Compare IBM Hyper Protect Virtual Servers vs. Google Cloud Confidential VMs

IBM Hyper Protect Virtual Servers

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What is IBM Hyper Protect Virtual Servers?

IBM Hyper Protect Virtual Servers employ IBM Secure Execution for Linux, establishing a confidential computing environment that protects sensitive data within both virtual servers and container settings. This solution harnesses a hardware-based, trusted execution environment (TEE) to ensure secure computations, accessible both on-premises and as a managed service via IBM Cloud. Organizations are able to confidently develop, deploy, and manage essential applications across hybrid multi-cloud setups while taking advantage of the confidential computing features available on IBM Z and LinuxONE. Developers are equipped to create their applications within a secure framework that guarantees data integrity, and administrators can verify that applications originate from trustworthy sources through their auditing processes. Additionally, operations teams are empowered to oversee systems without requiring direct access to either applications or their sensitive data. This methodology provides substantial protection for digital assets on a secure, tamper-resistant Linux platform, instilling confidence in businesses as they navigate intricate security challenges. Consequently, IBM Hyper Protect Virtual Servers are integral to bolstering the overall security strategies of organizations, helping them adapt to evolving threats in the digital landscape. This comprehensive approach ensures that enterprises can maintain operational efficiency while safeguarding their most critical information assets.

What is Google Cloud Confidential VMs?

Google Cloud's Confidential Computing provides hardware-based Trusted Execution Environments (TEEs) that ensure data is encrypted during active use, thus finalizing the encryption for data both at rest and while in transit. This comprehensive suite features Confidential VMs, which incorporate technologies such as AMD SEV, SEV-SNP, Intel TDX, and NVIDIA confidential GPUs, as well as Confidential Space to enable secure multi-party data sharing, Google Cloud Attestation, and split-trust encryption mechanisms. Confidential VMs are specifically engineered to support various workloads within Compute Engine and are compatible with numerous services, including Dataproc, Dataflow, GKE, and Vertex AI Workbench. The foundational architecture guarantees encryption of memory during runtime, effectively isolating workloads from the host operating system and hypervisor, and also includes attestation capabilities that offer clients verifiable proof of secure enclave operations. Use cases for this technology are wide-ranging, encompassing confidential analytics, federated learning in industries such as healthcare and finance, deployment of generative AI models, and collaborative data sharing within supply chains. By adopting this cutting-edge method, the trust boundary is significantly reduced to only the guest application, rather than the broader computing environment, which greatly enhances the security and privacy of sensitive workloads. Furthermore, this innovative solution empowers organizations to maintain control over their data while leveraging cloud resources efficiently.