diff --git a/contributors/devel/cri-container-stats.md b/contributors/devel/cri-container-stats.md new file mode 100644 index 00000000000..b44cfdbf3b2 --- /dev/null +++ b/contributors/devel/cri-container-stats.md @@ -0,0 +1,121 @@ +# Container Runtime Interface: Container Metrics + +[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. + +## Background + +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. + +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. + +*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.* + +# Container Metrics + +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. + + +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. + +```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) {} +``` + +```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; +} + +// 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; +} + +// 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; +} + +// 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; +} +``` + +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. + +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. + + +*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.* + +## Status + +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. +