Allocation API
Throughout our API documentation, we use localhost:9090
as the default Kubecost URL, but your Kubecost instance may be exposed by a service or ingress. To reach Kubecost at port 9090, run: kubectl port-forward deployment/kubecost-cost-analyzer -n kubecost 9090
. When querying the cost-model container directly (ex. localhost:9003), the /model
part of the URI should be removed.
Allocation API
GET
http://<your-kubecost-address>/model/allocation
The Allocation API is the preferred way to query for costs and resources allocated to Kubernetes workloads and optionally aggregated by Kubernetes concepts like namespace
, controller
, and label
. Data is served from one of Kubecost's ETL pipelines.
Path Parameters
Name | Type | Description |
---|---|---|
window* | string | Duration of time over which to query. Accepts words like |
aggregate | string | Field by which to aggregate the results. Accepts: |
accumulate | boolean | If |
idle | boolean | If |
external | boolean | If |
filterClusters | string | Comma-separated list of clusters to match; e.g. |
filterNodes | string | Comma-separated list of nodes to match; e.g. |
filterNamespaces | string | Comma-separated list of namespaces to match; e.g. |
filterControllerKinds | string | Comma-separated list of controller kinds to match; e.g. |
filterControllers | string | Comma-separated list of controllers to match; e.g. |
filterPods | string | Comma-separated list of pods to match; e.g. |
filterAnnotations | string | Comma-separated list of annotations to match; e.g. |
filterLabels | string | Comma-separated list of annotations to match; e.g. |
filterServices | string | Comma-separated list of services to match; e.g. |
format | string | Set to |
costUnit | string | Cost metric format. Learn about cost metric calculations in our Allocations Dashboard doc. Supports |
shareIdle | boolean | If |
splitIdle | boolean | If |
idleByNode | boolean | If |
includeSharedCostBreakdown | boolean | Provides breakdown of cost metrics for any shared resources. Default is |
reconcile | boolean | If |
shareTenancyCosts | boolean | If |
shareNamespaces | string | Comma-separated list of namespaces to share; e.g. |
shareLabels | string | Comma-separated list of labels to share; e.g. |
shareCost | float | Floating-point value representing a monthly cost to share with the remaining non-idle, unshared allocations; e.g. |
shareSplit | string | Determines how to split shared costs among non-idle, unshared allocations. By default, the split will be |
step | string | Duration of each individual data metric across the |
Allocation API (Aggregator only)
GET
http://<your-kubecost-address>/model/allocation
The Allocation API is the preferred way to query for costs and resources allocated to Kubernetes workloads and optionally aggregated by Kubernetes concepts like namespace
, controller
, and label
. This Allocation API should only be consulted for users who have configured Kubecost Aggregator.
Path Parameters
Name | Type | Description |
---|---|---|
window* | string | Duration of time over which to query. Accepts words like |
aggregate | string | Field by which to aggregate the results. Accepts: |
accumulate | string | If |
idle | boolean | If |
external | boolean | If |
offset | int | Refers to the number of pages you are searching through which will increase by integers for the amount of pages you want to skip. Starting value is |
limit | int | Refers to the number of line items per page. Pair with the |
filter | string | Filter your results by any category which you can aggregate by, can support multiple filterable items in the same category in a comma-separated list. For example, to filter results by clusters A and B, use |
format | string | Set to |
format | string | Cost metric format. Learn about cost metric calculations in our Allocations Dashboard doc. Supports |
shareIdle | boolean | If |
splitIdle | boolean | If |
idleByNode | boolean | If |
includeSharedCostBreakdown | boolean | Provides breakdown of cost metrics for any shared resources. Default is |
reconcile | boolean | If |
shareTenancyCosts | boolean | If |
shareNamespaces | string | Comma-separated list of namespaces to share; e.g. |
shareLabels | string | Comma-separated list of labels to share; e.g. |
shareCost | float | Floating-point value representing a monthly cost to share with the remaining non-idle, unshared allocations; e.g. |
shareSplit | string | Determines how to split shared costs among non-idle, unshared allocations. By default, the split will be |
Allocation schema
Field | Description |
---|---|
name | Name of each relevant Kubernetes concept described by the allocation, delimited by slashes, e.g. "cluster/node/namespace/pod/container" |
properties | Map of name-to-value for all relevant property fields, including: |
window | Period of time over which the allocation is defined. |
start | Precise starting time of the allocation. By definition must be within the window. |
end | Precise ending time of the allocation. By definition must be within the window. |
minutes | Number of minutes running; i.e. the minutes from |
cpuCores | Average number of CPU cores allocated while running. |
cpuCoreRequestAverage | Average number of CPU cores requested while running. |
cpuCoreUsageAverage | Average number of CPU cores used while running. |
cpuCoreHours | Cumulative CPU core-hours allocated. |
cpuCost | Cumulative cost of allocated CPU core-hours. |
cpuCostAdjustment | Change in cost after allocated CPUs have been reconciled with updated node cost |
cpuEfficiency | Ratio of |
gpuCount | Number of GPUs allocated to the workload. |
gpuHours | Cumulative GPU-hours allocated. |
gpuCost | Cumulative cost of allocated GPU-hours. |
gpuCostAdjustment | Change in cost after allocated GPUs have been reconciled with updated node cost |
networkTransferBytes | Total bytes sent from the workload |
networkReceiveBytes | Total bytes received by the workload |
networkCost | Cumulative cost of network usage. |
networkCrossZoneCost | Cumulative cost of Cross-zone network egress usage. |
networkCrossRegionCost | Cumulative cost of Cross-region network egress usage. |
networkInternetCost | Cumulative cost of internet egress usage. |
networkCostAdjustment | Updated network cost |
loadBalancerCost | Cumulative cost of allocated load balancers. |
loadBalancerCostAdjustment | Updated load balancer cost. |
pvBytes | Average number of bytes of PersistentVolumes allocated while running. |
pvByteHours | Cumulative PersistentVolume byte-hours allocated. |
pvCost | Cumulative cost of allocated PersistentVolume byte-hours. |
pvs | Map of PersistentVolumeClaim costs that have been allocated to the workload |
pvCostAdjustment | Updated persistent volume cost. |
ramBytes | Average number of RAM bytes allocated. An allocated resource is the source of cost, according to Kubecost - regardless of if a requested resource is used. |
ramByteRequestAverage | Average of the RAM requested by the workload. Requests are a Kubernetes tool for preallocating/reserving resources for a given container. |
ramByteUsageAverage | Average of the RAM used by the workload. This comes from moment-to-moment measurements of live RAM byte usage of each container. This is roughly the number you see under RAM if you pull up Task Manager (Windows), top on Linux, or Activity Monitor (MacOS). |
ramByteHours | Cumulative RAM byte-hours allocated. |
ramCost | Cumulative cost of allocated RAM byte-hours. |
ramEfficiency | Ratio of |
sharedCost | Cumulative cost of shared resources, including shared namespaces, shared labels, shared overhead. |
externalCost | Cumulative cost of external resources. |
totalCost | Total cumulative cost |
totalEfficiency | Cost-weighted average of |
rawAllocationOnly | Object with fields |
Quick start
Request allocation data for each 24-hour period in the last three days, aggregated by namespace:
Querying for window=3d
should return a range of four sets because the queried range will overlap with four precomputed 24-hour sets, each aligned to the configured time zone. For example, querying window=3d
on 2021/01/04T12:00:00 will return:
2021/01/04 00:00:00 until 2021/01/04T12:00:00 (now)
2021/01/03 00:00:00 until 2021/01/04 00:00:00
2021/01/02 00:00:00 until 2021/01/03 00:00:00
2021/01/01 00:00:00 until 2021/01/02 00:00:00
See Querying for the full list of arguments and Examples for more example queries.
Special types of allocation
__idle__
refers to resources on a cluster that were not dedicated to a Kubernetes object (e.g. unused CPU core-hours on a node). An idle resource can be shared (proportionally or evenly) with the other allocations from the same cluster. (See the argumentshareIdle
.)__unallocated__
refers to aggregated allocations without the selectedaggregate
field; e.g. aggregating bylabel:app
might produce an__unallocated__
allocation composed of allocations without theapp
label.__unmounted__
(or "Unmounted PVs") refers to the resources used by PersistentVolumes that aren't mounted to a pod using a PVC, and thus cannot be allocated to a pod.
Query examples
Allocation data for today unaggregated:
Allocation data for last week, per day, aggregated by cluster:
Allocation data for the last 30 days, aggregated by the "app" label, sharing idle allocation, sharing allocations from two namespaces, sharing $100/mo in overhead, and accumulated into one allocation for the entire window:
Allocation data for 2021-03-10T00:00:00 to 2021-03-11T00:00:00 (i.e. 24h), multi-aggregated by namespace and the "app" label, filtering by properties.cluster == "cluster-one"
, and accumulated into one allocation for the entire window.
Allocation data for today, aggregated by annotation. See Enabling Annotation Emission to enable annotations.
Querying with /summary
endpoint to view condensed payload per line item
/summary
endpoint to view condensed payload per line item/summary
is an optional API endpoint which can be added to your Allocation query via .../model/allocation/summary?window=...
to provide a condensed list of your cost metrics per line item. Instead of returning the full list of schema values listed above, your query will return something like:
Querying with /topline
endpoint to view cost totals across query (Aggregator only)
/topline
endpoint to view cost totals across query (Aggregator only)/topline
is an optional API endpoint which can be added to your /summary
Allocation query via .../model/allocation/summary/topline?window=...
to provide a condensed overview of your total cost metrics including all line items sampled. You will receive a single list which sums the values per all items queried, formatted similar to a regular /summary
query, where numResults
displays the total number of items sampled. Idle costs still need to be configured separately.
Allocation of asset costs
Both the reconcile
and shareTenancyCosts
flags start processes that distribute the costs of Assets to Allocations related to them. For the reconcile
flag, these connections can be straightforward like the connection between a node Asset and an Allocation where the CPU, GPU, and RAM usage can be used to distribute a proportion of the node's cost to the Allocations that run on it. For Assets and Allocations where the connection is less well-defined, such as network Assets we have opted for a method of distributing the cost that we call Distribution by Usage Hours.
Distribution by Usage Hours takes the usage of the windows (start time and end time) of an Asset and all the Allocations connected to it and finds the number of hours that both the Allocation and Asset were running. The number of hours for each Allocation related to an Asset is called Alloc_Usage_Hours
. The sum of all Alloc_Usage_Hours
for a single Assets is Total_Usage_Hours
. With these values, an Assets cost is distributed to each connected Allocation using the formula Asset_Cos
t * Alloc_Usage_Hours/Total_Usage_Hours
. Depending on the Asset type an Allocation can receive proportions of multiple Asset Costs.
Asset types that use this distribution method include:
Network (
reconcile
): When the network pod is not enabled cost is distributed by usage hours. If the network pod is enabled cost is distributed to Allocations proportionally to usage.Load Balancer (
reconcile
)Cluster Management (
shareTenancyCosts
)Attached disks (
shareTenancyCosts
): Does not include PVs, which are handled byreconcile
Querying on-demand (experimental)
Querying on-demand with high resolution for long windows can cause serious Prometheus performance issues, including OOM errors. Start with short windows (1d
or less) and proceed with caution.
Computing allocation data on-demand allows for greater flexibility with respect to step size and accuracy-versus-performance. (See resolution
and error bounds for details.) Unlike the standard endpoint, which can only serve results from precomputed sets with predefined step sizes (e.g. 24h aligned to the UTC time zone), asking for a "7d" query will almost certainly result in 8 sets, including "today" and the final set, which might span 6.5d-7.5d ago. With this endpoint, however, you will be computing everything on-demand, so "7d" will return exactly seven days of data, starting at the moment the query is received. (You can still use window keywords like "today" and "lastweek", of course, which should align perfectly with the same queries of the standard ETL-driven endpoint.)
Additionally, unlike the standard endpoint, querying on-demand will not use reconciled asset costs. Therefore, the results returned will show all adjustments (e.g. CPU, GPU, RAM) to be 0.
Allocation On-Demand API
GET
http://<kubecost>/model/allocation/compute
Path Parameters
Name | Type | Description |
---|---|---|
window* | string | Duration of time over which to query. Accepts words like
|
resolution | string | Duration to use as resolution in Prometheus queries. Smaller values (i.e. higher resolutions) will provide better accuracy, but worse performance (i.e. slower query time, higher memory use). Larger values (i.e. lower resolutions) will perform better, but at the expense of lower accuracy for short-running workloads. See for details. Default is
. |
step | string | Duration of a single allocation set. If unspecified, this defaults to the |
aggregate | string | Field by which to aggregate the results. Accepts: |
accumulate | boolean | If |
On-demand query examples
Allocation data for the last 60m, in steps of 10m, with resolution 1m, aggregated by cluster.
Allocation data for the last 9d, in steps of 3d, with a 10m resolution, aggregated by namespace.
Theoretical error bounds
Tuning the resolution parameter allows the querier to make tradeoffs between accuracy and performance. For long-running pods (>1d) resolution can be tuned aggressively low (>10m) with relatively little effect on accuracy. However, even modestly low resolutions (5m) can result in significant accuracy degradation for short-running pods (<1h).
Here, we provide theoretical error bounds for different resolution values given pods of differing running durations. The tuple represents lower- and upper-bounds for accuracy as a percentage of the actual value. For example:
1.00, 1.00 means that results should always be accurate to less than 0.5% error
0.83, 1.00 means that results should never be high by more than 0.5% error, but could be low by as much as 17% error
-1.00, 10.00 means that the result could be as high as 1000% error (e.g. 30s pod being counted for 5m) or the pod could be missed altogether, i.e. -100% error.
resolution | 30s pod | 5m pod | 1h pod | 1d pod | 7d pod |
---|---|---|---|---|---|
1m | -1.00, 2.00 | 0.80, 1.00 | 0.98, 1.00 | 1.00, 1.00 | 1.00, 1.00 |
2m | -1.00, 4.00 | 0.80, 1.20 | 0.97, 1.00 | 1.00, 1.00 | 1.00, 1.00 |
5m | -1.00, 10.00 | -1.00, 1.00 | 0.92, 1.00 | 1.00, 1.00 | 1.00, 1.00 |
10m | -1.00, 20.00 | -1.00, 2.00 | 0.83, 1.00 | 0.99, 1.00 | 1.00, 1.00 |
30m | -1.00, 60.00 | -1.00, 6.00 | 0.50, 1.00 | 0.98, 1.00 | 1.00, 1.00 |
60m | -1.00, 120.00 | -1.00, 12.00 | -1.00, 1.00 | 0.96, 1.00 | 0.99, 1.00 |
Troubleshooting
Incomplete cost data for short window queries when using Thanos
While using Thanos, data can delayed from 1 to 3 hours, which may result in allocation queries retrieving inaccurate or incomplete data when using short window
intervals. Avoid using values for window
smaller than 5h
as a best practice.
Last updated