HPA autoscaling/v2beta2 の機能解説と Datadog を利用した HPA External Metrics の活用事例 / Introduction to the feature of HPA autoscaling/v2beta2 and examples of using HPA External Metrics with Datadog
HPA autoscaling/v2beta2 の機能解説と Datadog を利用した HPA External Metrics の活用事例 / Introduction to the feature of HPA autoscaling/v2beta2 and examples of using HPA External Metrics with Datadog
HPA autoscaling/v2beta2 ͷػೳղઆͱ Datadog Λར༻ͨ͠ HPA External Metrics ͷ׆༻ࣄྫ Introduction to the feature of HPA autoscaling/v2beta2 and examples of using HPA External Metrics with Datadog Takeshi Kondo / @chaspy 2021/01/21 Kubernetes Meetup Tokyo #38
autoscaling/v1 autoscaling/v2beta2 Let's check out v1 first to learn the basic algorithm Note: autoscaling/v2beta1 is deprecated in v1.19 https://v1-19.docs.kubernetes.io/docs/setup/release/notes/#deprecation
autoscaling/v1 scaleTargetRef -required reference to scaled resource; horizontal pod autoscaler will learn the current resource consumption and will set the desired number of pods by using its Scale subresource.
autoscaling/v1 minReplicas minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the alpha feature gate HPAScaleToZero is enabled and at least one Object or External metric is configured. Scaling is active as long as at least one metric value is available. https://kubernetes.io/docs/reference/command-line-tools-reference/feature-gates/ HPAScaleToZero ͷ Feature Gate 1.16 ͔Β
autoscaling/v1 targetCPUUtilizationPercentage target average CPU utilization (represented as a percentage of requested CPU) over all the pods; if not specified the default autoscaling policy will be used.
target average CPU utilization (represented as a percentage of requested CPU) over all the pods; if not specified the default autoscaling policy will be used.
autoscaling/v1 CPU Request ͕ 100m core ͩͬͨ ߹ɺHPA Pod ͷฏۉ CPU ༻ ͕ 100m core ʹͳΔΑ͏ʹ replicas Λ૿ݮͤ͞Δ ʢtargetCPUUtilizationPercentage Request ʹର͢Δ Percentageʣ
autoscaling/v1 autoscaling/v2beta2 New features are available in v2 Note: autoscaling/v2beta1 is deprecated in v1.19 https://v1-19.docs.kubernetes.io/docs/setup/release/notes/#deprecation
Support for multiple metrics • the Horizontal Pod Autoscaler controller will evaluate each metric, and propose a new scale based on that metric. The largest of the proposed scales will be used as the new scale. Ref: https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/#support-for-multiple-metrics
Support for multiple metrics Ref: https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/#support-for-multiple-metrics Current Pod = 3 resource.name = cpu target.averageUtilization = 100 resource.name = memory target.averageUtilization = 100 Desired replicas CPU base ͩͱ 5 Memory base ͩͱ 2 HPA 5 Λ࠾༻ ʢΑΓେ͖͍Λ࠾༻ʣ
Support for custom metrics • Kubernetes then queries the new custom metrics API to fetch the values of the appropriate custom metrics. • By default, the HorizontalPodAutoscaler controller retrieves metrics from a series of APIs. In order for it to access these APIs, cluster administrators must ensure that: • The API aggregation layer is enabled. • The corresponding APIs are registered: • For resource metrics, this is the metrics.k8s.io API, generally provided by metrics- server... • For custom metrics, this is the custom.metrics.k8s.io API. It's provided by "adapter" API servers provided by metrics solution vendors... • For external metrics, this is the external.metrics.k8s.io API.... https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/#support-for-custom-metrics https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/#support-for-metrics-apis
How to get the custom/external metrics? HPA Controller API Server Custom Metrics Server Tell me the value of your custom/external metric Aggregation Layer External Metrics Server
Support for configurable scaling behavior(v1.18~) • Scaling Policies • When the number of pods is more than 40 the second policy will be used for scaling down. For instance if there are 80 replicas and the target has to be scaled down to 10 replicas then during the first step 8 replicas will be reduced 1 behavior: 2 scaleDown: 3 policies: 4 - type: Pods 5 value: 4 6 periodSeconds: 60 7 - type: Percent 8 value: 10 9 periodSeconds: 60
Support for configurable scaling behavior(v1.18~) • Stabilization Window • The stabilization window is used to restrict the flapping of replicas when the metrics used for scaling keep fluctuating. The stabilization window is used by the autoscaling algorithm to consider the computed desired state from the past to prevent scaling 1 scaleDown: 2 stabilizationWindowSeconds: 300
autoscaling/v2beta2 1 apiVersion: autoscaling/v2beta2 2 kind: HorizontalPodAutoscaler 3 metadata: 4 name: api 5 spec: 6 scaleTargetRef: 7 apiVersion: apps/v1 8 kind: Deployment 9 name: api 10 minReplicas: 40 11 maxReplicas: 1000 12 metrics: 13 - type: Resource 14 resource: 15 name: cpu 16 target: 17 type: Utilization 18 averageUtilization: 60 19 - type: External 20 external: 21 metric: 22 name: [email protected]:timed-exam 23 target: 24 type: AverageValue 25 averageValue: 1 averageUtilization averageUtilization is the target value of the average of the resource metric across all relevant pods, represented as a percentage of the requested value of the resource for the pods. Currently only valid for Resource metric source type
10:00 - 11:00 A school 18 11:00 - 12:00 B school 30 13:00 - 14:00 C school 500 Time,#pods 10:00 90 11:00 270 13:00 2500 Scheduled-Scaling Desired replicas
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