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TAG Workloads Foundation

TAG Workloads Foundation defines and advances practices and standards for fundamental cloud native workload execution environments and their related lifecycle management within cloud native systems, applications, and architectures.

Mission Statement​

To define and advance practices and standards for fundamental cloud native workload execution environments and their related lifecycle management within cloud native systems, applications, and architectures. This supports the CNCF's technical vision by addressing critical problems faced by adopters and contributing to a robust cloud native ecosystem.

Leadership​

Chairs​

NameGitHubOrganizationTerm
Danielle Tal@miao0miao-2025-07-01 to 2026-06-30
Paco Xu@pacoxuDaoCloud2025-07-01 to 2027-06-30
Yuan Tang@terrytangyuanRed Hat2025-07-01 to 2027-06-30

Tech Leads​

NameGitHubOrganizationTerm
Alexander D. Kanevskiy@kadIntel2025-07-02 to 2026-06-30
Hongcai Ren@RainbowMangoHuawei2025-07-02 to 2027-06-30
Kante Yin@kerthcetHiverge2025-07-02 to 2027-06-30
Rajas Kakodkar@rajaskakodkarBroadcom2025-07-02 to 2027-06-30
Stephen Rust@srustAkamai2025-07-02 to 2026-06-30

TOC Liaisons​

Meetings​

TAG Workloads Foundation Meetings

All meetings are open to the public. No registration required - simply join the meeting from the calendar link.

Communication Channels​

Slack​

Join the CNCF Slack workspace and connect with the TAG:

Mailing List​

Focus Areas​

TAG Workloads Foundation works on fundamental aspects of cloud native workload execution:

Workload Execution Environments​

  • Container runtime interfaces and standards
  • Virtual machine and container integration
  • Sandboxing and isolation technologies
  • Runtime security models

Lifecycle Management​

  • Workload deployment patterns
  • Update and rollback strategies
  • Scaling and scheduling
  • Health checking and self-healing

Resource Management​

  • CPU and memory allocation
  • Storage provisioning and management
  • Network resource allocation
  • GPU and specialized hardware

Workload Types​

  • Stateless and stateful workloads
  • Batch and job processing
  • Long-running services
  • Event-driven workloads

Standards and APIs​

  • Workload specification standards
  • Runtime interface definitions
  • Portability across platforms
  • Interoperability between systems

Subprojects​

Batch​

To enhance collaboration among projects, improve interoperability, and empower users to efficiently leverage batch systems in cloud-native environments.

In scope:

To reduce fragmentation in the k8s batch ecosystem: congregate leads and users from different external and internal projects and user groups (CNCF TAGs, k8s sub-projects focused on batch-related features such as topology-aware scheduling) in the batch ecosystem to gather requirements, validate designs and encourage reutilization of core K8s APIs.

The following recommendations for enhancements:

  • Additions to the batch API group, currently including Job and CronJob resources that benefit batch use cases such as HPC, AI/ML, data analytics and CI.
  • Primitives for job-level queueing, not limited to the k8s Job resource. Long-term, this could include multi-cluster support.
  • Primitives to control and maximize utilization of resources in fixed-size clusters (on-prem) and elastic clusters (cloud).
  • Benchmarking models for Batch systems
  • Data Locality
  • User Stories
  • Scheduling support for specialized hardware (Accelerators, NUMA, Networking, etc.)

Out of scope:

  • Addition of new API kinds that serve a specialized type of workload. The focus should be on general APIs that specialized controllers can build on top of.
  • Uses of the batch APIs as support for serving workloads (eg. backups, upgrades, migrations). These can be served by existing SIGs.
  • Proposals that duplicate the functionality of core kubernetes components (job-controller, kube-scheduler, cluster-autoscaler).
  • Job workflows or pipelines. Mature third party frameworks serve these use cases with the current kubernetes primitives. But additional primitives to support these frameworks could be in scope.

Deliverable(s) or exit criteria:

  • Maintaining a landscape document for currently available projects (already published-relocated and maintained)
  • Data Locality project-deliverables TBD, but something that helps in this space (already in process)
  • Benchmarking suite for Batch systems (already in process)
  • User stories published doc for Batch systems (already in process)

Initiatives​

View current and past initiatives:

Getting Involved​

We welcome contributions from anyone interested in cloud native workload execution:

Attend Meetings​

Join our regular meetings to hear about ongoing work and participate in discussions. Check the meeting calendar for details.

Contribute to Initiatives​

Browse active initiatives and volunteer to help with specific deliverables.

Share Your Experience​

  • Present workload management use cases or lessons learned at TAG meetings
  • Write blog posts about workload execution patterns and practices
  • Contribute to white papers and best practices documents

Join the Conversation​

Resources​