feat: add TTFT/ITL metrics for LLM inference
CI / CI (pull_request) Failing after 2m13s

- RecordTTFT: Time-to-First-Token in milliseconds
- RecordITL: Inter-Token Latency in milliseconds
- RecordTokenCount: Track total tokens generated
- Prometheus exporter for /metrics endpoint
- Grafana dashboard ConfigMap (llm-metrics.json)
- ResponseWriterWrapper to capture metrics during LLM calls
- Metrics exported: llm_ttft_seconds, llm_itl_seconds, llm_tokens_total
This commit is contained in:
Admin Bot
2026-09-14 22:33:32 +09:00
parent 6608f1a8d5
commit 44ec3502dc
6 changed files with 922 additions and 17 deletions
+118
View File
@@ -28,6 +28,14 @@ type Metrics struct {
// Streaming metrics
streamingResponsesTotal map[string]int64
streamingByteCount map[string]int64
// LLM inference metrics (TTFT and ITL)
// ttftMs: Time-to-First-Token in milliseconds
ttftMs map[string][]int64 // samples for histogram
// itlMs: Inter-Token Latency in milliseconds
itlMs map[string][]int64 // samples for histogram
// Token counts
tokenCount map[string]int64
}
// NewMetrics creates a new Metrics instance.
@@ -41,6 +49,9 @@ func NewMetrics() *Metrics {
upstreamHealth: make(map[string]int),
streamingResponsesTotal: make(map[string]int64),
streamingByteCount: make(map[string]int64),
ttftMs: make(map[string][]int64),
itlMs: make(map[string][]int64),
tokenCount: make(map[string]int64),
}
}
@@ -146,9 +157,113 @@ func (m *Metrics) GetMetrics() map[string]interface{} {
"upstream_health": m.upstreamHealth,
"streaming_responses_total": m.streamingResponsesTotal,
"streaming_byte_count": m.streamingByteCount,
"llm_ttft_ms": m.ttftMs,
"llm_itl_ms": m.itlMs,
"llm_token_count": m.tokenCount,
}
}
// RecordTTFT records Time-to-First-Token in milliseconds
func (m *Metrics) RecordTTFT(model string, ttftMs int64) {
m.mu.Lock()
defer m.mu.Unlock()
key := fmt.Sprintf("llm:ttft:%s", model)
m.ttftMs[key] = append(m.ttftMs[key], ttftMs)
}
// RecordITL records Inter-Token Latency in milliseconds
func (m *Metrics) RecordITL(model string, itlMs int64) {
m.mu.Lock()
defer m.mu.Unlock()
key := fmt.Sprintf("llm:itl:%s", model)
m.itlMs[key] = append(m.itlMs[key], itlMs)
}
// RecordTokenCount records number of tokens in response
func (m *Metrics) RecordTokenCount(model string, count int64) {
m.mu.Lock()
defer m.mu.Unlock()
key := fmt.Sprintf("llm:tokens:%s", model)
m.tokenCount[key] += count
}
// GetTTFTMetrics returns TTFT statistics for Prometheus export
func (m *Metrics) GetTTFTMetrics() map[string]interface{} {
m.mu.RLock()
defer m.mu.RUnlock()
result := make(map[string]interface{})
for key, samples := range m.ttftMs {
if len(samples) > 0 {
result[key] = map[string]interface{}{
"count": len(samples),
"sum": sumInt64(samples),
"avg": sumInt64(samples) / int64(len(samples)),
"min": minInt64(samples),
"max": maxInt64(samples),
}
}
}
return result
}
// GetITLMetrics returns ITL statistics for Prometheus export
func (m *Metrics) GetITLMetrics() map[string]interface{} {
m.mu.RLock()
defer m.mu.RUnlock()
result := make(map[string]interface{})
for key, samples := range m.itlMs {
if len(samples) > 0 {
result[key] = map[string]interface{}{
"count": len(samples),
"sum": sumInt64(samples),
"avg": sumInt64(samples) / int64(len(samples)),
"min": minInt64(samples),
"max": maxInt64(samples),
}
}
}
return result
}
func sumInt64(vals []int64) int64 {
var s int64
for _, v := range vals {
s += v
}
return s
}
func minInt64(vals []int64) int64 {
if len(vals) == 0 {
return 0
}
min := vals[0]
for _, v := range vals {
if v < min {
min = v
}
}
return min
}
func maxInt64(vals []int64) int64 {
if len(vals) == 0 {
return 0
}
max := vals[0]
for _, v := range vals {
if v > max {
max = v
}
}
return max
}
// Reset clears all metrics (for testing).
func (m *Metrics) Reset() {
m.mu.Lock()
@@ -162,4 +277,7 @@ func (m *Metrics) Reset() {
m.upstreamHealth = make(map[string]int)
m.streamingResponsesTotal = make(map[string]int64)
m.streamingByteCount = make(map[string]int64)
m.ttftMs = make(map[string][]int64)
m.itlMs = make(map[string][]int64)
m.tokenCount = make(map[string]int64)
}