Add dashboards and alerts as code, mark Phase 6 done
Dashboards: observability/dashboards/generate.py (Grafana Foundation SDK) writes k8s/grafana/dashboards/*.json -- a RED dashboard per HTTP service and a system overview -- shipped through a file provider and configMapGenerators, so `kubectl apply -k k8s/` rebuilds them. Verified by deleting Grafana and its volume and re-applying. Adds tracesToMetrics to the Tempo datasource. Alerts: Prometheus rule files delivering to Alertmanager, under a labels/annotations contract enforced by observability/alerts/check_contract.py, with runbooks in docs/runbooks/. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
This commit is contained in:
Movses Aslanyan
co-authored by
Claude Sonnet 5.5
Claude Sonnet 5.5
parent
b50f8c3b24
commit
fef735c922
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"""Generate Grafana dashboard JSON into k8s/grafana/dashboards/.
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python -m venv .venv && .venv/bin/pip install -r requirements.txt
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.venv/bin/python generate.py
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"""
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import json
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from pathlib import Path
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from grafana_foundation_sdk.builders.dashboard import Dashboard
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from grafana_foundation_sdk.builders.prometheus import Dataquery as PromQuery
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from grafana_foundation_sdk.builders.nodegraph import Panel as NodeGraph
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from grafana_foundation_sdk.builders.tempo import TempoQuery
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from grafana_foundation_sdk.builders.timeseries import Panel as Timeseries
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from grafana_foundation_sdk.cog.encoder import JSONEncoder
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from grafana_foundation_sdk.models.dashboard import DataSourceRef
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OUT_DIR = Path(__file__).resolve().parents[2] / "k8s" / "grafana" / "dashboards"
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PROMETHEUS = DataSourceRef(type_val="prometheus", uid="prometheus")
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# Audit and Notifier are consumers and does not have HTTP, so commented them out for now
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SERVICES = [
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"gateway",
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"ledger",
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"fraud",
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"sanctions",
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"insights",
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# "audit",
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# "notifier",
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]
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def prom(expr: str, ref_id: str, legend: str) -> PromQuery:
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return (
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PromQuery()
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.expr(expr)
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.ref_id(ref_id)
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.legend_format(legend)
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.datasource(PROMETHEUS)
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)
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def red_dashboard(service: str) -> Dashboard:
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"""Rate, Errors, Duration for one service, in the order you'd ask them
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during an incident: is it serving, is it failing, is it slow."""
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# `service` and `instance` carry the same value on these series.
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sel = f'job="ledgerline",service="{service}"'
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count = f"http_server_request_duration_seconds_count{{{sel}}}"
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bucket = f"http_server_request_duration_seconds_bucket{{{sel}}}"
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def quantile(q: float) -> str:
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return f"histogram_quantile({q}, sum by (le) (rate({bucket}[5m])))"
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rate = (
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Timeseries()
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.title("Request rate")
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.datasource(PROMETHEUS)
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.unit("reqps")
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.with_target(
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prom(
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f"sum by (http_route) (rate({count}[5m]))",
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"rate",
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"{{http_route}}",
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)
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)
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)
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errors = (
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Timeseries()
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.title("Error ratio")
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.datasource(PROMETHEUS)
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.unit("percentunit")
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.min(0)
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.with_target(
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prom(
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# 5xx only: a 404 is the client's mistake, not the service failing.
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# `or vector(0)` keeps the line at 0 when no 5xx series exists yet;
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# with no traffic the denominator is 0 and the result is NaN (a gap).
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f'(sum(rate({count[:-1]},http_response_status_code=~"5.."}}[5m])) or vector(0))'
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f" / sum(rate({count}[5m]))",
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"errors",
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"5xx ratio",
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)
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)
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)
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duration = (
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Timeseries()
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.title("Request duration")
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.datasource(PROMETHEUS)
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.unit("s")
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# One query per quantile. Aggregate the histogram *buckets* first and
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# compute the quantile after; never average per-instance quantiles.
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.with_target(prom(quantile(0.50), "p50", "p50"))
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.with_target(prom(quantile(0.95), "p95", "p95"))
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.with_target(prom(quantile(0.99), "p99", "p99"))
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)
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return (
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Dashboard(f"RED: {service}")
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.uid(f"red-{service}")
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.tags(["generated", "red"])
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.time("now-1h", "now")
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.refresh("15s")
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.readonly()
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.with_panel(rate)
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.with_panel(errors)
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.with_panel(duration)
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)
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TEMPO = DataSourceRef(type_val="tempo", uid="tempo")
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def overview_dashboard() -> Dashboard:
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"""System-wide: who calls whom, is the async hop keeping up, is a pool
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under pressure. Not per service, so no `service` variable."""
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# Not a backend query: Grafana's browser builds the node graph from the
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# Prometheus span metrics that Tempo's metrics-generator writes (wired by
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# `serviceMap.datasourceUid` in datasources.yml). Calling it through
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# /api/ds/query fails with "unsupported query type", so this panel can only
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# be checked by looking at it in the browser.
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service_graph = (
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NodeGraph()
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.title("Service graph")
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.datasource(TEMPO)
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.span(24)
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.height(12)
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.with_target(
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TempoQuery()
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.datasource(TEMPO)
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.ref_id("graph")
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.query_type("serviceMap")
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)
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)
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lag = (
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Timeseries()
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.title("Stream consumer lag")
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.datasource(PROMETHEUS)
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.span(12)
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.unit("none")
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.with_target(
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prom(
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"ledgerline_stream_lag",
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"lag",
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"{{consumer_group}}",
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)
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)
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)
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pool = (
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Timeseries()
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.title("DB pool connections in use")
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.datasource(PROMETHEUS)
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.span(12)
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.unit("none")
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.with_target(
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prom(
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# "In use", not a percentage: the app exports no pool *size*.
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# What would you need to turn this into saturation, and where
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# could it come from? (Also look at the labels of
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# `db_client_connections_usage_connections{state=...}`.)
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"sum by (service, pool) (ledgerline_db_pool_in_use)",
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"pool",
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"{{service}} / {{pool}}",
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)
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)
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)
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return (
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Dashboard("System overview")
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.uid("overview")
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.tags(["generated", "overview"])
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.time("now-1h", "now")
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.refresh("15s")
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.readonly()
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.with_panel(service_graph)
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.with_panel(lag)
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.with_panel(pool)
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)
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DASHBOARDS = {
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"overview": overview_dashboard,
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**{f"red-{svc}": (lambda s=svc: red_dashboard(s)) for svc in SERVICES},
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}
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# A ConfigMap is capped at ~1 MiB, and client-side `kubectl apply` stores a
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# second copy in an annotation, so keep well under half of it.
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MAX_TOTAL_BYTES = 400_000
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def main() -> None:
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OUT_DIR.mkdir(parents=True, exist_ok=True)
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rendered = {
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name: json.dumps(fn().build(), cls=JSONEncoder, indent=2, sort_keys=True) + "\n"
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for name, fn in DASHBOARDS.items()
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}
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for name, text in rendered.items():
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assert "FIXME" not in text, f"{name}: unfilled FIXME in generated JSON"
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total = sum(len(t) for t in rendered.values())
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assert total < MAX_TOTAL_BYTES, f"{total} bytes of dashboards; ConfigMap limit"
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for name, text in rendered.items():
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(OUT_DIR / f"{name}.json").write_text(text)
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print(f"wrote {OUT_DIR / f'{name}.json'}")
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print(f"{total} bytes total")
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if __name__ == "__main__":
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main()
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