Every major cloud provider now sells some version of "your data is encrypted even while it's running," but the implementations differ enough that a lift-and-shift assumption can quietly break your threat model. Confidential virtual machines encrypt memory and isolate compute at the hardware level using technologies like AMD SEV-SNP and Intel TDX, so that even a compromised hypervisor, a malicious cloud insider, or a co-tenant workload can't read your data in use. That sounds like a single category, but Azure confidential VM offerings, AWS Nitro Enclaves, and GCP confidential compute take genuinely different architectural paths to get there. For teams building software supply chain security into infrastructure -- especially anyone signing artifacts, running key management, or processing regulated data -- picking the wrong flavor can mean re-architecting later. This guide compares the real options on the criteria that matter for production workloads, not marketing slides.
What "Confidential Virtual Machines" Actually Means
Before comparing vendors, it's worth being precise about scope. Confidential virtual machines are a subset of confidential computing that protects an entire VM -- OS, application, memory -- inside a hardware-based trusted execution environment (TEE), as opposed to enclave models that isolate only a portion of an application's memory. The distinction matters because it changes your migration effort: a full confidential VM can often run an existing OS image with minimal changes, while an enclave-based model typically requires re-partitioning your application into trusted and untrusted components. Both approaches rely on remote attestation -- a cryptographic proof that your workload is running in a genuine, unmodified TEE -- which is the feature you should scrutinize most closely, since it's what lets a relying party (a customer, an auditor, a key management service) actually trust the environment rather than take the provider's word for it.
Evaluation Criteria for Confidential Computing Platforms
When comparing offerings, we weighted the following:
Hardware Root of Trust and CPU Generation
Most confidential VM offerings today are built on AMD SEV-SNP or Intel TDX, with a shrinking number still relying on the weaker AMD SEV or SEV-ES without the "SNP" (Secure Nested Paging) integrity protections. SNP and TDX both defend against a broader set of hypervisor-level attacks, including memory remapping and replay attacks, than earlier SEV. If a provider doesn't specify which generation you're getting, ask -- the gap between SEV and SEV-SNP is not cosmetic.
Attestation Depth and Portability
A confidential VM is only as trustworthy as its attestation story. Look for whether attestation reports are verifiable independently of the cloud provider (open specifications, third-party verifiers) or whether you're locked into a proprietary attestation service. Portable, standards-based attestation (leaning on specs from the Confidential Computing Consortium) makes it far easier to build cross-cloud trust pipelines or satisfy an auditor who doesn't want to trust a vendor's black box.
Performance Overhead
Memory encryption and integrity checking impose real overhead, typically single-digit to low-double-digit percentages depending on workload type, with memory-bandwidth-heavy applications hit hardest. Benchmarks vary widely by provider and instance family, so validate with your own workload rather than trusting vendor-published numbers alone.
Ecosystem Maturity and Managed Service Integration
Does the confidential VM tier integrate with the provider's key management service, container orchestration, and CI/CD tooling, or is it an isolated instance type you have to bolt everything onto yourself? This matters enormously for software supply chain use cases like confidential build pipelines or hardware-backed signing keys.
Compliance and Attestation Documentation
For regulated workloads, check whether the provider publishes SOC 2, FedRAMP, or ISO mappings specific to the confidential computing product, not just the general cloud platform.
The Roundup: Confidential VM and Confidential Computing Offerings
Microsoft Azure Confidential VMs
Azure has arguably the broadest confidential VM lineup, spanning AMD SEV-SNP-based DCasv5/ECasv5 series and Intel TDX-based DCesv5/ECesv5 series, plus confidential AKS nodes for containerized workloads. Strengths: deep integration with Azure Key Vault's managed HSM, a mature Azure Attestation service, and support for "confidential OS disk encryption" so the boot volume itself is protected under the same trust boundary. Limitations: the confidential SKUs carry a real price premium over standard VMs, regional availability lags behind general-purpose instance types, and some confidential features (like confidential containers via AKS) are newer and less battle-tested than the core VM offering.
AWS Nitro Enclaves
AWS takes a different architectural stance. Rather than offering a hardware-TEE confidential VM in the SEV-SNP/TDX sense as the default confidential path, AWS's flagship isolation product is Nitro Enclaves -- an enclave carved out of an EC2 instance's own resources, with no persistent storage, no external networking, and cryptographic attestation via the Nitro hypervisor. Strengths: the Nitro security model (custom silicon offloading virtualization functions from the host) has a strong independent security track record, and enclaves integrate cleanly with AWS KMS for attestation-gated key release. Limitations: Nitro Enclaves require re-architecting an application into a parent-instance/enclave split rather than running an unmodified VM, which is a heavier lift than a true confidential VM; AWS has separately added AMD SEV-SNP-based confidential VM support on select instance types, but it is less central to their confidential computing story than Nitro Enclaves and has narrower availability.
Google Cloud Confidential VMs / Confidential Compute
GCP confidential compute was among the first mainstream confidential VM products, launching with AMD SEV support and expanding to SEV-SNP and Intel TDX on newer instance families (N2D, C3). Strengths: confidential VMs can typically be enabled with a single flag on existing machine types with minimal re-architecture, and Google's Confidential Space product extends the model to multi-party computation scenarios where mutually distrusting parties can jointly process data with attestation-verified code. Limitations: TDX-based confidential VMs are newer and available on a narrower set of machine types than the SEV-SNP line, and some advanced features (like confidential GPUs) are still rolling out region by region.
Intel and the TDX/SGX Ecosystem
Intel isn't a cloud provider, but its TDX and SGX technologies underpin offerings across Azure, GCP, and Alibaba Cloud, and are worth understanding directly. SGX offers fine-grained enclave isolation (smaller trusted computing base, more restrictive programming model) while TDX protects whole VMs. Strengths: SGX has one of the longest security research histories of any TEE technology, with extensive academic scrutiny. Limitations: that same scrutiny has surfaced real side-channel vulnerabilities over the years (speculative execution attacks affecting SGX in particular), a reminder that hardware TEEs reduce but do not eliminate attack surface, and that patching cadence and microcode updates matter as much as the initial architecture.
Alibaba Cloud Confidential Computing
Less discussed in Western security circles but relevant for global deployments, Alibaba Cloud offers SEV-SNP-based confidential instances and its own Trusted and Reliable Computing service. Strengths: competitive pricing and useful for organizations with APAC compliance requirements. Limitations: documentation and third-party security review are noticeably thinner than the big three US hyperscalers, so due diligence takes more direct vendor engagement.
IBM Cloud Hyper Protect Virtual Servers
IBM's confidential offering is distinctive because it's built on IBM Z and LinuxONE secure execution rather than x86 SEV/TDX, giving it a different (and in some respects more mature, given IBM's mainframe security lineage) trust model. Strengths: strong attestation guarantees and a long history of hardware security module integration. Limitations: the architecture is less familiar to teams standardized on x86 tooling, and the ecosystem of compatible container images and CI/CD integrations is smaller than the hyperscaler options.
Practical Guidance for Choosing
If you're running unmodified VMs and want the lightest migration path, Azure or GCP's confidential VM tiers are the more direct fit. If you're building something enclave-native from scratch -- particularly for key custody or signing operations where you want the smallest possible trusted computing base -- AWS Nitro Enclaves or Intel SGX-based approaches deserve a closer look. In either case, don't treat "confidential computing" as a checkbox; verify the attestation chain end to end, confirm which CPU generation you're actually being billed for, and re-benchmark your own workload rather than relying on published overhead figures.
How Safeguard Helps
Confidential virtual machines solve hardware-level isolation, but they don't answer a related question that matters just as much for software supply chain security: can you prove that the code running inside that trusted environment is exactly the code your pipeline built, signed, and approved? Safeguard closes that gap. We help teams tie attestation evidence from confidential VM platforms -- whether that's Azure confidential VM attestation, Nitro Enclave attestation documents, or GCP confidential compute measurements -- back to verifiable build provenance, so a TEE's cryptographic guarantee of "this hardware is genuine" is backed by an equally verifiable guarantee of "this software is what we think it is." That means continuous monitoring of the artifacts deployed into confidential compute environments, SBOM-backed visibility into what's actually running inside the enclave or VM, and policy enforcement that flags drift between an attested build and what shows up in production. For teams navigating SOC 2 or similar compliance requirements around confidential workloads, Safeguard also helps generate the audit trail connecting infrastructure-level attestation to application-level integrity -- turning "we run on confidential VMs" into evidence an auditor can actually verify.