Cloud Intelligence™ vs. CloudHealth

Yes. CloudHealth is an enterprise cloud cost reporting and governance platform — Perspectives for allocation, FlexReports for analysis, budgets, anomaly detection, and a policy engine for hygiene automation. Cloud Intelligence™ covers that visibility and governance ground, then goes further into execution: infrastructure remediation (CloudFlow), autonomous workload optimization (PerfectScale for Kubernetes and Snowflake), commitment automation across AWS and GCP (PerfectScale for Commitments), runtime cost attribution without tagging, and Forward Deployed Engineers included in the platform.

Execution and pricing. CloudHealth reports, governs, and recommends; outside of Convertible RI exchanges and hygiene policy actions, realizing savings is your engineers' work — and the platform fee is a percentage of your tracked cloud spend, so it grows with your bill. DoiT executes across workloads, commitments, and infrastructure at flat pricing that doesn't scale with spend.

CloudHealth Technologies was acquired by VMware in 2018, became VMware Tanzu CloudHealth, and moved to Broadcom with the VMware acquisition in late 2023. In May 2024, Broadcom made Arrow Electronics the exclusive global provider — Arrow handles sales, marketing, and technical support, while Broadcom retains R&D. In June 2025 Broadcom shipped a refreshed user experience with AI features (Intelligent Assist, Smart Summary). The product is actively maintained; the go-to-market and ownership have changed hands three times in six years, which is worth weighing in any long-term platform bet.

Partially, on AWS only. Savings Automator automates exchanging and modifying AWS Convertible Reserved Instances to maintain coverage. New Savings Plan purchases are recommendation-driven: the beta recommendations generate only when total commitment coverage is below 50%, default to one-year terms, and purchases route through authorizer/approver workflows. Azure and GCP commitments get analysis and recommendations, not automation. PerfectScale for Commitments ladders Savings Plans, Database Savings Plans, and Compute Engine CUDs across AWS and GCP — autonomous or approval-gated, validated continuously against hourly usage — at flat pricing.

CloudHealth typically charges 2.2–2.5% of the cloud spend it tracks, on 12-to-36-month contracts, with overage fees around $0.03 per dollar of spend above your contracted cap. The fee scales with your cloud bill regardless of savings delivered. DoiT is flat: platform pricing that doesn't scale with spend, or bundled with multi-cloud procurement — DoiT resells AWS, GCP, and Azure at no markup, and many teams find consolidation effectively pays for the platform.

CloudHealth allocates Kubernetes cost. Its Helm-based collector rolls container spend up by cluster, namespace, or workload, split by requests or actual usage. It does not execute container rightsizing, GPU utilization is not a first-class dimension, and its anomaly detection does not cover Kubernetes workloads. PerfectScale for Kubernetes executes autonomous, workload-aware rightsizing at pod and container level with stability-first guardrails. Customers typically see 30–50% K8s cost reductions.

Within limits. Grant CloudHealth its Automated Actions IAM role and its policy engine can stop or start instances, delete unattached volumes, take snapshots, and schedule environments — useful hygiene automation with human-in-the-loop approvals. It is a fixed set of provider primitives, though: no historical simulation before enabling a policy, and no general execution path for optimization changes. DoiT CloudFlow is a full execution layer — visual plus code-extensible, 40+ production templates, rollback safety — that turns Composer findings into executed changes.

With DoiT, yes. Runtime cost attribution in Cloud Intelligence™ uses kernel-level telemetry (eBPF) to observe actual traffic and resource consumption, mapping every dollar to the customer, feature, team, or AI agent that drove it — no tagging required. CloudHealth's Perspectives are the classic alternative: rule-based groupings over tags and metadata. They work where metadata is disciplined, but shared clusters, shared GPUs, and multi-tenant endpoints stay opaque because the metadata doesn't carry the answer.

They're largely outside CloudHealth's frame: its native cost sources are cloud providers (AWS, Azure, GCP, Alibaba), Kubernetes, and VMware/on-prem estates. Snowflake, Databricks, OpenAI, and Anthropic spend can only be represented as custom line items on the bill. DoiT ingests them natively — and goes past visibility: PerfectScale for Snowflake automates warehouse rightsizing, idle suspension, and query efficiency; GenAI Intelligence tracks 9 AI providers and custom models per-customer, per-feature, per-unit.

Yes — the 2025 CloudHealth refresh added Intelligent Assist, a GenAI copilot that answers natural-language questions about cost data and builds reports, plus Smart Summary for explaining spend changes. DoiT's FinOps AI covers the same conversational ground and adds an MCP server, so you can query your cost data from Claude, ChatGPT, or any LLM client. The bigger difference is what sits underneath: FinOps AI is wired into execution engines that can run the fix, not just explain the bill.

Large enterprises with significant VMware or on-prem estates alongside public cloud, organizations whose finance teams have a decade of institutional knowledge in Perspectives, FlexOrgs, and FlexReports, and MSPs built on the CloudHealth partner platform. If your FinOps practice is primarily standardized reporting, governance policy, and chargeback across a hybrid estate — and engineering owns implementation — CloudHealth remains a credible incumbent. The fit weakens when you need autonomous optimization, multi-cloud commitment automation, data platform or AI cost management, per-customer attribution on shared infrastructure, or pricing that does not scale with your cloud bill.