dt-obs-services

# Application Services Skill Monitor application service performance, health, and runtime-specific metrics using DQL. --- ## Core Capabilities ### 1. Service Performance (RED Metrics) Monitor service **Rate, Errors, Duration** using metrics-based timeseries queries. **Key Metrics:** - `dt.service.request.response_time` - Response time (microseconds) - `dt.service.request.count` - Request count - `dt.service.request.failure_count` - Failed request count **Common Use Cases:** - Response time monitoring (avg, p50, p95, p99) - Error rate tracking and spike detection - Traffic analysis (throughput, peaks, growth) - Performance degradation detection - Multi-cluster comparison **Quick Example:** ```dql timeseries { p95 = percentile(dt.service.request.response_time, 95), total_requests = sum(dt.service.request.count), failures = sum(dt.service.request.failure_count) }, by: {dt.service.name} | fieldsAdd p95_ms = p95[] / 1000, error_rate_pct = (failures[] * 100.0) / total_requests[] ``` → **For detailed queries:** See [references/service-metrics.md](references/service-metrics.md) ### 2. Advanced Service Analysis Span-based queries for complex scenarios requiring flexible filtering and custom aggregations. **Use Cases:** - SLA compliance tracking with custom thresholds - Service health scoring (multi-dimensional) - Operation/endpoint-level performance analysis - Custom error classification - Failure pattern detection with error details **Quick Example:** ```dql fetch ...