diff --git a/devops/gc/deploy/README.md b/devops/gc/deploy/README.md index 1631e70678fdd36d1e86a57b897371a9ac3effd5..528d4c526f566bb8385b74750c4d9ca8f33da815 100644 --- a/devops/gc/deploy/README.md +++ b/devops/gc/deploy/README.md @@ -93,26 +93,34 @@ First you need to set variables in **values.yaml** file using any code editor. S ### 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 | `120` | 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 | `100` | 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 | `70` | only if `global.autoscaling` is true and `global.tier` is PROD -**limits.tokensPerFill** | number of new tokens allowed every fillInterval | integer | `70` | 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 | `100` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **limits.tokensPerFill** | number of new tokens allowed every fillInterval | integer | `100` | 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 df9ba53019c4cbe506b3e4c52c061c371fd00dcb..12a31dae9c7b15613853c93155cee93cfb65b15a 100644 --- a/devops/gc/deploy/values.yaml +++ b/devops/gc/deploy/values.yaml @@ -43,7 +43,7 @@ hpa: minReplicas: 6 maxReplicas: 15 targetType: "AverageValue" - targetValue: 120 # rps*0.85*2 + targetValue: 100 behaviorScaleUpStabilizationWindowSeconds: 10 behaviorScaleUpPoliciesValue: 50 behaviorScaleUpPoliciesPeriodSeconds: 15 @@ -52,6 +52,6 @@ hpa: behaviorScaleDownPoliciesPeriodSeconds: 60 local_ratelimit: - max_tokens: 70 # rps - tokens_per_fill: 70 + max_tokens: 75 + tokens_per_fill: 75 fill_interval: "1s"