nntrivi2001
57dc91585d
Internal SmartGift build of a Claude Code monitoring dashboard. Lanes: a durable unit of parallel agent work, one per working directory, tracked across session restarts. Managed lanes are git worktrees the dashboard provisions and can reset or remove behind a three-check destroy guard and a counted preflight; adopted lanes are directories you already own and are never destroyable. Pipelines: a lane moves through pipeline stages. A stage the agent declares with evidence renders green; a stage inferred from the tool-event stream renders dashed amber and never counts as done. Detection is forward-only within a 30-minute window, and never writes the declared stage. Workspace: one page at /run with a lane grid, the selected lane's pipeline, and a full Claude console behind a disclosure.
246 lines
8.8 KiB
YAML
246 lines
8.8 KiB
YAML
# ─────────────────────────────────────────────────────────────────────────────
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# Coralogix Custom Dashboard – Agent Monitor
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#
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# Import via Coralogix UI: Dashboards → Custom Dashboards → Import
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# Or via API:
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# curl -X POST "https://api.coralogix.com/api/v1/external/grafana/api/dashboards/db" \
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# -H "Authorization: Bearer $CORALOGIX_API_KEY" \
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# -H "Content-Type: application/json" \
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# -d @dashboards.yaml
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#
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# This dashboard mirrors the Grafana dashboard (../grafana/dashboards/) while
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# leveraging Coralogix-native features: DataPrime queries, log correlation,
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# distributed tracing waterfall, and Apdex scoring.
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# ─────────────────────────────────────────────────────────────────────────────
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dashboard:
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name: "Agent Monitor – Operations"
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description: "Claude Code Agent Monitor: real-time operations, SLOs, and infrastructure health"
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folder: "Agent Monitor"
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tags:
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- agent-monitor
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- operations
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- sre
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# ── Row 1: Overview ──────────────────────────────────────────────────────
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rows:
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- name: "Overview"
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panels:
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- title: "Active Sessions"
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type: line-chart
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query:
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type: metrics
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promql: 'agent_monitor_active_sessions'
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legend: "{{namespace}}"
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span: 4
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- title: "Request Rate (req/s)"
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type: line-chart
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query:
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type: metrics
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promql: 'sum(rate(http_requests_total{job="agent-monitor"}[5m]))'
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legend: "Requests/sec"
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span: 4
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- title: "WebSocket Connections"
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type: line-chart
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query:
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type: metrics
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promql: 'websocket_connections_active{job="agent-monitor"}'
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legend: "{{pod}}"
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span: 4
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# ── Row 2: HTTP Performance ────────────────────────────────────────────
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- name: "HTTP Performance"
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panels:
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- title: "Latency Distribution (P50 / P95 / P99)"
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type: line-chart
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query:
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type: metrics
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promql: |
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histogram_quantile(0.50, sum(rate(http_request_duration_seconds_bucket{job="agent-monitor"}[5m])) by (le))
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histogram_quantile(0.95, sum(rate(http_request_duration_seconds_bucket{job="agent-monitor"}[5m])) by (le))
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histogram_quantile(0.99, sum(rate(http_request_duration_seconds_bucket{job="agent-monitor"}[5m])) by (le))
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span: 6
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- title: "Error Rate (%)"
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type: line-chart
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query:
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type: metrics
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promql: |
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sum(rate(http_requests_total{job="agent-monitor", status=~"5.."}[5m]))
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/
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sum(rate(http_requests_total{job="agent-monitor"}[5m])) * 100
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legend: "5xx %"
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thresholds:
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- value: 1
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color: yellow
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- value: 5
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color: red
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span: 3
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- title: "Status Code Distribution"
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type: bar-chart
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query:
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type: metrics
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promql: 'sum by (status) (increase(http_requests_total{job="agent-monitor"}[1h]))'
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span: 3
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# ── Row 3: Logs (DataPrime) ────────────────────────────────────────────
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- name: "Application Logs"
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panels:
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- title: "Error Logs"
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type: dataprime
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query: |
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source logs
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| filter $d.cx.application.name == 'agent-monitor'
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| filter $d.severity == 'ERROR' || $d.severity == 'FATAL'
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| select $m.timestamp, $d.k8s.pod.name, $d.message
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| order by $m.timestamp desc
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| limit 100
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span: 6
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- title: "Log Volume by Severity"
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type: bar-chart
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query:
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type: dataprime
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expression: |
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source logs
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| filter $d.cx.application.name == 'agent-monitor'
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| count_group_by $d.severity as count
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span: 3
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- title: "Hook Event Throughput"
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type: line-chart
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query:
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type: dataprime
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expression: |
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source logs
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| filter $d.cx.application.name == 'agent-monitor'
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| filter $d.message matches 'hook.*event'
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| count_per_time 1m as throughput
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span: 3
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# ── Row 4: Infrastructure ──────────────────────────────────────────────
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- name: "Infrastructure"
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panels:
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- title: "CPU Usage (%)"
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type: line-chart
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query:
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type: metrics
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promql: |
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rate(container_cpu_usage_seconds_total{
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namespace=~"agent-monitor.*",
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container="agent-monitor"
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}[5m]) * 100
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legend: "{{pod}}"
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span: 4
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- title: "Memory Usage (MiB)"
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type: line-chart
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query:
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type: metrics
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promql: |
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container_memory_working_set_bytes{
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namespace=~"agent-monitor.*",
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container="agent-monitor"
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} / 1024 / 1024
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legend: "{{pod}}"
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span: 4
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- title: "Pod Status"
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type: gauge
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query:
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type: metrics
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promql: |
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count by (phase) (
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kube_pod_status_phase{namespace=~"agent-monitor.*"}
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)
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span: 4
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# ── Row 5: Database & Storage ──────────────────────────────────────────
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- name: "Database & Storage"
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panels:
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- title: "SQLite Query Duration (ms)"
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type: line-chart
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query:
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type: metrics
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promql: 'sqlite_query_duration_seconds{job="agent-monitor"} * 1000'
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span: 4
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- title: "PV Usage (%)"
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type: gauge
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query:
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type: metrics
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promql: |
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(kubelet_volume_stats_used_bytes{namespace=~"agent-monitor.*"}
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/ kubelet_volume_stats_capacity_bytes{namespace=~"agent-monitor.*"}) * 100
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thresholds:
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- value: 70
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color: yellow
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- value: 90
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color: red
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span: 4
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- title: "Network I/O (bytes/s)"
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type: line-chart
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query:
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type: metrics
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promql: |
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sum by (pod) (rate(container_network_receive_bytes_total{namespace=~"agent-monitor.*"}[5m]))
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sum by (pod) (rate(container_network_transmit_bytes_total{namespace=~"agent-monitor.*"}[5m]))
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span: 4
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# ── Row 6: SLO Tracking ────────────────────────────────────────────────
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- name: "SLO Tracking"
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panels:
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- title: "Availability SLO (99.9% target)"
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type: gauge
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query:
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type: metrics
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promql: |
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(1 - sum(rate(http_requests_total{job="agent-monitor", status=~"5.."}[30d]))
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/ sum(rate(http_requests_total{job="agent-monitor"}[30d]))) * 100
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thresholds:
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- value: 99.9
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color: green
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- value: 99.5
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color: yellow
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- value: 99.0
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color: red
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span: 4
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- title: "Latency SLO (P95 < 500ms)"
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type: gauge
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query:
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type: metrics
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promql: |
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histogram_quantile(0.95,
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sum(rate(http_request_duration_seconds_bucket{job="agent-monitor"}[30d])) by (le)
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) * 1000
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thresholds:
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- value: 300
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color: green
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- value: 500
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color: yellow
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- value: 1000
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color: red
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span: 4
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- title: "Error Budget Remaining"
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type: gauge
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query:
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type: metrics
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promql: |
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(0.001 - sum(rate(http_requests_total{job="agent-monitor", status=~"5.."}[30d]))
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/ sum(rate(http_requests_total{job="agent-monitor"}[30d])))
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/ 0.001 * 100
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thresholds:
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- value: 50
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color: green
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- value: 25
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color: yellow
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- value: 0
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color: red
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span: 4
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