Fastly Stats

Fastly stats

Prefer the fastly CLI. Drop to curl only for the seven things the CLI cannot do, listed under Raw API below.

Rules that decide whether the answer is right

1. Bytes to GB is decimal SI: bytes / 1e9. TB is / 1e12. Never 2^30. Fastly bills in decimal units, so a GiB figure is wrong by 7.4% and still reads as a plausible number.
2. For a calendar window, pass explicit UTC boundaries: --from 2026-07-01T00:00:00Z --to 2026-08-01T00:00:00Z returns every day bucket in July. A bucket is emitted only when the whole period falls inside the window, and a relative window opens and closes mid-bucket, so --from "N days ago" --by day returns N-1 buckets, never N, and "1 day ago" returns none at all. Relative strings are safe at --by hour, not at --by day.
3. On the raw API, from=yesterday means 12:00:00 UTC, not midnight, and from=today means now. N days ago / N hours ago are exact offsets. Read back meta.from / meta.to.
4. hit_ratio, edge_hit_ratio and origin_offload are gauges. Never sum or average them across buckets. Recompute from the summed counters: hits / (hits + miss).
5. ts/h on rt.fastly.com covers the last 120 seconds, not an hour, and returns only the seconds that carried traffic. Divide a rate by 120 there, or by the window you bounded when sampling with the CLI; never by the sample count or the recorded span. Print the window beside the rate.
6. fastly stats ... --json emits NDJSON, one object per line, no array. Slurp with jq -s before aggregating. The raw HTTP API returns a normal array in data.
7. Stats responses omit services with zero traffic in the window. Enumerate from fastly service list --json and default sums with add // 0.
8. Do not read the newest bucket. Historical aggregation keeps growing for a few minutes after a period closes.
9. On a Compute service the traffic lands in compute_requests and requests stays 0. Summing requests alone reports zero traffic for a service that is serving fine. Check both.
10. Status codes split the same way. Use all_status_*, never bare status_* or compute_resp_status_*: status_5xx is 0 on Compute, compute_resp_status_5xx is absent on VCL, all_status_5xx is right on both. No all_requests exists, so denominators still need requests + compute_requests.

Pick the command

historical, aggregate and usage take --by minute|hour|day and --field. The two inspectors take --downsample and --metric (repeatable) instead, plus --group-by, --datacenter, --limit, --cursor, and --domain or --host. Mixing the two vocabularies fails with a usage error. historical has no --datacenter; realtime takes no filters at all, and regions takes no flags whatsoever, not even --json. The documented --metric cap of 10 is not enforced; 20 names in one call are accepted and echoed in meta.metric. Full flag matrix: the fastly-cli skill's stats reference.

Service-scoped subcommands take -s / --service-id or --service-name, falling back to FASTLY_SERVICE_ID then fastly.toml.

Worked answers

Cache hit ratio over a whole month, recomputed from counters rather than averaged:

fastly stats historical -s "$SID" --by day \
  --from 2026-07-01T00:00:00Z --to 2026-08-01T00:00:00Z --json \
  | jq -s '(map(.hits)|add // 0) as $h | (map(.miss)|add // 0) as $m
           | {hits:$h, miss:$m, hit_ratio: (if $h+$m > 0 then $h/($h+$m) else null end)}'

5xx count and share over a month, correct on both service types:

fastly stats historical -s "$SID" --by day \
  --from 2026-07-01T00:00:00Z --to 2026-08-01T00:00:00Z --json \
  | jq -s '{requests: (map((.requests // 0) + (.compute_requests // 0))|add // 0),
            status_5xx: (map(.all_status_5xx // 0)|add // 0)}
           | . + {pct: (if .requests > 0 then .status_5xx/.requests*100 else null end)}'

Bandwidth in GB per service, ranked. Drive the loop from the service list, not from a stats response, so zero-traffic services are still counted:

fastly service list --json | jq -r '.[] | "\(.ServiceID)|\(.Name)"' | while IFS='|' read -r id name; do
  gb=$(fastly stats historical -s "$id" --by day \
        --from 2026-07-01T00:00:00Z --to 2026-08-01T00:00:00Z --json \
        | jq -s '([.[].bandwidth] | add // 0) / 1e9')
  printf '%.3f\t%s\n' "$gb" "$name"
done | sort -rn

Account totals for a month. fastly stats usage --json returns one object keyed by region, so sum the leaves. Dropping compute_requests here omits every Compute service from the total:

fastly stats usage --from 2026-07-01T00:00:00Z --to 2026-08-01T00:00:00Z --json \
  | jq '{bandwidth_gb: (([.[].bandwidth]|add)/1e9),
         requests: ([.[] | .requests + .compute_requests]|add)}'

billable_units=true on GET /stats/usage_by_month rescales, it does not switch quantity: bandwidth / 1e9, requests and compute_requests / 10,000, so a requests of 1.4452 means 14,452. For one month /stats/usage, the per-service /stats sum and /stats/usage_by_month all report the same byte total, so a mismatch is an arithmetic bug, not a billing subtlety.

Live request rate. fastly stats realtime --json streams one flat object per second, {recorded, aggregated, datacenter}, no Data wrapper and no Timestamp; those exist only on the raw rt.fastly.com payload. It prints nothing on a quiet service and never exits, so head -n deadlocks. Bound it by wall clock and divide by that bound:

SECS=20
OUT=$(mktemp)
fastly stats realtime -s "$SID" --json > "$OUT" & P=$!
sleep "$SECS"; kill "$P" 2>/dev/null; wait "$P" 2>/dev/null
jq -s --argjson w "$SECS" \
  '{samples: length, window_s: $w,
    requests: (map((.aggregated.requests // 0) + (.aggregated.compute_requests // 0))|add // 0)}
   | . + {rps: (.requests / $w)}' "$OUT"
rm -f "$OUT"

Report the window beside the rate. Do not derive it from recorded min/max: only seconds with traffic are emitted, so on bursty traffic that span is a fraction of what you watched and the rate comes out several times too high. Ratios and same-window comparisons survive a misjudged window; extrapolated rates do not.

One-shot alternative, returns immediately even with no data: GET rt.fastly.com/v1/channel/{id}/ts/h, the traffic-bearing seconds of the last 120.

Raw API

Seven things the CLI cannot do. Everything else has a CLI command above.

datacenter= is absent from the CLI's SDK input type, not just its flags, so no flag combination reaches per-POP history. The two account-wide rows need curl because stats historical always resolves a service ID and errors without one; fastly stats aggregate is not a substitute, it sums every service into one series instead of breaking them out.

Auth is the header Fastly-Key: <token>. Feed it from the CLI and keep --quiet: without it a pending upgrade notice lands inside the header value and produces curl: (43) or a spurious 401.

curl -sS -H "Fastly-Key: $(fastly auth token --quiet)" \
  "https://api.fastly.com/stats/service/$SID?from=2026-07-01T00:00:00Z&to=2026-08-01T00:00:00Z&by=day&datacenter=SJC"

Never run fastly auth show --reveal bare and never pass -v on an authenticated call; both print the token into the transcript.

Endpoint paths, parameters and response shapes: references/api.md. Field names and aggregation shape: references/fields.md. Errors, empty data and wrong-scope symptoms: references/debugging.md.

Scope traps

• region= takes stats_region values (usa, europe), not the region values from /datacenters (US-East, North-America). Get the live list from fastly stats regions.
• region= is ignored on /stats/usage and /stats/usage_by_service: meta echoes it and all eleven regions come back, byte-identical to the unfiltered response. fastly stats usage --region filters client-side, so the CLI and the raw URL disagree. Filter usage responses yourself.
• Sending region and datacenter together returns HTTP 200 with the POP filter dropped silently: meta echoes region and omits datacenter entirely, and the numbers are whole-region. Never send both, and assert meta carries the filter you sent.
• POP codes are uppercase. A lowercase or unknown code fails loudly with invalid datacenter.
• Origin and Domain Inspector are paid add-ons. When not enabled the endpoints return HTTP 200, "status":"success" and an empty data array, which reads exactly like a service with no traffic. Check fastly products -s ID before concluding there is nothing to see.
• A shield POP's datacenter entry carries edge-to-shield traffic, not client traffic. Identify shields from the SHIELD column of fastly pops and label them separately.
• When diagnosing rather than reporting, pull the per-POP breakdown. A healthy service-wide number routinely hides one POP erroring: datacenter= on classic stats, --group-by datacenter on the inspectors, the datacenter map in real-time.

Not this skill

Creating or configuring services, backends, VCL or WAF: fastly-cli and fastly. Raw request logs: stats are pre-aggregated counters, not log lines. NGWAF security events: fastly-ngwaf.