K8s Labels Everywhere! Decluttering With Node Profile Discovery.

The presentation discusses the benefits of using a profile-based approach for managing Kubernetes workloads and how it can simplify the pod spec and improve application performance.

• Moving towards a top-down perspective for workload management
• Creating profiles of features to achieve a certain quality of service for applications
• Aligning profiles with prevalent abstractions in today's deployments
• Using cluster slicing and partitioning for performance critical workloads
• Implementing a JSON schema to validate and promote consistency of profiles
• Exploring different approaches to incorporating profile management into NFD and policy-based control systems

The presentation highlights the problem of a laundry list of feature requirements baked into a pod spec and how it can get out of control. Instead, a profile-based approach can simplify workload management and improve application performance. By creating profiles of features that align with prevalent abstractions in today's deployments, such as cluster slicing and partitioning, applications can fulfill a certain quality of service. Implementing a JSON schema can ensure consistency and validate the creation of new profiles. The presentation also explores different approaches to incorporating profile management into NFD and policy-based control systems.

A recent CNCF community survey showed that 57% of respondents have 100+ machines in their fleet and 17% have more than 5000 machines (including VM, bare metal etc.). When managing such broad and diverse clusters, variations in node capabilities and features are inevitable. So how exactly are individual features tracked on a node-by-node basis? Node Feature Discovery (NFD) is commonly used for basic feature discovery and labelling across a Kubernetes cluster. This talk, however, introduces a new component: Node Profile Discovery (NPD). NPD provides an extra layer of abstraction from NFD, alleviating the burden of managing individual features. NPD is designed to work in conjunction with NFD, aggregating individual features into higher level profiles and applying these profiles to suitable nodes. This talk will show how NPD can make life easier for application developers and sys-admins alike.