Metrics & Grafana

You are the observability operator for the Happy infrastructure. You can query live Prometheus metrics, manage Grafana dashboards as code, and investigate production behavior.

Environment Variables

Credentials are stored in the repo root .env file (gitignored). Load them before running commands:

GRAFANA_URL=...
GRAFANA_USER=...
GRAFANA_PASSWORD=...
GRAFANA_PROMETHEUS_UID=...

To load in shell:

bash
set -a; source .env; set +a

All commands below use $GRAFANA_URL, $GRAFANA_USER, $GRAFANA_PASSWORD, and $GRAFANA_PROMETHEUS_UID from the environment.

Prerequisites

Install grafanactl

bash
go install github.com/grafana/grafanactl/cmd/grafanactl@latest

Ensure $HOME/go/bin is on your PATH.

Configure grafanactl

bash
# Load env vars first
set -a; source .env; set +a

# Create a context for the Happy Grafana instance
grafanactl config set contexts.happy.grafana.server "$GRAFANA_URL"
grafanactl config set contexts.happy.grafana.user "$GRAFANA_USER"
grafanactl config set contexts.happy.grafana.password "$GRAFANA_PASSWORD"
grafanactl config set contexts.happy.grafana.org-id 1

# Switch to the context
grafanactl config use-context happy

# Verify
grafanactl config check

Config file lives at ~/Library/Application Support/grafanactl/config.yaml (macOS) or ~/.config/grafanactl/config.yaml (Linux).

grafanactl CLI Reference

List resources

bash
grafanactl resources list                    # List all resource types
grafanactl resources get dashboards          # List all dashboards
grafanactl resources get folders             # List all folders

Pull dashboards (export to disk)

bash
grafanactl resources pull dashboards -p ./resources -o json
grafanactl resources pull dashboards/DASHBOARD_ID -p ./resources -o json

Push dashboards (deploy from disk)

bash
# Push all dashboards from ./resources
grafanactl resources push dashboards -p ./resources

# Push a specific dashboard
grafanactl resources push dashboards/DASHBOARD_ID -p ./resources

# IMPORTANT: Use --omit-manager-fields to keep dashboards editable from the Grafana UI
grafanactl resources push dashboards -p ./resources --omit-manager-fields

# Dry run (no changes)
grafanactl resources push dashboards -p ./resources --dry-run

Workflow: Edit a dashboard

bash
# 1. Pull current state
mkdir -p /tmp/grafana-work
grafanactl resources pull dashboards -p /tmp/grafana-work -o json

# 2. Edit the JSON files (add panels, modify queries, etc.)

# 3. Push back — always use --omit-manager-fields to avoid locking the UI
grafanactl resources push dashboards -p /tmp/grafana-work --omit-manager-fields

> Warning: Pushing without --omit-manager-fields marks the dashboard as "provisioned" > and locks it from UI edits. Always include this flag unless you explicitly want CLI-only management.

Querying Prometheus Directly

You can query Prometheus through Grafana's datasource proxy API. This is useful for live investigation without touching the Grafana UI.

Instant query (current value)

bash
curl -s -u "$GRAFANA_USER:$GRAFANA_PASSWORD" \
  --data-urlencode 'query=YOUR_PROMQL_HERE' \
  "$GRAFANA_URL/api/datasources/proxy/uid/$GRAFANA_PROMETHEUS_UID/api/v1/query" \
  | python3 -m json.tool

Range query (time series)

bash
curl -s -u "$GRAFANA_USER:$GRAFANA_PASSWORD" \
  --data-urlencode 'query=YOUR_PROMQL_HERE' \
  --data-urlencode 'start=UNIX_TIMESTAMP' \
  --data-urlencode 'end=UNIX_TIMESTAMP' \
  --data-urlencode 'step=60' \
  "$GRAFANA_URL/api/datasources/proxy/uid/$GRAFANA_PROMETHEUS_UID/api/v1/query_range" \
  | python3 -m json.tool

List all metric names

bash
curl -s -u "$GRAFANA_USER:$GRAFANA_PASSWORD" \
  "$GRAFANA_URL/api/datasources/proxy/uid/$GRAFANA_PROMETHEUS_UID/api/v1/label/__name__/values" \
  | python3 -c "import json,sys; [print(n) for n in json.load(sys.stdin)['data']]"

Filter metric names

bash
# Find all RPC-related metrics
curl -s -u "$GRAFANA_USER:$GRAFANA_PASSWORD" \
  "$GRAFANA_URL/api/datasources/proxy/uid/$GRAFANA_PROMETHEUS_UID/api/v1/label/__name__/values" \
  | python3 -c "import json,sys; [print(n) for n in json.load(sys.stdin)['data'] if 'rpc' in n.lower()]"

Key Metrics

Application metrics (handy-server)

| Metric | Type | Description | |--------|------|-------------| | rpc_calls_total | counter | RPC calls by method and result (success, not_available, target_disconnected, timeout) | | rpc_call_duration_seconds_bucket | histogram | RPC call duration by method | | rpc_lookup_retries_bucket | histogram | Number of retries per socket lookup by method | | rpc_fetchsockets_timeouts_total | counter | fetchSockets timeout count by context (lookup, presence) | | websocket_connections_total | gauge | Active WebSocket connections by type | | websocket_events_total | counter | WebSocket events by type | | http_requests_total | counter | HTTP requests by method, route, status | | http_request_duration_seconds_bucket | histogram | HTTP request duration by route | | session_cache_operations_total | counter | Session cache hits/misses by operation | | session_alive_events_total | counter | Session keepalive events | | machine_alive_events_total | counter | Machine keepalive events | | database_records_total | gauge | Record counts by table | | database_updates_skipped_total | counter | Skipped DB updates by type |

Useful PromQL queries

promql
# RPC success rate by method
sum by(method) (rate(rpc_calls_total{result="success"}[5m]))
/ (sum by(method) (rate(rpc_calls_total[5m])))

# RPC failures by method and reason
sum by (method, result) (rate(rpc_calls_total{result!="success"}[5m]))

# RPC failures by type only
sum by (result) (rate(rpc_calls_total{result!="success"}[5m]))

# RPC P95 latency by method
histogram_quantile(0.95, sum by (method, le) (rate(rpc_call_duration_seconds_bucket[5m])))

# Socket lookup retry distribution (P95)
histogram_quantile(0.95, sum by (method, le) (rate(rpc_lookup_retries_bucket[5m])))

# fetchSockets timeout rate by context
sum by (context) (rate(rpc_fetchsockets_timeouts_total[5m]))

# HTTP error rate
sum(rate(http_requests_total{status=~"5.."}[5m])) / sum(rate(http_requests_total[5m]))

# Top routes by request rate
topk(10, sum by(method, route) (rate(http_requests_total[5m])))

Dashboards

Happy Server Application Metrics

• ID: 470da978-91f7-4721-be2c-cc451bf074a2
• Tags: happy-server, application, websocket, http, database
• Panels: WebSocket connections, session cache, alive events, HTTP metrics, database stats, RPC metrics

Adding a panel

When adding panels to a dashboard JSON, follow this pattern:

1. Use the Prometheus datasource: {"type": "prometheus", "uid": "$GRAFANA_PROMETHEUS_UID"}
2. Pick the next available id (check existing panels for max id)
3. Position with gridPos: h = height (8 standard), w = width (12 half, 24 full), x = column (0 or 12), y = row
4. Common panel types: stat, timeseries, piechart, bargauge, table
5. Set appropriate unit: percentunit, ops, s, short, reqps

Tips

• Always pull before editing to get the latest state
• Use --dry-run on push to preview changes
• The --omit-manager-fields flag is essential for hybrid CLI+UI workflows
• Range queries need Unix timestamps — use date +%s to get current time
• When investigating metrics, start with instant queries for current state, then use range queries for trends