diff --git a/devops/gc/deploy/README.md b/devops/gc/deploy/README.md index 31803b7e8193849d8791df0f06146adb73e59762..aa760e84dfff362af053bc1408295dde2d9c1e95 100644 --- a/devops/gc/deploy/README.md +++ b/devops/gc/deploy/README.md @@ -83,26 +83,34 @@ You need to set variables in **values.yaml** file using any code editor. Some of ### Horizontal Pod Autoscaling (HPA) variables (works only if tier=PROD and autoscaling=true) -| Name | Description | Type | Default |Required | -|------|-------------|------|---------|---------| -**hpa.minReplicas** | minimum number of replicas | integer | `6` | only if `global.autoscaling` is true and `global.tier` is PROD -**hpa.maxReplicas** | maximum number of replicas | integer | `15` | only if `global.autoscaling` is true and `global.tier` is PROD -**hpa.targetType** | type of measurements: AverageValue or Value | string | `AverageValue` | only if `global.autoscaling` is true and `global.tier` is PROD -**hpa.targetValue** | threshold value to trigger the scaling up | integer | `30` | only if `global.autoscaling` is true and `global.tier` is PROD -**hpa.behaviorScaleUpStabilizationWindowSeconds** | time to start implementing the scale up when it is triggered | integer | `10` | only if `global.autoscaling` is true and `global.tier` is PROD -**hpa.behaviorScaleUpPoliciesValue** | the maximum number of new replicas to create (in percents from current state)| integer | `50` | only if `global.autoscaling` is true and `global.tier` is PROD -**hpa.behaviorScaleUpPoliciesPeriodSeconds** | pause for every new scale up decision | integer | `15` | only if `global.autoscaling` is true and `global.tier` is PROD -**hpa.behaviorScaleDownStabilizationWindowSeconds** | time to start implementing the scale down when it is triggered | integer | `60` | only if `global.autoscaling` is true and `global.tier` is PROD -**hpa.behaviorScaleDownPoliciesValue** | the maximum number of replicas to destroy (in percents from current state) | integer | `25` | only if `global.autoscaling` is true and `global.tier` is PROD -**hpa.behaviorScaleDownPoliciesPeriodSeconds** | pause for every new scale down decision | integer | `60` | only if `global.autoscaling` is true and `global.tier` is PROD +| Name | Description | Type | Default | Required | +|-----------------------------------------------------|-------------------------------------------------------------------------------|---------|------------------|----------------------------------------------------------------| +| **hpa.minReplicas** | minimum number of replicas | integer | `6` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **hpa.maxReplicas** | maximum number of replicas | integer | `15` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **hpa.targetType** | type of measurements: AverageValue or Value | string | `"AverageValue"` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **hpa.targetValue** | threshold value to trigger the scaling up | integer | `200` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **hpa.behaviorScaleUpStabilizationWindowSeconds** | time to start implementing the scale up when it is triggered | integer | `10` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **hpa.behaviorScaleUpPoliciesValue** | the maximum number of new replicas to create (in percents from current state) | integer | `50` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **hpa.behaviorScaleUpPoliciesPeriodSeconds** | pause for every new scale up decision | integer | `15` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **hpa.behaviorScaleDownStabilizationWindowSeconds** | time to start implementing the scale down when it is triggered | integer | `60` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **hpa.behaviorScaleDownPoliciesValue** | the maximum number of replicas to destroy (in percents from current state) | integer | `25` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **hpa.behaviorScaleDownPoliciesPeriodSeconds** | pause for every new scale down decision | integer | `60` | only if `global.autoscaling` is true and `global.tier` is PROD | ### Limits variables -| Name | Description | Type | Default |Required | -|------|-------------|------|---------|---------| -**limits.maxTokens** | maximum number of requests per fillInterval | integer | `20` | only if `global.autoscaling` is true and `global.tier` is PROD -**limits.tokensPerFill** | number of new tokens allowed every fillInterval | integer | `20` | only if `global.autoscaling` is true and `global.tier` is PROD -**limits.fillInterval** | time interval | string | `1s` | only if `global.autoscaling` is true and `global.tier` is PROD +| Name | Description | Type | Default | Required | +|--------------------------|-------------------------------------------------|---------|---------|----------------------------------------------------------------| +| **limits.maxTokens** | maximum number of requests per fillInterval | integer | `150` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **limits.tokensPerFill** | number of new tokens allowed every fillInterval | integer | `150` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **limits.fillInterval** | time interval | string | `"1s"` | only if `global.autoscaling` is true and `global.tier` is PROD | + +### Methodology for Parameter Calculation variables: **hpa.targetValue**, **limits.maxTokens** and **limits.tokensPerFill** + +The parameters **hpa.targetValue**, **limits.maxTokens** and **limits.tokensPerFill** were determined through empirical testing during load testing. These tests were conducted using the N2D machine series, which can run on either AMD EPYC Milan or AMD EPYC Rome processors. The values were fine-tuned to ensure optimal performance under typical workloads. + +### Recommendations for New Instance Types + +When changing the instance type to a newer generation, such as the C3D series, it is essential to conduct new load testing. This ensures the parameters are recalibrated to match the performance characteristics of the new processor architecture, optimizing resource utilization and maintaining application stability. ## Install the Helm chart diff --git a/devops/gc/deploy/values.yaml b/devops/gc/deploy/values.yaml index f5c2a3c1dddad23cf27d559903a0cbcd26f6290d..04bf6cda337a22f7167e572aca23cfc2d0f28b82 100644 --- a/devops/gc/deploy/values.yaml +++ b/devops/gc/deploy/values.yaml @@ -45,7 +45,7 @@ hpa: minReplicas: 6 maxReplicas: 15 targetType: "AverageValue" - targetValue: 30 # rps*0.85*2 + targetValue: 200 behaviorScaleUpStabilizationWindowSeconds: 10 behaviorScaleUpPoliciesValue: 50 behaviorScaleUpPoliciesPeriodSeconds: 15 @@ -54,6 +54,6 @@ hpa: behaviorScaleDownPoliciesPeriodSeconds: 60 local_ratelimit: - max_tokens: 20 # rps - tokens_per_fill: 20 + max_tokens: 150 + tokens_per_fill: 150 fill_interval: "1s"