The CNCF Technical Oversight Committee (TOC) has voted to accept Confidential Containers as a CNCF incubating project.
About Confidential Containers
Confidential Containers addresses the need to protect data in use within cloud native environments. While data at rest and in transit are commonly encrypted, processing data in memory often leaves it vulnerable. Confidential Containers leverages hardware-based Trusted Execution Environments (TEEs) to encrypt data during computation. This allows organizations to run sensitive workloads on third-party infrastructure with the assurance that the infrastructure operator cannot access the data being processed. While most security solutions focus on data at rest or in transit, this project focuses on protecting data in use.
The project began as an open source effort in 2021 through a collaboration between Red Hat, Intel, IBM, and other industry partners to bring confidential computing to cloud native applications. By integrating hardware security features into the Kubernetes ecosystem through the Kata Containers runtime, Confidential Containers allows organizations to run sensitive workloads on public clouds or private infrastructure with increased assurance. These advancements allow developers to deploy confidential workloads using familiar Kubernetes workflows, reducing the complexity of adopting TEEs.
Confidential Containers Key Milestones and Ecosystem Development
Since joining the CNCF Sandbox, Confidential Containers has achieved significant growth, supported by major technology organizations and cloud service providers, including Microsoft Azure, Intel, AMD, IBM, NVIDIA, Alibaba, and Red Hat.
The project’s ecosystem now reflects robust engagement, with over 1,000 combined GitHub stars across foundational core organization repositories, over 1,200 merged pull requests across 26 repository groups, and more than 1,500 historical and active tracking issues. This activity is driven by a vibrant community of over 150 active contributors from hardware vendors, hyperscale cloud providers, and security researchers, all supported by more than 15 cumulative engineering lifecycle releases.
Confidential Containers continues to mature through seamless integration with Kubernetes and infrastructure automation via tools like Kyverno. It is also being integrated into KServe for supporting confidential AI use cases.
“The Confidential Containers community has successfully transformed TEE-backed security from a niche research interest into a robust, production-ready foundation for sensitive Kubernetes workloads. By joining CNCF, we secure the neutral, open governance required to set the industry standard for privacy-preserving infrastructure.” — Ariel Adam, Maintainer, Confidential Containers
“Our community has effectively abstracted the complexity of heterogeneous hardware-level isolation into standard, accessible Kubernetes patterns, ensuring security scales with the stack. Confidential Container’s transition to incubation allows us to align ‘data-in-use’ protection with the broader cloud native ecosystem, similar to how we’ve standardized critical infrastructure before. We are now delivering the secure, native capability required to deploy use cases such as confidential AI inference at production scale.” — Mikko Ylinen, Maintainer, Confidential Containers
The CNCF TOC provides technical leadership to the cloud native community. It defines and maintains the foundation’s technical vision, approves new projects, and stewards them across maturity levels. The TOC also aligns projects within the overall ecosystem, sets cross-cutting standards and best practices, and works with end users to ensure long-term sustainability. As part of its charter, the TOC evaluates and supports projects as they meet the requirements for incubation and continue progressing toward graduation.
“Confidential Containers has demonstrated clear maturity in integrating TEE-backed isolation within standard Kubernetes workflows, earning its place as an incubating project. This transition validates the community’s effort to standardize data-in-use protection, ensuring that security is baked into the infrastructure rather than bolted on as an afterthought.” — Faseela K, TOC Sponsor
“Achieving incubation is the direct result of the project’s robust development history, evidenced by its successful integration across heterogeneous TEE environments. By abstracting complex hardware security into standard Kubernetes patterns, the project allows developers to treat confidential computing as a native capability of their application stack. We’ve done this before with critical infrastructure standards, and this approach will now serve as the secure backbone for the next era of high-intensity, distributed AI inference.” — Kevin Wang, TOC Sponsor
Confidential Containers Main Components
Confidential Containers is composed of several components:
- Confidential Containers Pods: Enables deployment of unmodified containers across TEEs by abstracting complex hardware security into standard Kubernetes Pod resources.
- Trustee: A specialized, scalable attestation service that verifies the integrity of TEE-enabled nodes and workloads before granting secrets or keys.
- Helm Charts & Controllers: Provides lifecycle management, automating the provisioning and orchestration of confidential workloads across heterogeneous TEE environments.
- Hardware Abstraction Layer: Seamlessly integrates with multiple TEE technologies, including Intel® TDX and AMD SEV-SNP, allowing users to run sensitive applications without being locked into a single cloud provider’s hardware.
Confidential Containers Roadmap
The Confidential Containers project roadmap distinguishes between a short-term focus (2-6 months) and a mid-to-long-term outlook (6-18 months).
The short-term roadmap aims to deliver an end-to-end, stable, and easy-to-deploy solution, with development tracked across two GitHub projects: the release project for version-specific development and the Trustee project for ongoing implementation requirements.
In contrast, the mid- and long-term roadmap prioritizes use-case-driven development. Rather than focusing solely on specific features, this approach emphasizes delivering the real-world use cases that customers require, supported by robust CI/CD processes to ensure consistent end-to-end functionality.
To view the full project roadmap, visit: https://github.com/confidential-containers/confidential-containers/blob/main/roadmap.md
As a CNCF-hosted project, Confidential Containers is part of a neutral foundation aligned with its technical interests, as well as the larger Linux Foundation, which provides governance, marketing support, and community outreach. Confidential Containers joins incubating technologies: Backstage, Buildpacks, Chaos Mesh, Container Network Interface (CNI), Contour, Cortex, CubeFS, Emissary-Ingress, gRPC, HAMi, in-toto, Keptn, Keycloak, KubeEdge, Kubeflow, KubeVela, KubeVirt, Litmus, Longhorn, NATS, Notary, OpenFeature, OpenKruise, OpenMetrics, Operator Framework, Thanos, and Volcano. For more information on maturity requirements for each level, please visit the CNCF Graduation Criteria.
To learn more about Confidential Containers, visit confidentialcontainers.org, explore the GitHub repository, or join the community on the #confidential-containers Slack channel.
Facts Only
* The CNCF Technical Oversight Committee (TOC) voted to accept Confidential Containers as a CNCF incubating project.
* Confidential Containers addresses protecting data in use within cloud native environments by leveraging hardware-based Trusted Execution Environments (TEEs).
* The project originated as an open source effort in 2021 involving Red Hat, Intel, IBM, and other partners.
* Confidential Containers integrates hardware security into the Kubernetes ecosystem through the Kata Containers runtime.
* The project focuses on protecting data in use, unlike most solutions focusing on data at rest or in transit.
* The project has gained support from organizations including Microsoft Azure, Intel, AMD, IBM, NVIDIA, Alibaba, and Red Hat.
* Ecosystem metrics include over 1,000 combined GitHub stars, over 1,200 merged pull requests across 26 repository groups, and over 1,500 tracking issues.
* Key components include Confidential Containers Pods, a Trustee service, Helm Charts & Controllers, and a Hardware Abstraction Layer supporting Intel TDX and AMD SEV-SNP.
* The roadmap involves short-term delivery of an end-to-end solution and mid-to-long-term focus on use-case-driven development.
Executive Summary
The CNCF Technical Oversight Committee (TOC) has voted to accept Confidential Containers as a CNCF incubating project. This decision recognizes the project's role in protecting data in use within cloud-native environments by leveraging hardware-based Trusted Execution Environments (TEEs) for encryption during computation. Confidential Containers emerged from an open-source effort involving Red Hat, Intel, IBM, and others to integrate hardware security features into the Kubernetes ecosystem via the Kata Containers runtime. The project aims to allow sensitive workloads to run on public or private infrastructure with assurance that infrastructure operators cannot access the processed data, focusing specifically on protecting data in use rather than just data at rest or in transit.
The project has developed a significant ecosystem, evidenced by over 1,000 GitHub stars, 1,200 merged pull requests across 26 repository groups, and extensive tracking of issues, supported by contributions from major technology organizations like Microsoft Azure, Intel, AMD, and IBM. Key components include Confidential Containers Pods for deploying containers across TEEs, a Trustee service for integrity verification, Helm Charts/Controllers for orchestration, and a Hardware Abstraction Layer supporting technologies like Intel TDX and AMD SEV-SNP. The project is maturing through integration with Kubernetes tools like Kyverno and KServe, aiming to standardize data-in-use protection within the cloud-native stack.
Full Take
The transition of Confidential Containers into CNCF incubation signals a maturation point where specialized hardware security concepts are being formalized into standard cloud-native infrastructure patterns. The core pattern emerging is the abstraction of complex, heterogeneous hardware isolation mechanisms (TEEs) into familiar Kubernetes abstractions. This move aligns with the broader ecosystem push to bake security directly into the infrastructure layer rather than treating it as an external add-on. The community's success in achieving incubation appears rooted in successfully abstracting complexity—moving from low-level TEE management to high-level Pod and orchestration concepts.
The pattern of engagement—broad participation from major hardware vendors and hyperscalers—suggests that the perceived value shifts from a niche security research area to a foundational infrastructure requirement for future workloads, particularly those involving confidential AI. The emphasis on establishing neutral governance through the CNCF structure suggests an attempt to create shared standards rather than proprietary vendor solutions. However, the long-term challenge lies in ensuring this abstraction remains truly agnostic and that integration across diverse TEE implementations does not introduce new security pitfalls at scale.
What is the cost of this standardization? If successful, it could establish a baseline expectation for all cloud-native deployments regarding data-in-use protection, accelerating adoption. Conversely, if the abstractions over hardware heterogeneity prove insufficient or introduce systemic gaps, the complexity absorbed by the ecosystem might mask underlying architectural weaknesses that only specialized hardware knowledge can expose. Further inquiry should focus on the long-term stability of the Hardware Abstraction Layer and the governance mechanisms that will enforce standards across different cloud environments beyond those explicitly named as partners.
Sentinel — Human
The text reads as a well-structured summary of a technical project's status and achievements, strongly supported by direct community testimonials, suggesting human authorship focused on conveying factual development milestones.