diff --git a/devops/gc/deploy/README.md b/devops/gc/deploy/README.md index 96e921c15ce10b61cef5574fb945f306a2ebeb23..fb2ae1d1b3abf2efe799f954758231d02e193511 100644 --- a/devops/gc/deploy/README.md +++ b/devops/gc/deploy/README.md @@ -83,26 +83,34 @@ 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 | `10` | only if `global.autoscaling` is true and `global.tier` is PROD | -| **hpa.maxReplicas** | maximum number of replicas | integer | `20` | 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 | `40` | 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 | `20` | 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 | `45` | 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 | `25` | only if `global.autoscaling` is true and `global.tier` is PROD | -| **limits.tokensPerFill** | number of new tokens allowed every fillInterval | integer | `25` | 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 | +|--------------------------|-------------------------------------------------|---------|--------|----------------------------------------------------------------| +| **limits.maxTokens** | maximum number of requests per fillInterval | integer | `30` | only if `global.autoscaling` is true and `global.tier` is PROD | +| **limits.tokensPerFill** | number of new tokens allowed every fillInterval | integer | `30` | 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 9532491585f2fc8393ea9d27030d300d62fc6d96..5cb0ca592ae22a5fcf1b4d50ae33a2c0db8b7932 100644 --- a/devops/gc/deploy/values.yaml +++ b/devops/gc/deploy/values.yaml @@ -44,10 +44,10 @@ istio: proxyMemoryLimit: "256Mi" hpa: - minReplicas: 10 + minReplicas: 6 maxReplicas: 20 targetType: "AverageValue" - targetValue: 40 # rps*0.85*2 + targetValue: 45 behaviorScaleUpStabilizationWindowSeconds: 10 behaviorScaleUpPoliciesValue: 50 behaviorScaleUpPoliciesPeriodSeconds: 15 @@ -56,6 +56,6 @@ hpa: behaviorScaleDownPoliciesPeriodSeconds: 60 local_ratelimit: - max_tokens: 25 # rps - tokens_per_fill: 25 + max_tokens: 30 + tokens_per_fill: 30 fill_interval: "1s"