feat(T4.1-T4.4): implement advanced operations & analytics (part 1)

T4.1: Real-time Metrics Dashboard
- Add internal/dashboard package with MetricsAggregator
- Record, aggregate, and query metrics
- Percentile calculations (p50, p95, p99)
- Time-series data with max size eviction
- 13 metrics tests, all passing

T4.2: Workflow Visualization & DAG Rendering
- Add internal/visualization package with DAGRenderer
- Convert dependency graphs to DOT format
- Critical path highlighting
- Topological sorting with parallel task detection
- HTML rendering for visualization
- 11 DAG rendering tests, all passing

T4.3: Advanced Search & Filtering
- Add internal/search package with WorkflowSearch
- Full-text indexing with word-based lookup
- Filter by status, assignee, tag, date range
- Regex pattern matching
- Saved filters for reusable queries
- 15 search tests, all passing

T4.4: Cost Tracking & Optimization
- Add internal/cost package with CostTracker
- Track LLM API costs (by token)
- Track git operation costs
- Track compute resource costs (by duration)
- Cost aggregation by workflow/type
- Optimization recommendations
- 11 cost tests, all passing

Total T4.1-T4.4: 50 tests passing
Next: T4.5-T4.8 (alerting, profiling, multi-cluster, self-deployment)

internal/dashboard/metrics_aggregator.go

@@ -0,0 +1,203 @@
+package dashboard
+
+import (
+	"fmt"
+	"sort"
+	"sync"
+	"time"
+)
+
+// MetricSnapshot represents a point-in-time metric value
+type MetricSnapshot struct {
+	Timestamp time.Time
+	Value     float64
+	Name      string
+}
+
+// MetricsAggregator aggregates Prometheus metrics for dashboard display
+type MetricsAggregator struct {
+	mu       sync.RWMutex
+	metrics  map[string][]MetricSnapshot
+	ttl      time.Duration
+	maxSize  int
+}
+
+// NewMetricsAggregator creates a new metrics aggregator
+func NewMetricsAggregator(ttl time.Duration, maxSize int) *MetricsAggregator {
+	return &MetricsAggregator{
+		metrics:  make(map[string][]MetricSnapshot),
+		ttl:      ttl,
+		maxSize:  maxSize,
+	}
+}
+
+// Record records a metric value
+func (ma *MetricsAggregator) Record(name string, value float64) {
+	ma.mu.Lock()
+	defer ma.mu.Unlock()
+
+	snapshot := MetricSnapshot{
+		Timestamp: time.Now(),
+		Value:     value,
+		Name:      name,
+	}
+
+	ma.metrics[name] = append(ma.metrics[name], snapshot)
+
+	// Trim old entries
+	if len(ma.metrics[name]) > ma.maxSize {
+		ma.metrics[name] = ma.metrics[name][1:]
+	}
+}
+
+// GetTimeSeries retrieves metric time series
+func (ma *MetricsAggregator) GetTimeSeries(name string) []MetricSnapshot {
+	ma.mu.RLock()
+	defer ma.mu.RUnlock()
+
+	snapshots, exists := ma.metrics[name]
+	if !exists {
+		return []MetricSnapshot{}
+	}
+
+	result := make([]MetricSnapshot, len(snapshots))
+	copy(result, snapshots)
+	return result
+}
+
+// GetPercentile calculates percentile for a metric
+func (ma *MetricsAggregator) GetPercentile(name string, percentile float64) (float64, error) {
+	ma.mu.RLock()
+	defer ma.mu.RUnlock()
+
+	snapshots, exists := ma.metrics[name]
+	if !exists || len(snapshots) == 0 {
+		return 0, fmt.Errorf("metric not found: %s", name)
+	}
+
+	values := make([]float64, len(snapshots))
+	for i, s := range snapshots {
+		values[i] = s.Value
+	}
+
+	sort.Float64s(values)
+
+	index := int(float64(len(values)) * percentile / 100)
+	if index >= len(values) {
+		index = len(values) - 1
+	}
+
+	return values[index], nil
+}
+
+// GetAverage calculates average for a metric
+func (ma *MetricsAggregator) GetAverage(name string) (float64, error) {
+	ma.mu.RLock()
+	defer ma.mu.RUnlock()
+
+	snapshots, exists := ma.metrics[name]
+	if !exists || len(snapshots) == 0 {
+		return 0, fmt.Errorf("metric not found: %s", name)
+	}
+
+	sum := 0.0
+	for _, s := range snapshots {
+		sum += s.Value
+	}
+
+	return sum / float64(len(snapshots)), nil
+}
+
+// GetMax returns maximum value for a metric
+func (ma *MetricsAggregator) GetMax(name string) (float64, error) {
+	ma.mu.RLock()
+	defer ma.mu.RUnlock()
+
+	snapshots, exists := ma.metrics[name]
+	if !exists || len(snapshots) == 0 {
+		return 0, fmt.Errorf("metric not found: %s", name)
+	}
+
+	max := snapshots[0].Value
+	for _, s := range snapshots {
+		if s.Value > max {
+			max = s.Value
+		}
+	}
+
+	return max, nil
+}
+
+// GetMin returns minimum value for a metric
+func (ma *MetricsAggregator) GetMin(name string) (float64, error) {
+	ma.mu.RLock()
+	defer ma.mu.RUnlock()
+
+	snapshots, exists := ma.metrics[name]
+	if !exists || len(snapshots) == 0 {
+		return 0, fmt.Errorf("metric not found: %s", name)
+	}
+
+	min := snapshots[0].Value
+	for _, s := range snapshots {
+		if s.Value < min {
+			min = s.Value
+		}
+	}
+
+	return min, nil
+}
+
+// GetMetricNames returns all recorded metric names
+func (ma *MetricsAggregator) GetMetricNames() []string {
+	ma.mu.RLock()
+	defer ma.mu.RUnlock()
+
+	names := make([]string, 0, len(ma.metrics))
+	for name := range ma.metrics {
+		names = append(names, name)
+	}
+
+	return names
+}
+
+// GetLatest returns the latest snapshot for a metric
+func (ma *MetricsAggregator) GetLatest(name string) (MetricSnapshot, error) {
+	ma.mu.RLock()
+	defer ma.mu.RUnlock()
+
+	snapshots, exists := ma.metrics[name]
+	if !exists || len(snapshots) == 0 {
+		return MetricSnapshot{}, fmt.Errorf("metric not found: %s", name)
+	}
+
+	return snapshots[len(snapshots)-1], nil
+}
+
+// Clear clears all metrics
+func (ma *MetricsAggregator) Clear() {
+	ma.mu.Lock()
+	defer ma.mu.Unlock()
+
+	ma.metrics = make(map[string][]MetricSnapshot)
+}
+
+// GetCountInRange returns count of metrics within a time range
+func (ma *MetricsAggregator) GetCountInRange(name string, start, end time.Time) (int, error) {
+	ma.mu.RLock()
+	defer ma.mu.RUnlock()
+
+	snapshots, exists := ma.metrics[name]
+	if !exists {
+		return 0, fmt.Errorf("metric not found: %s", name)
+	}
+
+	count := 0
+	for _, s := range snapshots {
+		if s.Timestamp.After(start) && s.Timestamp.Before(end) {
+			count++
+		}
+	}
+
+	return count, nil
+}