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Container Request Right Sizing Recommendation API (V2)

GET http://<kubecost-address>/model/savings/requestSizingV2

The container request right sizing recommendation API provides recommendations for container resource requests based on configurable parameters and estimates the savings from implementing those recommendations on a per-container, per-controller level. If the cluster-level resources stay static, then there may not be significant savings from applying Kubecost's recommendations until you reduce your cluster resources. Instead, your idle allocation will increase.

Query Parameters

Name

Type

Description

[
    {
        "clusterID": "...",
        "namespace": "...",
        "controllerKind": "...",
        "controllerName": "...",
        "containerName": "...",
        "recommendedRequest": {
            "cpu": "00m",
            "memory": "00Mi"
        },
        "monthlySavings": {
            "cpu": 0.00,
            "memory": 0.00
        },
        "latestKnownRequest": {
            "cpu": "00m",
            "memory": "00Mi"
        },
        "currentEfficiency": {
            "cpu": 0.00,
            "memory": 0.00,
            "total": 0.00
        }
    }
]

API examples

KUBECOST_ADDRESS='http://localhost:9090/model'

curl -G \
  -d 'algorithmCPU=quantile' \
  -d 'qCPU=0.95' \
  -d 'algorithmRAM=max' \
  -d 'targetCPUUtilization=0.8' \
  -d 'targetRAMUtilization=0.8' \
  -d 'window=3d' \
  --data-urlencode 'filter=namespace:"kubecost"+container:"cost-model"' \
  ${KUBECOST_ADDRESS}/savings/requestSizingV2

Querying with `/topline` endpoint to view cost totals across query (Aggregator only)

/topline is an optional API endpoint which can be added to your right-sizing query via .../savings/RequestSizingV2/topline... to provide a condensed overview of all items sampled. TotalMonthlySavings is the total estimated savings value from adopting right-sizing recommendations. Count refers to the number of items sampled. Recommendations should return null, as it is unable to provide a universal right-sizing recommendation.

{
    "TotalMonthlySavings": ,
    "Count": ,
    "Recommendations": null 
}

Recommendation methodology

The "base" recommendation is calculated from the observed usage of each resource per unique container spec (e.g. a 2-replica, 3-container deployment will have 3 recommendations: one for each container spec).

Say you have a single-container deployment with two replicas: A and B.

A's container had peak usages of 120 mCPU and 300 MiB of RAM.
B's container had peak usages of 800 mCPU and 120 MiB of RAM.

The max algorithm recommendation for the deployment's container will be 800 mCPU and 300 MiB of RAM. Overhead will be added to the base recommendation according to the target utilization parameters as described above.

Applying your request sizing recommendations

After providing you with right sizing recommendations, Kubecost can additionally directly implement these recommendations into your environment. For more information, see the Container Request Recommendation Apply/Plan APIs doc.

Savings projection methodology

See V1 docs.

Container Request Right Sizing Recommendation API (V2)

GET http://<kubecost-address>/model/savings/requestSizingV2

Query Parameters

Name

Type

Description

[
    {
        "clusterID": "...",
        "namespace": "...",
        "controllerKind": "...",
        "controllerName": "...",
        "containerName": "...",
        "recommendedRequest": {
            "cpu": "00m",
            "memory": "00Mi"
        },
        "monthlySavings": {
            "cpu": 0.00,
            "memory": 0.00
        },
        "latestKnownRequest": {
            "cpu": "00m",
            "memory": "00Mi"
        },
        "currentEfficiency": {
            "cpu": 0.00,
            "memory": 0.00,
            "total": 0.00
        }
    }
]

API examples

KUBECOST_ADDRESS='http://localhost:9090/model'

curl -G \
  -d 'algorithmCPU=quantile' \
  -d 'qCPU=0.95' \
  -d 'algorithmRAM=max' \
  -d 'targetCPUUtilization=0.8' \
  -d 'targetRAMUtilization=0.8' \
  -d 'window=3d' \
  --data-urlencode 'filter=namespace:"kubecost"+container:"cost-model"' \
  ${KUBECOST_ADDRESS}/savings/requestSizingV2

Querying with `/topline` endpoint to view cost totals across query (Aggregator only)

{
    "TotalMonthlySavings": ,
    "Count": ,
    "Recommendations": null 
}

Recommendation methodology

Say you have a single-container deployment with two replicas: A and B.

A's container had peak usages of 120 mCPU and 300 MiB of RAM.
B's container had peak usages of 800 mCPU and 120 MiB of RAM.

Applying your request sizing recommendations

Savings projection methodology

See V1 docs.

The algorithm to be used to calculate CPU recommendations based on historical CPU usage data. Options are max and quantile. Max recommendations are based on the maximum-observed usage in window. Quantile recommendations are based on a quantile of observed usage in window (requires the qCPU parameter to set the desired quantile). Defaults to max. To use the quantile algorithm, the ContainerStats Pipeline must be enabled.

Container Request Right Sizing Recommendation API (V2)