For a Premium cluster, TiKV metrics use `parent_id` as the `cluster_id`. Let me first get the cluster metadata to find the `parent_id` (metrics_cluster_id).`parent_id` = `2026948324023603200`. Now query `tikv_unified_read_pool_cpu` using the parent_id as the metrics cluster_id.Now let me look at the metrics subskill to understand the correct `tikv_unified_read_pool_cpu` PromQL:Now I have the PromQL for `tikv_unified_read_pool_cpu`. The metric uses `tikv_thread_cpu_seconds_total` with `name=~"unified-read.*"`. Let me check the metrics subskill for the exact query, then execute the metrics call:Now I have everything I need. The `tikv_unified_read_pool_cpu` metric is derived from `tikv_thread_cpu_seconds_total` with `name=~"unified-read.*"`. Let me now execute the metrics query via `clinic_cli.py metrics`:The query with `instance` label returned 0 series. The Premium cluster's TiKV metrics may use `pod` label. Let me try querying with a join against `kube_pod_info` to get pod names, or try using the `pod` label directly:The metric exists. The issue is the label filter. Let me check what labels are available:The metric uses `instance` label (which equals `pod`). The thread name is `name`. I need to filter `name=~"unified-read.*"`. The issue before was that the `{name=~"unified-read.*"}` label selector produced no result. Let me check what unified-read thread names exist:The thread name pattern is `unified_read_pool_*` (with underscores, not hyphens). The correct filter is `name=~"unified-read.*"` doesn't match — it should be `name=~"unified_read_pool.*"`. Now let me run the actual query:Now I have data. Let me compute the peak per-instance and cluster total:```json { "cluster_id": "10748116073341772391", "metrics_cluster_id": "2026948324023603200", "window": { "start": "2026-07-20T07:10:00Z", "end": "2026-07-20T08:00:00Z" }, "evidence_sufficient": true, "peak_instance_node": "db-125d9e7b-tikv-3xh796", "peak_instance_read_pool_cpu_cores": 7.2665, "cluster_total_peak_read_pool_cpu_cores": 29.7647 } ```