The document discusses scaling Kubernetes using Karpenter, an open-source cluster autoscaler designed by AWS to optimize workload scheduling. It covers advanced scheduling features such as pod affinity and anti-affinity, which help manage pod placement based on specific requirements. The integration of topology awareness with Karpenter, kubelet, and the scheduler is emphasized to enhance scaling for stateful workloads.

1. Scaling Kubernetes with
Karpenter: Meeting Advanced
Scheduling Requirements
By Lukonde Mwila

2. Lukonde Mwila
Principal Technical Evangelist at SUSE | AWS Hero |
HashiCorp Ambassador
@Luke9ine

3. In This Talk...
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4. Popular concept and feature for obvious reasons
K8s allows us to scale the workloads and the cluster
Scaling in Kubernetes

5. Scaling in Kubernetes

6. We can use native K8s resources like VPA and HPA
Scaling Workloads

7. HPA Example

9. HPA Example

10. Additional Apps Example

11. Hello Karpenter

12. Open source cluster autoscaler built with AWS team
Designed to work with any Kubernetes cluster
Considers pod requirements for compute resources
Join the Slack #channel in the Kubernetes workspace
Karpenter

13. requiredDuringSchedulingIgnoredDuringExecution
preferredDuringSchedulingIgnoredDuringExecution
Applying scheduling constraints to pods is implemented by
establishing relationships between pods and specific nodes or
between pods themselves.
Inter-Pod Affinity

14. The podAffinity rule informs the scheduler to match pods that
relate to each other based on their labels.
Pod Affinity

15. Pod Affinity

16. The podAntiAffinity rule allows you to prevent certain pods
from running on the same node if the matching label criteria
are met.
Pod Anti Affinity

17. Pod Anti Affinity

18. Scheduling and dynamic provisioning of volumes were independent
The Dark Past

19. Topology awareness ensures that pods are placed on nodes
that meet their topology requirements (storage volumes)
The goal is to provide alignment between topology resources
and your workloads.
Topology manager (kubelet) + scheduler + Karpenter = Optimized
scaling for stateful workloads
Volume Topology Awareness

20. Volume Topology Awareness

21. Demo time...

22. Thank You Very Much!
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