What is Azure Confidential Computing?
Azure Confidential Computing significantly improves data privacy and security by protecting information during processing, rather than just focusing on its storage or transmission. This is accomplished through the use of hardware-based trusted execution environments that encrypt data in memory, allowing computations to proceed only once the cloud platform verifies the environment's authenticity. As a result, access from cloud service providers, administrators, and other privileged users is effectively restricted. Furthermore, it supports scenarios like multi-party analytics, enabling different organizations to collaborate on encrypted datasets for collective machine learning endeavors without revealing their individual data. Users retain full authority over their data and code, determining which hardware and software have access, and can seamlessly migrate existing workloads using familiar tools, SDKs, and cloud infrastructures. In essence, this innovative approach not only enhances collaborative efforts but also greatly increases trust and confidence in cloud computing environments, paving the way for secure and private data interactions across various sectors.
Integrations
Similar Software to Azure Confidential Computing
Google Compute Engine
Google's Compute Engine, which falls under the category of infrastructure as a service (IaaS), enables businesses to create and manage virtual machines in the cloud. This platform facilitates cloud transformation by offering computing infrastructure in both standard sizes and custom machine configurations. General-purpose machines, like the E2, N1, N2, and N2D, strike a balance between cost and performance, making them suitable for a variety of applications. For workloads that demand high processing power, compute-optimized machines (C2) deliver superior performance with advanced virtual CPUs. Memory-optimized systems (M2) are tailored for applications requiring extensive memory, making them perfect for in-memory database solutions. Additionally, accelerator-optimized machines (A2), which utilize A100 GPUs, cater to applications that have high computational demands. Users can integrate Compute Engine with other Google Cloud Services, including AI and machine learning or data analytics tools, to enhance their capabilities. To maintain sufficient application capacity during scaling, reservations are available, providing users with peace of mind. Furthermore, financial savings can be achieved through sustained-use discounts, and even greater savings can be realized with committed-use discounts, making it an attractive option for organizations looking to optimize their cloud spending. Overall, Compute Engine is designed not only to meet current needs but also to adapt and grow with future demands.
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Thinfinity Workspace
Key Features of Thinfinity Workspace 7.0:
- Utilizes Progressive Web App (PWA) technology to enhance user experience seamlessly.
- Combines Thinfinity VNC, VirtualUI, and z/Scope for unparalleled flexibility.
- Offers HTML5 terminal emulation compatible with DEC terminals, as well as TN 5220 and TN 3270 protocols.
- Includes comprehensive enterprise-grade audit logs to ensure robust security and compliance management.
- Employs a proprietary VNC protocol for effective real-time monitoring and troubleshooting.
ENHANCE USER EXPERIENCE
- Distribute essential applications, desktops, and files through a unified web portal.
- Simplify remote browser access for users, limiting them to only the necessary resources for their tasks.
STREAMLINE IT AND ELIMINATE VPNS
- Move away from traditional VPN setups and their associated complexities.
- Facilitate access from any device, including Chromebooks and mobile devices, with just a web browser—no setup required.
PROTECT YOUR BUSINESS SECURITY
- Utilize connections that are encrypted to enterprise-grade standards.
- Seamlessly integrate with both internal and external identity management systems.
- Implement two-factor or multi-factor authentication policies across all identity platforms, ensuring an additional layer of security for user access.
- This comprehensive approach not only enhances user experience but also strengthens overall system integrity, making it a vital tool for modern businesses.
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Delska
Delska operates as a specialized data center and network service provider, delivering customized IT and networking solutions for enterprises. With a total of five data centers in Latvia and Lithuania—one of which is set to open in 2025—and additional points of presence in Germany, the Netherlands, and Sweden, we create a robust regional ecosystem for data centers and networking. Our commitment to sustainability is reflected in our goal to reach net-zero CO2 emissions by 2030, establishing a benchmark for eco-friendly IT infrastructure in the Baltic region.
Beyond traditional services like cloud computing, colocation, and data security, we also introduced the myDelska self-service cloud platform, designed for rapid deployment of virtual machines and management of IT resources, with bare metal services expected soon.
Our platform boasts several essential features, including unlimited traffic and fixed monthly pricing, API integration, customizable firewall settings, comprehensive backup solutions, real-time network topology visualization, and a latency measurement map, supporting various operating systems such as Alpine Linux, Ubuntu, Debian, Windows OS, and openSUSE.
In June 2024, Delska expanded its portfolio by merging with two companies—DEAC European Data Center and Data Logistics Center (DLC)—which continue to function as separate legal entities under the ownership of Quaero European Infrastructure Fund II. This strategic merger enhances our capacity to provide even more innovative services and solutions to our clients.
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NVIDIA Confidential Computing
NVIDIA Confidential Computing provides robust protection for data during active processing, ensuring that AI models and workloads are secure while executing by leveraging hardware-based trusted execution environments found in NVIDIA Hopper and Blackwell architectures, along with compatible systems. This cutting-edge technology enables businesses to conduct AI training and inference effortlessly, whether it’s on-premises, in the cloud, or at edge sites, without the need for alterations to the model's code, all while safeguarding the confidentiality and integrity of their data and models. Key features include a zero-trust isolation mechanism that effectively separates workloads from the host operating system or hypervisor, device attestation that ensures only authorized NVIDIA hardware is executing the tasks, and extensive compatibility with shared or remote infrastructures, making it suitable for independent software vendors, enterprises, and multi-tenant environments. By securing sensitive AI models, inputs, weights, and inference operations, NVIDIA Confidential Computing allows for the execution of high-performance AI applications without compromising on security or efficiency. This capability not only enhances operational performance but also empowers organizations to confidently pursue innovation, with the assurance that their proprietary information will remain protected throughout all stages of the operational lifecycle. As a result, businesses can focus on advancing their AI strategies without the constant worry of potential security breaches.
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Company Facts
Company Name:
Microsoft
Date Founded:
1975
Company Location:
United States
Company Website:
azure.microsoft.com/en-us/solutions/confidential-compute
Product Details
Deployment
SaaS
Training Options
Documentation Hub
Online Training
Webinars
Video Library
Support
Standard Support
24 Hour Support
Web-Based Support
Product Details
Target Company Sizes
Individual
1-10
11-50
51-200
201-500
501-1000
1001-5000
5001-10000
10001+
Target Organization Types
Mid Size Business
Small Business
Enterprise
Freelance
Nonprofit
Government
Startup
Supported Languages
English