Introduce support for the resource metrics API

This introduces support for the resource metrics in the adapter.
The individual queries and window sizes are fully customizable via a new
config section.  This uses just the generic machinery from
metrics-server to serve the API.

pkg/config/config.go

@@ -1,11 +1,16 @@
 package config
 
+import (
+	pmodel "github.com/prometheus/common/model"
+)
+
 type MetricsDiscoveryConfig struct {
 	// Rules specifies how to discover and map Prometheus metrics to
 	// custom metrics API resources.  The rules are applied independently,
 	// and thus must be mutually exclusive.  Rules will the same SeriesQuery
 	// will make only a single API call.
-	Rules []DiscoveryRule `yaml:"rules"`
+	Rules         []DiscoveryRule `yaml:"rules"`
+	ResourceRules *ResourceRules  `yaml:"resourceRules,omitempty"`
 }
 
 // DiscoveryRule describes on set of rules for transforming Prometheus metrics to/from
@@ -73,3 +78,31 @@ type NameMapping struct {
 	// if only one is present, and will error if multiple are.
 	As string `yaml:"as"`
 }
+
+// ResourceRules describe the rules for querying resource metrics
+// API results.  It's assumed that the same metrics can be used
+// to aggregate across different resources.
+type ResourceRules struct {
+	CPU    ResourceRule `yaml:"cpu"`
+	Memory ResourceRule `yaml:"memory"`
+	// Window is the window size reported by the resource metrics API.  It should match the value used
+	// in your containerQuery and nodeQuery if you use a `rate` function.
+	Window pmodel.Duration `yaml:"window"`
+}
+
+// ResourceRule describes how to query metrics for some particular
+// system resource metric.
+type ResourceRule struct {
+	// Container is the query used to fetch the metrics for containers.
+	ContainerQuery string `yaml:"containerQuery"`
+	// NodeQuery is the query used to fetch the metrics for nodes
+	// (for instance, simply aggregating by node label is insufficient for
+	// cadvisor metrics -- you need to select the `/` container).
+	NodeQuery string `yaml:"nodeQuery"`
+	// Resources specifies how associated Kubernetes resources should be discovered for
+	// the given metrics.
+	Resources ResourceMapping `yaml:"resources"`
+	// ContainerLabel indicates the name of the Prometheus label containing the container name
+	// (since "container" is not a resource, this can't go in the `resources` block, but is similar).
+	ContainerLabel string `yaml:"containerLabel"`
+}

pkg/resourceprovider/provider.go

@@ -0,0 +1,385 @@
+/*
+Copyright 2018 The Kubernetes Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+*/
+
+package resourceprovider
+
+import (
+	"context"
+	"fmt"
+	"sync"
+	"time"
+
+	"github.com/golang/glog"
+	"github.com/kubernetes-incubator/metrics-server/pkg/provider"
+	corev1 "k8s.io/api/core/v1"
+	apimeta "k8s.io/apimachinery/pkg/api/meta"
+	"k8s.io/apimachinery/pkg/api/resource"
+	"k8s.io/apimachinery/pkg/runtime/schema"
+	apitypes "k8s.io/apimachinery/pkg/types"
+	metrics "k8s.io/metrics/pkg/apis/metrics"
+
+	"github.com/directxman12/k8s-prometheus-adapter/pkg/client"
+	"github.com/directxman12/k8s-prometheus-adapter/pkg/config"
+	"github.com/directxman12/k8s-prometheus-adapter/pkg/naming"
+	pmodel "github.com/prometheus/common/model"
+)
+
+var (
+	nodeResource = schema.GroupResource{Resource: "nodes"}
+	nsResource   = schema.GroupResource{Resource: "ns"}
+	podResource  = schema.GroupResource{Resource: "pods"}
+)
+
+// TODO(directxman12): consider support for nanocore values -- adjust scale if less than 1 millicore, or greater than max int64
+
+// newResourceQuery instantiates query information from the give configuration rule for querying
+// resource metrics for some resource.
+func newResourceQuery(cfg config.ResourceRule, mapper apimeta.RESTMapper) (resourceQuery, error) {
+	converter, err := naming.NewResourceConverter(cfg.Resources.Template, cfg.Resources.Overrides, mapper)
+	if err != nil {
+		return resourceQuery{}, fmt.Errorf("unable to construct label-resource converter: %v", err)
+	}
+
+	contQuery, err := naming.NewMetricsQuery(cfg.ContainerQuery, converter)
+	if err != nil {
+		return resourceQuery{}, fmt.Errorf("unable to construct container metrics query: %v", err)
+	}
+	nodeQuery, err := naming.NewMetricsQuery(cfg.NodeQuery, converter)
+	if err != nil {
+		return resourceQuery{}, fmt.Errorf("unable to construct node metrics query: %v", err)
+	}
+
+	return resourceQuery{
+		converter:      converter,
+		contQuery:      contQuery,
+		nodeQuery:      nodeQuery,
+		containerLabel: cfg.ContainerLabel,
+	}, nil
+
+}
+
+// resourceQuery represents query information for querying resource metrics for some resource,
+// like CPU or memory.
+type resourceQuery struct {
+	converter      naming.ResourceConverter
+	contQuery      naming.MetricsQuery
+	nodeQuery      naming.MetricsQuery
+	containerLabel string
+}
+
+// NewProvider constructs a new MetricsProvider to provide resource metrics from Prometheus using the given rules.
+func NewProvider(prom client.Client, mapper apimeta.RESTMapper, cfg *config.ResourceRules) (provider.MetricsProvider, error) {
+	cpuQuery, err := newResourceQuery(cfg.CPU, mapper)
+	if err != nil {
+		return nil, fmt.Errorf("unable to construct querier for CPU metrics: %v", err)
+	}
+	memQuery, err := newResourceQuery(cfg.Memory, mapper)
+	if err != nil {
+		return nil, fmt.Errorf("unable to construct querier for memory metrics: %v", err)
+	}
+
+	return &resourceProvider{
+		prom:   prom,
+		cpu:    cpuQuery,
+		mem:    memQuery,
+		window: time.Duration(cfg.Window),
+	}, nil
+}
+
+// resourceProvider is a MetricsProvider that contacts Prometheus to provide
+// the resource metrics.
+type resourceProvider struct {
+	prom client.Client
+
+	cpu, mem resourceQuery
+
+	window time.Duration
+}
+
+// nsQueryResults holds the results of one set
+// of queries necessary to construct a resource metrics
+// API response for a single namespace.
+type nsQueryResults struct {
+	namespace string
+	cpu, mem  queryResults
+	err       error
+}
+
+func (p *resourceProvider) GetContainerMetrics(pods ...apitypes.NamespacedName) ([]provider.TimeInfo, [][]metrics.ContainerMetrics, error) {
+	if len(pods) == 0 {
+		return nil, nil, fmt.Errorf("no pods to fetch metrics for")
+	}
+
+	// TODO(directxman12): figure out how well this scales if we go to list 1000+ pods
+	// (and consider adding timeouts)
+
+	// group pods by namespace (we could be listing for all pods in the cluster)
+	podsByNs := make(map[string][]string, len(pods))
+	for _, pod := range pods {
+		podsByNs[pod.Namespace] = append(podsByNs[pod.Namespace], pod.Name)
+	}
+
+	// actually fetch the results for each namespace
+	now := pmodel.Now()
+	resChan := make(chan nsQueryResults, len(podsByNs))
+	var wg sync.WaitGroup
+	wg.Add(len(podsByNs))
+
+	for ns, podNames := range podsByNs {
+		go func(ns string, podNames []string) {
+			defer wg.Done()
+			resChan <- p.queryBoth(now, podResource, ns, podNames...)
+		}(ns, podNames)
+	}
+
+	wg.Wait()
+	close(resChan)
+
+	// index those results in a map for easy lookup
+	resultsByNs := make(map[string]nsQueryResults, len(podsByNs))
+	for result := range resChan {
+		if result.err != nil {
+			glog.Errorf("unable to fetch metrics for pods in namespace %q, skipping: %v", result.namespace, result.err)
+			continue
+		}
+		resultsByNs[result.namespace] = result
+	}
+
+	// convert the unorganized per-container results into results grouped
+	// together by namespace, pod, and container
+	resTimes := make([]provider.TimeInfo, len(pods))
+	resMetrics := make([][]metrics.ContainerMetrics, len(pods))
+	for i, pod := range pods {
+		p.assignForPod(pod, resultsByNs, &resMetrics[i], &resTimes[i])
+	}
+
+	return resTimes, resMetrics, nil
+}
+
+// assignForPod takes the resource metrics for all containers in the given pod
+// from resultsByNs, and places them in MetricsProvider response format in resMetrics,
+// also recording the earliest time in resTime.  It will return without operating if
+// any data is missing.
+func (p *resourceProvider) assignForPod(pod apitypes.NamespacedName, resultsByNs map[string]nsQueryResults, resMetrics *[]metrics.ContainerMetrics, resTime *provider.TimeInfo) {
+	// check to make sure everything is present
+	nsRes, nsResPresent := resultsByNs[pod.Namespace]
+	if !nsResPresent {
+		glog.Errorf("unable to fetch metrics for pods in namespace %q, skipping pod %s", pod.Namespace, pod.String())
+		return
+	}
+	cpuRes, hasResult := nsRes.cpu[pod.Name]
+	if !hasResult {
+		glog.Errorf("unable to fetch CPU metrics for pod %s, skipping", pod.String())
+		return
+	}
+	memRes, hasResult := nsRes.mem[pod.Name]
+	if !hasResult {
+		glog.Errorf("unable to fetch memory metrics for pod %s, skipping", pod.String())
+		return
+	}
+
+	earliestTs := pmodel.Latest
+	containerMetrics := make(map[string]metrics.ContainerMetrics)
+
+	// organize all the CPU results
+	for _, cpu := range cpuRes {
+		containerName := string(cpu.Metric[pmodel.LabelName(p.cpu.containerLabel)])
+		if _, present := containerMetrics[containerName]; !present {
+			containerMetrics[containerName] = metrics.ContainerMetrics{
+				Name:  containerName,
+				Usage: corev1.ResourceList{},
+			}
+		}
+		containerMetrics[containerName].Usage[corev1.ResourceCPU] = *resource.NewMilliQuantity(int64(cpu.Value*1000.0), resource.DecimalSI)
+		if cpu.Timestamp.Before(earliestTs) {
+			earliestTs = cpu.Timestamp
+		}
+	}
+
+	// organize the memory results
+	for _, mem := range memRes {
+		containerName := string(mem.Metric[pmodel.LabelName(p.mem.containerLabel)])
+		if _, present := containerMetrics[containerName]; !present {
+			containerMetrics[containerName] = metrics.ContainerMetrics{
+				Name:  containerName,
+				Usage: corev1.ResourceList{},
+			}
+		}
+		containerMetrics[containerName].Usage[corev1.ResourceMemory] = *resource.NewMilliQuantity(int64(mem.Value*1000.0), resource.BinarySI)
+		if mem.Timestamp.Before(earliestTs) {
+			earliestTs = mem.Timestamp
+		}
+	}
+
+	// store the time in the final format
+	*resTime = provider.TimeInfo{
+		Timestamp: earliestTs.Time(),
+		Window:    p.window,
+	}
+
+	// store the container metrics in the final format
+	containerMetricsList := make([]metrics.ContainerMetrics, 0, len(containerMetrics))
+	for _, containerMetric := range containerMetrics {
+		containerMetricsList = append(containerMetricsList, containerMetric)
+	}
+	*resMetrics = containerMetricsList
+}
+
+func (p *resourceProvider) GetNodeMetrics(nodes ...string) ([]provider.TimeInfo, []corev1.ResourceList, error) {
+	if len(nodes) == 0 {
+		return nil, nil, fmt.Errorf("no nodes to fetch metrics for")
+	}
+
+	now := pmodel.Now()
+
+	// run the actual query
+	qRes := p.queryBoth(now, nodeResource, "", nodes...)
+	if qRes.err != nil {
+		return nil, nil, qRes.err
+	}
+
+	resTimes := make([]provider.TimeInfo, len(nodes))
+	resMetrics := make([]corev1.ResourceList, len(nodes))
+
+	// organize the results
+	for i, nodeName := range nodes {
+		// skip if any data is missing
+		rawCPUs, gotResult := qRes.cpu[nodeName]
+		if !gotResult {
+			glog.V(1).Infof("missing CPU for node %q, skipping", nodeName)
+			continue
+		}
+		rawMems, gotResult := qRes.mem[nodeName]
+		if !gotResult {
+			glog.V(1).Infof("missing memory for node %q, skipping", nodeName)
+			continue
+		}
+
+		rawMem := rawMems[0]
+		rawCPU := rawCPUs[0]
+
+		// store the results
+		resMetrics[i] = corev1.ResourceList{
+			corev1.ResourceCPU:    *resource.NewMilliQuantity(int64(rawCPU.Value*1000.0), resource.DecimalSI),
+			corev1.ResourceMemory: *resource.NewMilliQuantity(int64(rawMem.Value*1000.0), resource.BinarySI),
+		}
+
+		// use the earliest timestamp available (in order to be conservative
+		// when determining if metrics are tainted by startup)
+		if rawMem.Timestamp.Before(rawCPU.Timestamp) {
+			resTimes[i] = provider.TimeInfo{
+				Timestamp: rawMem.Timestamp.Time(),
+				Window:    p.window,
+			}
+		} else {
+			resTimes[i] = provider.TimeInfo{
+				Timestamp: rawCPU.Timestamp.Time(),
+				Window:    1 * time.Minute,
+			}
+		}
+	}
+
+	return resTimes, resMetrics, nil
+}
+
+// queryBoth queries for both CPU and memory metrics on the given
+// Kubernetes API resource (pods or nodes), and errors out if
+// either query fails.
+func (p *resourceProvider) queryBoth(now pmodel.Time, resource schema.GroupResource, namespace string, names ...string) nsQueryResults {
+	var cpuRes, memRes queryResults
+	var cpuErr, memErr error
+
+	var wg sync.WaitGroup
+	wg.Add(2)
+	go func() {
+		defer wg.Done()
+		cpuRes, cpuErr = p.runQuery(now, p.cpu, resource, "", names...)
+	}()
+	go func() {
+		defer wg.Done()
+		memRes, memErr = p.runQuery(now, p.mem, resource, "", names...)
+	}()
+	wg.Wait()
+
+	if cpuErr != nil {
+		return nsQueryResults{
+			namespace: namespace,
+			err:       fmt.Errorf("unable to fetch node CPU metrics: %v", cpuErr),
+		}
+	}
+	if memErr != nil {
+		return nsQueryResults{
+			namespace: namespace,
+			err:       fmt.Errorf("unable to fetch node memory metrics: %v", memErr),
+		}
+	}
+
+	return nsQueryResults{
+		namespace: namespace,
+		cpu:       cpuRes,
+		mem:       memRes,
+	}
+}
+
+// queryResults maps an object name to all the results matching that object
+type queryResults map[string][]*pmodel.Sample
+
+// runQuery actually queries Prometheus for the metric represented by the given query information, on
+// the given Kubernetes API resource (pods or nodes).
+func (p *resourceProvider) runQuery(now pmodel.Time, queryInfo resourceQuery, resource schema.GroupResource, namespace string, names ...string) (queryResults, error) {
+	var query client.Selector
+	var err error
+
+	// build the query, which needs the special "container" group by if this is for pod metrics
+	if resource == nodeResource {
+		query, err = queryInfo.nodeQuery.Build("", resource, namespace, nil, names...)
+	} else {
+		extraGroupBy := []string{queryInfo.containerLabel}
+		query, err = queryInfo.contQuery.Build("", resource, namespace, extraGroupBy, names...)
+	}
+	if err != nil {
+		return nil, fmt.Errorf("unable to construct query: %v", err)
+	}
+
+	// run the query
+	rawRes, err := p.prom.Query(context.Background(), now, query)
+	if err != nil {
+		return nil, fmt.Errorf("unable to execute query: %v", err)
+	}
+
+	if rawRes.Type != pmodel.ValVector || rawRes.Vector == nil {
+		return nil, fmt.Errorf("invalid or empty value of non-vector type (%s) returned", rawRes.Type)
+	}
+
+	// check the appropriate label for the resource in question
+	resourceLbl, err := queryInfo.converter.LabelForResource(resource)
+	if err != nil {
+		return nil, fmt.Errorf("unable to find label for resource %s: %v", resource.String(), err)
+	}
+
+	// associate the results back to each given pod or node
+	res := make(queryResults, len(*rawRes.Vector))
+	for _, val := range *rawRes.Vector {
+		if val == nil {
+			// skip empty values
+			continue
+		}
+		resKey := string(val.Metric[resourceLbl])
+		res[resKey] = append(res[resKey], val)
+	}
+
+	return res, nil
+}