Event-driven Autoscaling with KEDA & AKS by Ronak Banka
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Kubernetes is an excellent container orchestration platform, but when it comes to AutoScaling of containers, there is limited capability with just CPU & memory metrics scaling applications. This talk will introduce how can the combination of KEDA & Azure Kubernetes Service can help AutoScaling of applications based on metrics from various metric sources, eg. Prometheus, Kafka, etc.
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Event-driven Autoscaling with KEDA & AKS by Ronak Banka
- 1. Event Driven Scaling with KEDA & AKS Ronak Banka
- 2. HELLO! I am Ronak Banka Senior Solutions Architect with VMware, Singapore ▸ Loves Kubernetes, Cloud & Containers ▸ SRE practitioner ▸ Loves Cooking 2 @ronakbanka https://devstack.in
- 3. Agenda ▸ Why AutoScaling? ▸ Scaling options in K8s ▸ What is KEDA? ▸ KEDA Architecture Overview ▸ Demo ▸ Scaling using Prometheus metrics 3
- 6. Scaling Options in k8s
- 7. Scaling options 7 ● Manual Scaling ● Horizontal pod Autoscaler (HPA) ● Virtual Nodes ● Event Driven Scaling
- 8. ▸ This type of Scaling depends on human action to scale the application $ Kubectl scale deployment/my-app --replicas=2 Similar operation can be done for cluster Autoscaling using az cli 8 Manual Scaling
- 9. ▸ This type of Scaling depends on system metrics to scale the application $ Kubectl autoscale deployment/my-app --max=5 --cpu-percent=80 Limited by metric types which can be used out of the box 9 Horizontal pod Autoscaler (HPA)
- 10. ▸ This type of Scaling implements Virtual Kubelet in AKS cluster. ▸ Azure container instances(ACI) are responsible for running extra pods without any additional infrastructure required. 10 Virtual Nodes
- 11. 11 Virtual Nodes
- 12. ▸ This type of Scaling can use metrics from different sources. ▸ Uses HPA in backend for actual scaling ▸ Can be used in combination with Virtual Node 12 Event Driven Scaling
- 13. What is KEDA?
- 14. 14 KEDA is a Kubernetes-based Event Driven Autoscaler
- 15. KEDA works alongside standard Kubernetes components like the Horizontal Pod Autoscaler and can extend functionality without overwriting or duplication. Roles of Keda-operator: ▸ Agent - KEDA activates and deactivates Kubernetes Deployments to scale to and from zero on no events. ▸ Metrics - KEDA acts as a Kubernetes metrics server that exposes rich event data like queue length or stream lag to the Horizontal Pod Autoscaler 15 How does KEDA works?
- 16. 16 KEDA Architecture ScaledObjects: Desired mapping between an event source and the Kubernetes Deployment External trigger source: Prometheus, Kafka, RabbitMQ, etc Scaler: Detect if a deployment should be activated or deactivated, and feed custom metrics for a specific event source Metrics adapter: Presents metrics from external sources to the Horizontal Pod Autoscaler
- 17. 17 KEDA Scalers
- 18. DEMO TIME
- 19. 19
- 20. 20 THANKS! Any questions? You can find me at: ▸ @ronakbanka on Twitter ▸ Check my Blog on https://devstack.in
Notas del editor
- Let’s talk about, what is this container, which everyone is talking about these days? Why containers are becoming so important these days?
- Isolation- Containers virtualize CPU, memory, storage, and network resources at the OS-level
- Before we go to the Demo….let’s and next slide