cost Assessment

Gauge the health and maturity level of your cost management and optimization efforts

Featured

CloudZero Advisor

Compare pricing and get advice on AWS services including EC2, RDS, ElastiCache, and more

Learn more Arrow Arrow

How SeatGeek Measures Cost Per Customer

Discover how SeatGeek decoded its AWS bill and measures cost per customer

Read customer story orangearrow arrow-right

How Skyscanner Creates A Cost-Aware Culture

Learn how Skyscanner decentralized cloud cost to their engineering teams

Read customer story orangearrow arrow-right

How Malwarebytes Measures Cost Per Customer

Learn how Malwarebytes measures cloud cost per product

Read customer story orangearrow arrow-right

How Remitly Shifts Cloud Costs Left

Learn how Remitly built an engineering culture of cost autonomy

Read customer story orangearrow arrow-right

How Ninjacat Combines AWS And Snowflake Spend

Discover how Ninjacat uses cloud cost intelligence to inform business decisions

Read customer story orangearrow arrow-right

How Smartbear Uses Cloud Cost To Inform GTM Strategies

Learn Smartbear optimized engineering use and inform go-to-market strategies

Read customer story orangearrow arrow-right
arrow-left arrow-right
View all customer stories

Kubecost Vs. Cast.ai: Battle Of The Kubernetes Cost Tools

Kubecost and CAST AI are two popular Kubernetes cost tools. But how do they differ, and are one of these platforms right for your K8s environment?

Is your current cloud cost tool giving you the cost intelligence you need?  Most tools are manual, clunky, and inexact. Discover how CloudZero takes a new  approach to organizing your cloud spend.Click here to learn more.

Kubecost and Cast AI promise real-time Kubernetes cost monitoring. Both deliver this to a good extent. For example, Kubecost provides cost data from within and outside a K8s cluster. It also shares the data in a granular format, such as cost by Kubernetes concepts like namespaces, pods, and custom labels.

Cast.ai offers several similar capabilities, including cost savings recommendations, and is currently available for AWS, Google Cloud, Azure, and on-prem Kubernetes. Despite these similarities, Cast AI and Kubecost differ in several key ways, as we will discuss below.

Table of Contents

First, a little background.

What Does Cast.ai Do?

CAST AI is a Kubernetes cost-monitoring platform. It continuously collects, analyses, and reports Kubernetes costs in real-time within your K8s environment. This way, you can track and optimize cost changes as they occur.

Dashboard

CAST AI dashboard

The CAST AI cost monitoring solution includes the following features:

  • Real-time K8s cluster cost monitoring - Use universal metrics to capture and analyze the cost of your Kubernetes operations across multiple clouds (AWS, GCP, Azure, and on-prem K8s). It also includes real-time alerting so you can tell when you are hitting certain consumption thresholds.
  • Granular Kubernetes cost allocation - Break down your Kubernetes costs by native Kubernetes concepts like cluster, pod, namespace, workload, and deployment. Cost allocation works per node and cluster basis. By seeing the values of your requested, allocatable, and overhead resources, you can better understand your CPU and memory provisioning costs.
  • Automated cost saving recommendations - Automatically apply CAST AI’s K8s cost optimization recommendations as soon as they are available to ensure around-the-clock efficiency (Instant rebalancing).
  • Real-time autoscaling for rebalancing - Automate lowering your Kubernetes costs with CAST AI-powered autoscaling, bin packing, rightsizing, and spot instance automation.
  • Automatic cluster rightsizing - Automatically add or remove resources, such as nodes, to meet your use case requirements at the best price-performance ratio.

Here’s how Kubecost compares.

What Does Kubecost Do?

Kubecost continuously measures and allocates both in-cluster and out-of-cluster Kubernetes costs in real-time.

The platform tracks your K8s costs data across the major cloud providers; Google Cloud (Google Kubernetes Engine), AWS (Amazon EKS), Microsoft Azure (Azure Kubernetes Service), and on-premises.

Dashboard

Kubecost dashboard

Kubecost features include the following:

  • Cost allocation - Allocate K8s costs using Kubernetes concepts, like cluster, namespace, service, label, deployment, pod, environment, team, product, or a custom label. Use a single API endpoint to view costs across multiple clusters in one place.
  • Real-time Kubernetes cost monitoring - Bring together and view your in-cluster costs (CPU, RAM, network, storage, etc) and out-of-cluster costs (infrastructure and services) within a single platform.
  • K8s cost optimization recommendations - Get cluster-level insights tailored to your usage patterns and environment to prevent overprovisioning (waste) or under-provisioning (performance degradation).
  • Customizable alerts and governance - Access real-time warnings via email or Slack about suspicious spend patterns, potential budget overruns, and non-efficient Kubernetes tenants.

So, what's the best Kubernetes cost monitoring tool; Kubecost or CAST AI?

What Are The Differences Between CAST AI And Kubecost?

The following are a few areas where CAST AI and Kubecost differ in monitoring and optimizing Kubernetes costs.

1. Cost allocation and tagging

CAST AI and Kubecost allocate costs based on Kubernetes concepts such as namespace, deployment, service, and workload. You can also use either tool to organize cost data at the microservice level. This provides detailed information for processing chargebacks and showbacks.

To tag resources, Kubecost and CAST AI use the underlying cloud provider’s resource tagging mechanism. For example, if you are using Amazon Web Services, either tool will take advantage of AWS tagging to allocate out-of-cluster costs to concepts like deployment, pod, and namespace.

In either case, you can manually add custom cost allocation tags if you prefer user-defined cost allocation tags.

2. Kubernetes cost visibility

They both support real-time K8s cost visibility. With CAST AI, you can view and manage multi-cloud infrastructure costs in one place. The platform supports universal metrics that you can use across any cloud provider.

With Kubecost, you can use a single API endpoint to view (not directly manage or optimize) cost insights across multiple clusters and cloud environments.

There’s more. Kubecost supports multi-tenant cost monitoring. That means you can, for example;

  • Run multiple Amazon EKS clusters in separate, dedicated AWS accounts (hard multi-tenancy)
  • Run several groups of nodes in a shared Amazon EKS cluster (soft multi-tenancy)

Kubecost also enables you to connect real-time in-cluster costs (such as CPU, RAM, storage, network, etc.) and out-of-cluster spend from cloud services across AWS, Google Cloud, and Microsoft Azure.

You can, for example, collect cost data on your tagged RDS instances, Amazon S3 buckets, or BigQuery warehouses. You can expect context-aware, cluster-level reporting.

​CAST AI emphasizes detailed CPU costs in the Savings estimator. This displays your potential savings from deployments on Spot Instances. As of this writing, CAST AI is yet to enroll other dimensions, such as control plane, egress, network, and storage.

3. FinOps, engineering accountability, and financial reporting

Both Kubecost and CAST AI support automatic alerts for anomalous cost trends. In addition to Slack, you can receive the alerts via email or another incident reporting tool, such as PagerDuty or ServiceNow.

CAST AI limits allocating organizational costs by cluster and pod. With Kubecost, you can go further with cost allocation concepts such as project, team, product, environment, and more.

Now, while each has a different level of engineering event correlation, neither offers a dedicated FinOps resource or a shared Slack channel to chat with resources. It may also be challenging to correlate your costs to dimensions such as cost per customer, and cost per internal software feature vs. customer-facing software (product feature).

In addition, neither CAST AI nor Kubecost combines all cloud costs in a single place, such as displaying your Kubernetes costs alongside AWS (cloud provider), Snowflake (data cloud), or New Relic (monitoring) costs. All you'll be able to do is analyze and optimize Kubernetes costs.

Speaking of optimizing Kubernetes costs.

4. Kubernetes cost optimization and reducing waste

Kubecost provides cost-saving recommendations tailored to your Kubernetes' environment. But it leaves you to decide if you want to implement its recommendations or not.

If you do, you have to apply them manually, unlike CAST AI, which applies its optimization recommendations automatically and around the clock.

Kubernetes Cost Optimization in Cast.ai

Automated Kubernetes cost optimization in CAST AI

Also, CAST AI offers several ways to optimize costs and reduce resource waste in Kubernetes environments:

  • Horizontal pod autoscaling - Automatically increase or decrease your pod replica count as demand increases or decreases. It uses business metrics to calculate the number of pod instances needed. CAST AI supports node autoscaling.
  • AI-driven instance selection - CAST AI selects the most cost-effective instance types to meet your performance requirements. CAST AI can also generate a mix of different instance types adapted to your performance and cost requirements.
  • Automatic bin packing - Instead of distributing workloads evenly among clusters, CAST AI modifies the default pod scheduling strategy and applies automated bin packing to generate the biggest savings based on user preferences.
  • Cluster scheduling - Automatically pause and resume your clusters as needed, so you don't have to pay for resources your team isn't using.

One more thing. CAST AI provides Spot Instance automation. This feature automatically replaces interrupted Spot Instances to prevent downtime. The service ensures high availability by continuously scanning for replacement instances and spinning them in a fraction of a second.

Kubecost does not currently offer this Spot instance orchestration. Instead, it offers Spot Readiness Checklist, a way to check if your Kubernetes workloads are spot-ready based on six parameters; Controller type, Local storage, Rolling update strategy, Replica count, Controller pod distribution budget, and Manual annotation overrides.

Best Kubernetes Cost Optimization Platform: CloudZero Vs. Cast.ai Vs. Kubecost

Here’s a table to compare the best Kubernetes cost monitoring and optimization platform.

 

CloudZero

Kubecost

CAST AI

Data Quality & Scale

     

Cost data reflected in real-time

Yes

Yes

Yes

Configuration changes affected immediately

Yes

Yes

Yes

Infrastructure Support

     

Supports multi-service (e.g. Snowflake, Databricks, New Relic, MongoDB, etc)

Fully

Limited

No

Supports multicloud (AWS, Azure, GCP, and on-prem K8s)

Yes

Yes

Yes

Consolidates K8s and non-Kubernetes costs

Yes

No (Kubernetes only)

No (Kubernetes only)

Ability to Organize and Track Costs

     

Tag-based cost allocation

Yes

Yes

Yes

Code-driven cost allocation

Yes

No

No

Splitting shared costs (proportionally)

Yes

Yes

No

Splitting shared costs (telemetry driven allocation)

Yes

Yes

No

Average cost per customer metric

Yes

Yes

No

Cost per individual customer (driven by telemetry)

Yes 

No

No

Engineering Friendliness

     

Slack integration

Yes

Yes

Yes

Automatic cost anomaly detection and alerts

Yes

Yes

Yes

Cost debugging workflow (drill down into cost)

Yes

Yes

Yes

Engineering event correlation (e.g. GitHub)

Yes

Limited

Limited

Services

     

Dedicated FinOps Resource

Yes

No

No

Shared Slack Channel to chat with resource

Yes

No

No

Cost Optimization

     

Horizontal pod autoscaling

Yes (via ProsperOps)

No

Yes

Automatic instance selection

Yes (via ProsperOps)

No

Yes

Automated Spot instance orchestration

Yes (via Xosphere)

No

Yes

Pod and Node autoscaling

Yes (via ProsperOps)

No

Yes

Cluster auto-scheduling 

Yes (via ProsperOps)

No

Yes

Pricing

Steady and predictable tiered pricing

Tiered, consumption based

Tiered, consumption based

When To Use CloudZero

Use CloudZero if you want to:

  • Boost cost visibility across your entire cloud infrastructure, containerized and non-containerized.
  • Consolidate or compare cloud cost across multiple providers (AWS, Azure, Google Cloud, etc.) and services (Snowflake, Databricks, MongoDB, New Relic, specific AWS services, etc.).
  • Get detailed insights into cloud costs across business dimensions, such as cost per customer, per product, per team, per feature, per deployment, per environment, and more.
  • Investigate Kubernetes cost using any K8s native concept, such as cost per pod, cluster, namespace, service, deployment, etc.
  • Accurately capture, analyze, and allocate the costs of tagged, untagged, untaggable, and multi-tenant resources within a single platform.

CloudZero also provides budgeting tools, forecasting tools, and the ability to manage public cloud discounts in one place.

Schedule a demo today to see how it all works together — without adding a layer of complexity like other tools do.

STAY IN THE LOOP


Join thousands of engineers who already receive the best AWS and cloud cost intelligence content.