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| 1 | +// Copyright 2025 The Cockroach Authors. |
| 2 | +// |
| 3 | +// Use of this software is governed by the CockroachDB Software License |
| 4 | +// included in the /LICENSE file. |
| 5 | + |
| 6 | +package load |
| 7 | + |
| 8 | +import ( |
| 9 | + "context" |
| 10 | + "time" |
| 11 | + |
| 12 | + "github.com/VividCortex/ewma" |
| 13 | + "github.com/cockroachdb/cockroach/pkg/roachpb" |
| 14 | + "github.com/cockroachdb/cockroach/pkg/server/status" |
| 15 | + "github.com/cockroachdb/cockroach/pkg/util/buildutil" |
| 16 | + "github.com/cockroachdb/cockroach/pkg/util/log" |
| 17 | + "github.com/cockroachdb/cockroach/pkg/util/stop" |
| 18 | + "github.com/cockroachdb/cockroach/pkg/util/syncutil" |
| 19 | + "github.com/cockroachdb/errors" |
| 20 | +) |
| 21 | + |
| 22 | +// StoresStatsAggregator provides aggregated cpu usage stats across all stores. |
| 23 | +type StoresStatsAggregator interface { |
| 24 | + // GetAggregatedStoreStats returns the total cpu usage across all stores and |
| 25 | + // the count of stores. If useCached is true, it uses the cached store |
| 26 | + // descriptor instead of computing new ones. Implemented by Stores. |
| 27 | + GetAggregatedStoreStats(useCached bool) (aggregatedCPUUsage int64, totalStoreCount int32) |
| 28 | +} |
| 29 | + |
| 30 | +// NodeCapacityProvider reports node-level cpu usage and capacity by sampling |
| 31 | +// runtime stats and aggregating store-level cpu capacity across all stores. It |
| 32 | +// is used by Store to populate the NodeCapacity field in the StoreDescriptor. |
| 33 | +type NodeCapacityProvider struct { |
| 34 | + stores StoresStatsAggregator |
| 35 | + runtimeLoadMonitor *runtimeLoadMonitor |
| 36 | +} |
| 37 | + |
| 38 | +// NewNodeCapacityProvider creates a new NodeCapacityProvider that monitors CPU |
| 39 | +// metrics using the provided stores aggregator. The optional knobs parameter |
| 40 | +// allows customizing refresh intervals for testing. |
| 41 | +func NewNodeCapacityProvider( |
| 42 | + stopper *stop.Stopper, stores StoresStatsAggregator, knobs *NodeCapacityProviderTestingKnobs, |
| 43 | +) *NodeCapacityProvider { |
| 44 | + if stopper == nil || stores == nil { |
| 45 | + panic("programming error: stopper or stores aggregator cannot be nil") |
| 46 | + } |
| 47 | + |
| 48 | + // refreshIntervals define how frequently cpu metrics are updated. |
| 49 | + const ( |
| 50 | + // defaultCPUUsageRefreshInterval controls how often cpu usage measurements |
| 51 | + // are taken. |
| 52 | + defaultCPUUsageRefreshInterval = time.Second |
| 53 | + // defaultCPUCapacityRefreshInterval controls how often the total CPU |
| 54 | + // capacity of the node is re-calculated. This is less frequent than usage |
| 55 | + // since capacity changes happen less often. |
| 56 | + defaultCPUCapacityRefreshInterval = 10 * time.Second |
| 57 | + ) |
| 58 | + |
| 59 | + // defaultMovingAverageAge defines the effective time window size. With a |
| 60 | + // value of 20, the 20th-to-last measurement contributes meaningfully to the |
| 61 | + // average, while earlier measurements have diminishing impact. |
| 62 | + const defaultMovingAverageAge = 20 |
| 63 | + |
| 64 | + usageInterval := defaultCPUUsageRefreshInterval |
| 65 | + capacityInterval := defaultCPUCapacityRefreshInterval |
| 66 | + if knobs != nil { |
| 67 | + usageInterval = knobs.CpuUsageRefreshInterval |
| 68 | + capacityInterval = knobs.CpuCapacityRefreshInterval |
| 69 | + } |
| 70 | + |
| 71 | + monitor := &runtimeLoadMonitor{ |
| 72 | + stopper: stopper, |
| 73 | + usageRefreshInterval: usageInterval, |
| 74 | + capacityRefreshInterval: capacityInterval, |
| 75 | + } |
| 76 | + monitor.mu.usageEWMA = ewma.NewMovingAverage(defaultMovingAverageAge) |
| 77 | + monitor.recordCPUCapacity(context.Background()) |
| 78 | + return &NodeCapacityProvider{ |
| 79 | + stores: stores, |
| 80 | + runtimeLoadMonitor: monitor, |
| 81 | + } |
| 82 | +} |
| 83 | + |
| 84 | +// Run starts the background monitoring of cpu metrics. |
| 85 | +func (n *NodeCapacityProvider) Run(ctx context.Context) { |
| 86 | + _ = n.runtimeLoadMonitor.stopper.RunAsyncTask(ctx, "runtime-load-monitor", func(ctx context.Context) { |
| 87 | + n.runtimeLoadMonitor.run(ctx) |
| 88 | + }) |
| 89 | +} |
| 90 | + |
| 91 | +// GetNodeCapacity returns the NodeCapacity which node-level cpu usage and |
| 92 | +// capacity and aggregated store-level cpu usage. If useCached is true, it will |
| 93 | +// use cached store descriptors to aggregate the sum of store-level cpu |
| 94 | +// capacity. |
| 95 | +func (n *NodeCapacityProvider) GetNodeCapacity(useCached bool) roachpb.NodeCapacity { |
| 96 | + storesCPURate, numStores := n.stores.GetAggregatedStoreStats(useCached) |
| 97 | + // TODO(wenyihu6): may be unexpected to caller that useCached only applies to |
| 98 | + // the stores stats but not runtime load monitor. We can change |
| 99 | + // runtimeLoadMonitor to also fetch updated stats. |
| 100 | + // TODO(wenyihu6): NodeCPURateCapacity <= NodeCPURateUsage fails on CI and |
| 101 | + // requires more investigation. |
| 102 | + cpuUsageNanoPerSec, cpuCapacityNanoPerSec := n.runtimeLoadMonitor.GetCPUStats() |
| 103 | + return roachpb.NodeCapacity{ |
| 104 | + StoresCPURate: storesCPURate, |
| 105 | + NumStores: numStores, |
| 106 | + NodeCPURateCapacity: cpuCapacityNanoPerSec, |
| 107 | + NodeCPURateUsage: cpuUsageNanoPerSec, |
| 108 | + } |
| 109 | +} |
| 110 | + |
| 111 | +// runtimeLoadMonitor polls cpu usage and capacity stats of the node |
| 112 | +// periodically and maintaining a moving average. |
| 113 | +type runtimeLoadMonitor struct { |
| 114 | + usageRefreshInterval time.Duration |
| 115 | + capacityRefreshInterval time.Duration |
| 116 | + stopper *stop.Stopper |
| 117 | + |
| 118 | + mu struct { |
| 119 | + syncutil.Mutex |
| 120 | + // lastTotalUsageNanos tracks cumulative cpu usage in nanoseconds using |
| 121 | + // status.GetProcCPUTime. |
| 122 | + lastTotalUsageNanos float64 |
| 123 | + // usageEWMA maintains a moving average of delta cpu usage between two |
| 124 | + // subsequent polls in nanoseconds. The cpu usage is obtained by polling |
| 125 | + // stats from status.GetProcCPUTime which is cumulative. |
| 126 | + usageEWMA ewma.MovingAverage |
| 127 | + // logicalCPUsPerSec represents the node's cpu capacity in logical |
| 128 | + // CPU-seconds per second, obtained from status.GetCPUCapacity. |
| 129 | + logicalCPUsPerSec int64 |
| 130 | + } |
| 131 | +} |
| 132 | + |
| 133 | +// GetCPUStats returns the current cpu usage and capacity stats for the node. |
| 134 | +func (m *runtimeLoadMonitor) GetCPUStats() (cpuUsageNanoPerSec int64, cpuCapacityNanoPerSec int64) { |
| 135 | + m.mu.Lock() |
| 136 | + defer m.mu.Unlock() |
| 137 | + // usageEWMA is usage in nanoseconds. Divide by refresh interval to get the |
| 138 | + // per-second nano-sec rate. |
| 139 | + cpuUsageNanoPerSec = int64(m.mu.usageEWMA.Value() / m.usageRefreshInterval.Seconds()) |
| 140 | + // logicalCPUsPerSec is in logical cpu-seconds per second. Convert the unit |
| 141 | + // from cpu-seconds to cpu-nanoseconds. |
| 142 | + cpuCapacityNanoPerSec = m.mu.logicalCPUsPerSec * time.Second.Nanoseconds() |
| 143 | + return |
| 144 | +} |
| 145 | + |
| 146 | +// recordCPUUsage samples and records the current cpu usage of the node. |
| 147 | +func (m *runtimeLoadMonitor) recordCPUUsage(ctx context.Context) { |
| 148 | + m.mu.Lock() |
| 149 | + defer m.mu.Unlock() |
| 150 | + userTimeMillis, sysTimeMillis, err := status.GetProcCPUTime(ctx) |
| 151 | + if err != nil { |
| 152 | + if buildutil.CrdbTestBuild { |
| 153 | + panic(err) |
| 154 | + } |
| 155 | + // TODO(wenyihu6): we should revisit error handling here for production. |
| 156 | + log.Warningf(ctx, "failed to get cpu usage: %v", err) |
| 157 | + } |
| 158 | + // Convert milliseconds to nanoseconds. |
| 159 | + totalUsageNanos := float64(userTimeMillis*1e6 + sysTimeMillis*1e6) |
| 160 | + if buildutil.CrdbTestBuild && m.mu.lastTotalUsageNanos > totalUsageNanos { |
| 161 | + panic(errors.Newf("programming error: last cpu usage is larger than current: %v > %v", |
| 162 | + m.mu.lastTotalUsageNanos, totalUsageNanos)) |
| 163 | + } |
| 164 | + m.mu.usageEWMA.Add(totalUsageNanos - m.mu.lastTotalUsageNanos) |
| 165 | + m.mu.lastTotalUsageNanos = totalUsageNanos |
| 166 | +} |
| 167 | + |
| 168 | +// recordCPUCapacity samples and records the current cpu capacity of the node. |
| 169 | +func (m *runtimeLoadMonitor) recordCPUCapacity(ctx context.Context) { |
| 170 | + m.mu.Lock() |
| 171 | + defer m.mu.Unlock() |
| 172 | + m.mu.logicalCPUsPerSec = int64(status.GetCPUCapacity()) |
| 173 | + if m.mu.logicalCPUsPerSec == 0 { |
| 174 | + if buildutil.CrdbTestBuild { |
| 175 | + panic("programming error: cpu capacity is 0") |
| 176 | + } |
| 177 | + // TODO(wenyihu6): we should pass in an actual context here. |
| 178 | + log.Warningf(ctx, "failed to get cpu capacity") |
| 179 | + } |
| 180 | +} |
| 181 | + |
| 182 | +// run is the main loop of the RuntimeLoadMonitor and periodically polls the cpu |
| 183 | +// usage and capacity. It continues to run until the context is done or the |
| 184 | +// stopper is quiesced. |
| 185 | +func (m *runtimeLoadMonitor) run(ctx context.Context) { |
| 186 | + usageTimer := time.NewTicker(m.usageRefreshInterval) |
| 187 | + defer usageTimer.Stop() |
| 188 | + capacityTimer := time.NewTicker(m.capacityRefreshInterval) |
| 189 | + defer capacityTimer.Stop() |
| 190 | + |
| 191 | + for { |
| 192 | + select { |
| 193 | + case <-ctx.Done(): |
| 194 | + return |
| 195 | + case <-m.stopper.ShouldQuiesce(): |
| 196 | + return |
| 197 | + case <-usageTimer.C: |
| 198 | + usageTimer.Reset(m.usageRefreshInterval) |
| 199 | + m.recordCPUUsage(ctx) |
| 200 | + case <-capacityTimer.C: |
| 201 | + capacityTimer.Reset(m.capacityRefreshInterval) |
| 202 | + m.recordCPUCapacity(ctx) |
| 203 | + } |
| 204 | + } |
| 205 | +} |
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