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Add documentation for CRI container metrics
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# Container Runtime Interface: Container Metrics | ||
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[Container runtime interface | ||
(CRI)](https://github.com/kubernetes/community/blob/master/contributors/devel/container-runtime-interface.md) | ||
provides an abstraction for container runtimes to integrate with Kubernetes. | ||
CRI expects the runtime to provide resource usage statistics for the | ||
containers. | ||
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## Background | ||
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Historically Kubelet relied on the [cAdvisor](https://github.com/google/cadvisor) | ||
library, an open-source project hosted in a separate repository, to retrieve | ||
container metrics such as CPU and memory usage. These metrics are then aggregated | ||
and exposed through Kubelet's [Summary | ||
API](https://github.com/kubernetes/kubernetes/blob/master/pkg/kubelet/apis/stats/v1alpha1/types.go) | ||
for the monitoring pipeline (and other components) to consume. Any container | ||
runtime (e.g., Docker and Rkt) integrated with Kubernetes needed to add a | ||
corresponding package in cAdvisor to support tracking container and image file | ||
system metrics. | ||
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With CRI being the new abstraction for integration, it was a natural | ||
progression to augment CRI to serve container metrics to eliminate a separate | ||
integration point. | ||
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*See the [core metrics design | ||
proposal](https://github.com/kubernetes/community/blob/master/contributors/design-proposals/core-metrics-pipeline.md) | ||
for more information on metrics exposed by Kubelet, and [monitoring | ||
architecture](https://github.com/kubernetes/community/blob/master/contributors/design-proposals/monitoring_architecture.md) | ||
for the evolving monitoring pipeline in Kubernetes.* | ||
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# Container Metrics | ||
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Kubelet is responsible for creating pod-level cgroups based on the Quality of | ||
Service class to which the pod belongs, and passes this as a parent cgroup to the | ||
runtime so that it can ensure all resources used by the pod (e.g., pod sandbox, | ||
containers) will be charged to the cgroup. Therefore, Kubelet has the ability | ||
to track resource usage at the pod level (using the built-in cAdvisor), and the | ||
API enhancement focuses on the container-level metrics. | ||
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We include the only a set of metrics that are necessary to fulfill the needs of | ||
Kubelet. As the requirements evolve over time, we may extend the API to support | ||
more metrics. Below is the API with the metrics supported today. | ||
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```go | ||
// ContainerStats returns stats of the container. If the container does not | ||
// exist, the call returns an error. | ||
rpc ContainerStats(ContainerStatsRequest) returns (ContainerStatsResponse) {} | ||
// ListContainerStats returns stats of all running containers. | ||
rpc ListContainerStats(ListContainerStatsRequest) returns (ListContainerStatsResponse) {} | ||
``` | ||
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```go | ||
// ContainerStats provides the resource usage statistics for a container. | ||
message ContainerStats { | ||
// Information of the container. | ||
ContainerAttributes attributes = 1; | ||
// CPU usage gathered from the container. | ||
CpuUsage cpu = 2; | ||
// Memory usage gathered from the container. | ||
MemoryUsage memory = 3; | ||
// Usage of the writable layer. | ||
FilesystemUsage writable_layer = 4; | ||
} | ||
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// CpuUsage provides the CPU usage information. | ||
message CpuUsage { | ||
// Timestamp in nanoseconds at which the information were collected. Must be > 0. | ||
int64 timestamp = 1; | ||
// Cumulative CPU usage (sum across all cores) since object creation. | ||
UInt64Value usage_core_nano_seconds = 2; | ||
} | ||
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// MemoryUsage provides the memory usage information. | ||
message MemoryUsage { | ||
// Timestamp in nanoseconds at which the information were collected. Must be > 0. | ||
int64 timestamp = 1; | ||
// The amount of working set memory in bytes. | ||
UInt64Value working_set_bytes = 2; | ||
} | ||
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// FilesystemUsage provides the filesystem usage information. | ||
message FilesystemUsage { | ||
// Timestamp in nanoseconds at which the information were collected. Must be > 0. | ||
int64 timestamp = 1; | ||
// The underlying storage of the filesystem. | ||
StorageIdentifier storage_id = 2; | ||
// UsedBytes represents the bytes used for images on the filesystem. | ||
// This may differ from the total bytes used on the filesystem and may not | ||
// equal CapacityBytes - AvailableBytes. | ||
UInt64Value used_bytes = 3; | ||
// InodesUsed represents the inodes used by the images. | ||
// This may not equal InodesCapacity - InodesAvailable because the underlying | ||
// filesystem may also be used for purposes other than storing images. | ||
UInt64Value inodes_used = 4; | ||
} | ||
``` | ||
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There are three categories or resources: CPU, memory, and filesystem. Each of | ||
the resource usage message includes a timestamp to indicate when the usage | ||
statistics is collected. This is necessary because some resource usage (e.g., | ||
filesystem) are inherently more expensive to collect and may be updated less | ||
frequently than others. Having the timestamp allows the consumer to know how | ||
stale/fresh the data is, while giving the runtime flexibility to adjust. | ||
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Although CRI does not dictate the frequency of the stats update, Kubelet needs | ||
a minimum guarantee of freshness of the stats for certain resources so that it | ||
can reclaim them timely when under pressure. We will formulate the requirements | ||
for any of such resources and include them in CRI in the near future. | ||
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*For more details on why we request cached stats with timestamps as opposed to | ||
requesting stats on-demand, here is the [rationale](https://github.com/kubernetes/kubernetes/pull/45614#issuecomment-302258090) | ||
behind it.* | ||
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## Status | ||
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The container metrics calls are added to CRI in Kubernetes 1.7, but Kubelet does not | ||
yet use it to gather metrics from the runtime. We plan to enable Kubelet to | ||
optionally consume the container metrics from the API in 1.8. | ||
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