10 CloudHealth Alternatives and Competitors to Consider (2026)

CloudHealth alternatives range from FinOps platforms built around allocation and AI spend to tools that focus on commitments, observability, or hybrid-cloud operations. This guide compares 10 of them, starting with Finout, an enterprise-grade FinOps platform for cloud and AI spend, and covers what to check before you switch.

What Is CloudHealth by Broadcom?

CloudHealth by Broadcom, formerly VMware Tanzu CloudHealth, is a multi-cloud cost management platform used to monitor, allocate, and govern cloud spend across teams. The platform’s official product page now carries the CloudHealth by Broadcom name, and Broadcom’s fiscal 2025 Form 10-K confirms that Broadcom completed its VMware merger on November 22, 2023.

The platform consolidates data from public cloud providers like AWS, Microsoft Azure, and Google Cloud Platform, offering a central interface to manage cloud resources. By providing insights and analytics into cloud spending, CloudHealth enables companies to identify savings opportunities, enforce governance policies, and track cloud usage across teams.

Editor’s note: Updated in October 2026 with current CloudHealth ownership, pricing, and documented capabilities, plus a refreshed list of CloudHealth alternatives.

This is part of a series of articles about CloudHealth

Key Features of CloudHealth

CloudHealth covers the core cost management workflow: reporting, allocation, governance, and optimization. Its documented capabilities include:

• Multi-cloud support: Centralized cost management across AWS, Azure, and Google Cloud.
• Reporting, anomaly, and commitment views: Custom reports and dashboards, including FlexReports that can be embedded in dashboards; views that flag unexpected cost or usage changes and why; and a multi-cloud commitment discounts dashboard, per Broadcom’s guided walkthrough of the new CloudHealth experience.
• Optimization tracking: Cost optimization recommendations, plus a Realized Savings report that tracks the savings achieved by implementing them.
• Kubernetes cost reporting: A CloudHealth Collector agent deployed to each cluster gathers the metadata behind Kubernetes cost and usage reports.
• AI cost visibility: An AI & Tokenomics dashboard that brings AI-related costs across AWS, Azure, and GCP services into one view.
• AI assistants and integrations: Intelligent Assist for natural-language questions about FinOps data, documented in the same guided walkthrough, and, since Broadcom’s September 2026 update, an MCP integration with AI clients such as Cursor, GitHub Copilot, and Claude.

Why Consider CloudHealth Alternatives?

Teams usually start comparing CloudHealth alternatives when its pricing model, setup, or coverage stops matching how they manage spend. These are the documented points worth checking:

• Pricing is keyed to AWS spend tiers: CloudHealth’s AWS Marketplace listing prices 12-month contracts by monthly AWS spend, from $45,000 for up to $150K a month to $150,000 for up to $500K, with overage fees above the contracted amount. As spend grows past a tier, your CloudHealth cost moves with it.
• Kubernetes needs an agent in every cluster: Broadcom’s Kubernetes setup guide has you deploy the CloudHealth Collector agent to each cluster before container cost reports populate. That’s one more component to roll out and keep updated across your fleet.
• AI cost views center on the hyperscalers: Broadcom documents the AI & Tokenomics dashboard as a view of AI-related costs across AWS, Azure, and GCP services. If your AI spend also runs through direct provider contracts or developer tools, check how each alternative ingests those bills.
• Review volume is modest: CloudHealth holds a 4.1 out of 5 rating from about 20 reviews on G2, and some reviewers say the dashboards take time to learn.

None of this makes CloudHealth a poor choice. It means the evaluation should start with how you price, allocate, and report spend today.

What to Look For in a CloudHealth Alternative

The FinOps Foundation’s State of FinOps 2026 found that workload optimization and waste reduction remain the single top current priority for FinOps teams, and that 98% of respondents now manage AI spend, up from 31% in 2024. A replacement has to handle both: the optimization work you already run and the AI spend landing on the same bill.

• Allocation that works without perfect tags: If your tag coverage has gaps, look for rule-based allocation that maps untagged and shared costs to owners. Allocation is what makes showback, chargeback, and unit economics possible.
• Coverage across cloud, Kubernetes, SaaS, and AI: If your spend runs beyond one or two hyperscalers, confirm the platform brings Kubernetes, data platforms like Snowflake, and AI providers like OpenAI and Anthropic into the same cost model.
• A pricing model that fits how you grow: If your spend is rising fast, compare spend-tier pricing with overage, percentage-of-savings pricing, and flat-fee pricing before you sign.
• Budgets and forecasts tied to owners: If finance needs plan versus actual by team, look for forecasting built on the same allocation data, not a separate spreadsheet.
• Anomaly alerts that reach an owner: If cost spikes go unnoticed for weeks, prioritize alerts scoped to a team or service and delivered through Slack, email, or tickets.
• Time to value: If you’re replacing a tool before a renewal date, ask how long it takes to connect billing data and reach full allocation.

CloudHealth Alternatives at a Glance

The table compares the 10 CloudHealth alternatives in this guide by category, primary focus, a notable capability, and the key consideration to check before you buy.

Cloud Cost Management and FinOps Platforms

These platforms differ most in how they allocate untagged and shared costs, which clouds and AI providers they ingest, and how they charge.

1. Finout

Finout is an enterprise-grade FinOps platform for cloud and AI spend. Finout brings AWS, Azure, Google Cloud, Kubernetes, SaaS tools like Snowflake and Datadog, and AI providers like OpenAI and Anthropic into the patented MegaBill, then delivers 100% cost allocation to teams, products, and customers, including spend that native tags miss.

CloudHealth’s marketplace tiers add overage fees once you pass the contracted AWS spend. Finout’s pricing is fixed and transparent: a flat fee tied to a committed cloud and AI spend tier, with no surprise overages and no savings fees.

At Lyft, Finout improved cost attribution from 80% to more than 96% and cut anomaly detection time from weeks to days, according to the Lyft case study.

Key features:

• FinOps for AI: Brings Amazon Bedrock, Google Vertex AI, Azure OpenAI, OpenAI, and Anthropic costs into the MegaBill, with per-token, per-model, and per-team allocation.
• Billy: Finout’s AI FinOps assistant answers plain-English questions about team spend, anomalies, and commitment coverage with chart-backed answers from live Finout data.
• FinOps Agents: The Detection Agent continuously scans cloud, Kubernetes, AI, and SaaS for waste, drift, and anomalies, and the Investigation Agent traces each finding to its root cause, blast radius, and owner.
• MCP server: Connects Claude, Cursor, or any MCP-compatible client to the same governed data layer that powers Finout’s UI.
• AI-Powered Virtual Tags: Scan names, labels, namespaces, and accounts to propose allocation rules you approve, edit, or reject, keeping allocation in sync as teams and services change.
• Financial Plans: Budgets and forecasts built from historical and seasonal data, tracked by feature, team, or segment.
• Anomaly Detection: ML-powered detection of cost spikes, with Slack or email alerts at any level, from an individual to an environment.
• FinOps Dashboards: Drag-and-drop dashboards and reports sent through Slack, email, or Teams to specific teams based on Virtual Tag values.

Key consideration: Finout quotes pricing against your actual environment instead of publishing a list price. Expect a scoping conversation before you see a number.

2. Umbrella

Umbrella is an AI-based cloud cost management platform for enterprises and managed service providers that detects waste, tracks savings, and forecasts costs. Umbrella began as Anodot’s cloud cost product: Anodot launched Umbrella as an independent business unit in 2025, and Glassbox acquired Anodot in November 2025.

Key features:

• Multi-cloud and Kubernetes visibility: Connects AWS, Azure, and GCP, plus other cloud and SaaS sources through Bring Your Own Data (BYOD).
• Real-time anomaly alerts: Uses AI and machine learning to detect unusual spending patterns as they occur.
• Recommendations and savings tracking: Surfaces waste-reduction recommendations and tracks the impact of the ones you implement.
• CostGPT: A generative AI chatbot for cost analysis questions.
• MSP billing: Multi-account billing and management for MSPs serving many clients. 

Key consideration: Umbrella has operated as a standalone business unit since 2025, and Anodot, where it started, now belongs to Glassbox. Ask about roadmap and support commitments during evaluation.

3. CloudCheckr

Key features:

• Cost and usage visibility: Provides insights into current and historical cloud spend and resource consumption
• Automated cost optimization: Identifies waste and recommends rightsizing and commitment-discount purchases
• Governance and compliance checks: Includes controls to enforce policies and maintain compliance across cloud environments
• Custom reporting and billing: Supports tailored reports and billing views for internal teams or customers
• FinOps collaboration tools: Enables teams to share insights and manage cloud financial operations together

Key consideration: Coverage is limited to AWS and Azure. Flexera now points CloudCheckr customers to Flexera One FinOps for broader cloud insights.

4. IBM Cloudability

IBM Cloudability, formerly Apptio Cloudability, is an enterprise FinOps platform that provides visibility across cloud, AI, and SaaS spend and connects costs to ownership. Cloudability supports collaboration between finance, engineering, and product teams.

Key features:

• Multi-cloud, container, AI, and SaaS visibility: Resource-level analytics across cloud, AI, and SaaS spend, with container cost allocation.
• Anomaly detection and waste reduction: Notifications for budget breaches and spending anomalies, plus waste-reduction recommendations.
• Commitment management automation: Commitment purchasing and management through the Cloudability Savings Automation add-on.
• Unit economics: Overlays cloud costs with business metrics to track unit costs in near real time.
• Forecasting and budgeting: AI-backed bottom-up forecasting and top-down budgeting.

Key consideration: Automated commitment management is sold as a separate add-on, not as part of the core platform.

Learn more in our detailed guide to CloudHealth vs Cloudability

5. Ternary

Key features:

• Multi-cloud normalization: Ingests AWS, Azure, and GCP billing and maps it to a shared cost taxonomy.
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• Spend alerts: Real-time alerts on spend spikes, idle resources, and prepaid credit burn.
• Commitment modeling: Models savings plan and reserved instance coverage against actual utilization.
• AI cost attribution: Shows who is consuming AI and at what cost, down to the user and team.
• ERP and AI assistant access: Integrates with SAP, Oracle, and Workday, and exposes the ledger to Claude, ChatGPT, or an enterprise LLM through MCP.

Key consideration: Ternary positions itself as technology investment intelligence for Finance, with the ledger built around ERP structures.

6. nOps

nOps is an automated AI and cloud cost optimization platform built around commitment management for AWS, Azure, and GCP. nOps also allocates AI and cloud spend to the model, team, customer, and feature that drove it.

Key features:

• Automated commitment management: Rebalances commitments to maximize discounts, adapting hourly to usage.
• AI cost visibility and allocation: Allocates hourly AI spend across Bedrock, Cursor, Claude, OpenAI, and other sources.
• AI anomaly detection and forecasting: Hourly cost anomaly detection and forecasting for AI spend.

Key consideration: nOps pricing combines a fixed fee for Cost Visibility & Allocation with a percentage of realized savings for Autonomous Rate Optimization.

Cloud Management, Observability, and Optimization Platforms

These tools approach cost from another direction: resource automation, hybrid-cloud operations, observability, or IT asset management.

1. IBM Turbonomic

Key features:

• Full-stack visibility: Analyzes applications, containers, VMs, and infrastructure to map dependencies and usage
• Automated resource optimization: Continuously adjusts compute, storage, and network resources in real time
• Kubernetes optimization: Right-sizes containers and pods to reduce overprovisioning and cluster costs
• Capacity modeling: Uses resource data for right-sizing, capacity modeling, and policy-compliant scaling decisions
• Policy-driven automation: Enforces governance rules while optimizing performance and cost

Key consideration: Turbonomic executes actions in live environments. Decide up front which actions run automatically and which need approval.

2. CloudBolt

CloudBolt is a cloud management platform for governing, automating, and optimizing cloud and AI infrastructure. CloudBolt CMP handles hybrid-cloud governance and provisioning, while StormForge by CloudBolt handles Kubernetes rightsizing.

Key features:

• Hybrid cloud management: CloudBolt CMP supports more than 25 cloud providers and hypervisor platforms, plus Kubernetes.
• Provisioning and self-service: Role-based self-service provisioning with IT visibility and control.
• Cost allocation and chargeback: Kubernetes cost allocation that allocates shared costs and integrates with enterprise chargeback.
• Kubernetes rightsizing: Machine learning-based rightsizing of container resources through StormForge by CloudBolt.
• Workflow automation: Connects workflows and approvals in one orchestration layer, with 200 out-of-the-box integrations.

Key consideration: Kubernetes rightsizing comes through StormForge by CloudBolt, a separate product line from CloudBolt CMP.

3. Datadog Cloud Cost Management

Key features:

• Unified cost observability: Cloud, SaaS, and AI cost observability in the same platform engineers use for monitoring.
• Integrated cost visibility: Surfaces AWS, Azure, Google Cloud, OCI, SaaS, and AI costs in dashboards, Software Catalog, Resource Catalog, and Container Monitoring.
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• Cost monitors and anomaly alerts: Alerts teams to cost anomalies, with detection and root cause analysis.
• Collaboration: Notebooks add business context to optimization work for FinOps and Finance.

Key consideration: Cost views live inside the Datadog platform, alongside its dashboards, Software Catalog, and Container Monitoring.

4. Flexera One

Flexera One provides a single platform for IT asset management (ITAM), SaaS management, and FinOps, giving organizations a broader view of technology spend and risk.

Key features:

• Unified IT visibility: Tracks hardware, software, SaaS, and cloud resources in one platform
• Cost optimization: Rate and workload optimization across major cloud providers
• Business mapping of costs: Normalizes cost and usage data and maps it to your business to show cost and value drivers
• Compliance and risk management: Uses end-of-life, end-of-support, and vulnerability data, plus license analytics, to support compliance and audit defense
• Hybrid environment support: Covers cloud, on-premises, and SaaS environments

Key consideration: Flexera One’s scope extends to hardware, software licenses, and SaaS. If you only need cloud cost management, part of the platform will go unused.

What Usually Gets Missed When Replacing CloudHealth?

That’s an allocation problem before it’s a dashboard problem. AI charges arrive through hyperscaler bills, direct invoices from providers like OpenAI and Anthropic, and developer tools like Cursor, and each provider structures billing and model names differently. Tokens are also only part of the cost: orchestration, retrieval, evaluations, and the infrastructure around each model sit outside the token line. If you shortlist CloudHealth alternatives on cloud features alone, you can end up with clean cloud reporting and the same unanswered AI question. Ask each vendor to show AI spend from every source allocated to an owner, next to the cloud spend that supports it.

How to Choose the Right CloudHealth Alternative

Start from the decision the tool needs to support, then match it to the platform built around that decision.

• If you need to allocate cloud, Kubernetes, SaaS, and AI spend to owners without a tagging cleanup project first, prioritize Finout, because Virtual Tags deliver 100% cost allocation, including untagged spend, from one MegaBill.
• If commitment discounts on AWS, Azure, and GCP are your main savings lever, look at nOps, which rebalances commitments hourly against usage.
• If you run an MSP practice that needs multi-tenant billing, compare Umbrella’s MSP edition with CloudCheckr, keeping in mind that CloudCheckr covers AWS and Azure.
• If finance owns technology spend reporting and needs it mapped to the ERP, look at Ternary.
• If you want AI-backed forecasting inside an established enterprise FinOps suite, look at IBM Cloudability.
• If your engineers already work in Datadog, Datadog Cloud Cost Management keeps cost next to the performance data they use.
• If you manage private and public cloud together and need governed self-service provisioning, look at CloudBolt.
• If you want automated resizing and scaling based on application demand, look at IBM Turbonomic.
• If you need software license and hardware asset management alongside FinOps, look at Flexera One.

Related content:

• Read our guide on CloudHealth Pricing