Kubernetes - Load Balancing For Virtual Machines (Pods)

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1 Kubernetes - Load Balancing For Virtual Machines (Pods) 4 th of Feb 2018 Yanir Quinn Senior Software Engineer Red Hat This presentation is licensed under a Creative Commons Attribution 4.0 International License

2 About me and ovirt/kubevirt Yanir Quinn Working for Red Hat since 2016 ovirt SLA team / KubeVirt ovirt Red Hat Virtualization KubeVirt 2

3 Agenda A quick intro to Kubevirt What is Kubernetes + Kubevirt in a nutshell Scheduling in Kubernetes Basic characteristics of scheduling in kubernetes Why load balancing? What is missing in current Kubernetes release What work can be done or in progress Dscheduler Kubernetes incubator project Dry run functionality for Kubernetes What is scheduling simulation Dry run scheduling use cases VM migration What is VM migration? How can it be reflected on pods? Load balancing algorithm An example for a load balancing algorithm that can Make use of dry run scheduling 3

4 Kubernetes Kubernetes is about managing tasks and applications at cloud scale By using container runtimes It allows managing containers on a cluster-level 4

5 With Kubernetes You Can Orchestrate containers across multiple hosts Make better use of hardware to maximize resources needed to run your enterprise apps Control and automate application deployments and updates Mount and add storage to run stateful apps 5

6 With Kubernetes You Can Scale containerized applications and their resources on the fly Declaratively manage services, which guarantees the deployed applications are always running how you deployed them Health-check and self-heal your apps with autoplacement, autorestart, autoreplication, and autoscaling 6

7 Kubernetes 7

8 Kubernetes Node Kubelet cadvisor Kube-Proxy 8

9 Kubernetes Master DevOps Controller manager API Server Scheduler etcd 9

10 KubeVirt Tries to close the gap between containers and VMs by enabling VM management on top of Kubernetes and integrating the VM into Kubernetes infrastructure where possible 10

11 Converged Infrastructure Virtual Machines Containers 11

12 KubeVirt 12

13 KubeVirt Drops directly into existing Kubernetes Clusters No additional host setup Simple install Extends Kubernetes so VMs can be scheduled alongside Containers Ties VMs into Pod Network Integrates with other Kubernetes concepts Manage VMs like Pods 13

14 Scheduling in Kubernetes Kubectl Kubectl apply -f pod-def.yaml def Im supposed to run that pod! I m running the Pod etcd / API server Kubelet on Node X For def node X A new pod with no machine assigned! Assign the pod to node X Scheduler 14

15 Why Load Balancing? (Rescheduling) Free Holes Scheduling decisions are only made at the time Pods are created Optimize cluster layout 15

16 Current Work Related to Rescheduling Autoscaling Eviction Policy Affinity + Taints and Tolerations Pod Priority and Preemption Critical add-ons 16

17 Current Work Related to Rescheduling Cluster Capacity Dscheduler Kubernetes Incubator 17

18 Dscheduler Set a strategy for balancing the cluster Find pods that could be evicted Scheduler will reschedule the evicted pods Minimal to no disturbance on the cluster 18

19 Dscheduler - Policies and Strategies Node #Pods < N Node Node Node Memory < X CPU < Y Node #Pods > N Memory > X CPU > Y Node Node Node 19

20 Dscheduler - Strategies apiversion: "descheduler/v1alpha1" kind: "DeschedulerPolicy" strategies: "LowNodeUtilization": enabled: true params: noderesourceutilizationthresholds: thresholds: "cpu" : 20 "memory": 20 "pods": 20 targetthresholds: "cpu" : 50 "memory": 50 "pods": 50 Nodes under that bound indicate Underutilization Potential nodes from where pods Could be evicted 20

21 Dscheduler - Strategies noderesourceutilizationthresholds: thresholds: "cpu" : 20 "memory": 20 "pods": 20 targetthresholds: "cpu" : 50 "memory": 50 "pods": 50 Nodes under that bound indicate Underutilization Potential nodes from where pods Could be evicted 21

22 Dscheduler - Eviction Policy Pods that cannot be evicted : Critical Not expected to terminate Provide machine specific service Have local storage Best efforts pods are evicted before Burstable and Guaranteed pods. 22

23 What Might Be Missing? Optionally verify if can schedule and where An accurate simulation of Pods reassignment No duplicates of a Pod s resource consumption Actual rescheduling of replacement pods to better nodes 23

24 Dry Run Functionality for Kubernetes Scheduler "dry run" endpoint that takes a pod and tells you which nodes it can schedule onto Output: A destination Node for a newly created Pod (without performing any real binding) Output: Can a Pod be scheduled on Node/Nodes? Node Node Scheduler??? Node 24

25 Dry Run Functionality Use Cases Rescheduling / Load Balancing Simulation of the system s state after pods creation Including assignment to nodes Cluster capacity analysis, Autoscaler, DeamonSet Controller, etc. Using a replacement scheduler with stricter predicates Obstacles 25

26 Load Balancing Virtual Machines (VM) (VM) 26

27 Virtual Machines Migration kind: Migration metadata: generatename: my-migration spec: nodeselector: kubevirt.io/hostname: node1 selector: name: testvm status: phase: Succeeded Backed by a controller: On object create, schedules a new Pod On successful Pod start, it triggers the migration At the end of the migration the object is moved to a final state Always one VirtualMachine object you reference The objects Migration with VirtualMachine provide a consistent entry point to anything VirtualMachine related, like the Pod does for Kubernetes. 27

28 So How Can It Work On KubeVirt? Integrate Dscheduler Pod gets marked for deletion Pod deletion blocked Virtual machine is migrated behind the scenes Explicit load balancing based on the migration object 28

29 Load Balancing Algorithm Scheduler Node Bes O r Node X Cpu 1 Mem Ove l 2 29

30 Summary It's about balancing VMs Leveraging Kubernetes More to come 30

31 THANK YOU This presentation is licensed under a Creative Commons Attribution 4.0 International License

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