git:20260314.9629b35 to git:20260517.e6c4538

---

name: statsd

description: >-

StatsD metric instrumentation: push metrics over UDP, choose the right metric

type, name consistently. Invoke whenever task involves any interaction with

StatsD metrics — emitting counters, gauges, timers, histograms, sets, or

distributions; configuring DogStatsD tags; tuning sampling rates; or

integrating with Graphite, Prometheus, or Telegraf backends.

---

# StatsD

Choose the right metric type, name it with dot-delimited hierarchy, tag dimensions instead of encoding them in names.

## References

- **Metric types** — [`${CLAUDE_SKILL_DIR}/references/metric-types.md`]: Wire format details, type comparison, sampling

correction

- **Naming** — [`${CLAUDE_SKILL_DIR}/references/naming.md`]: Graphite namespace mapping, character rules, naming

examples

- **DogStatsD** — [`${CLAUDE_SKILL_DIR}/references/dogstatsd.md`]: Events format, service checks, protocol versions,

distributions vs histograms

- **Aggregation** — [`${CLAUDE_SKILL_DIR}/references/aggregation.md`]: Flush mechanics, Graphite downsampling, DogStatsD

aggregation, timestamps

- **Client patterns** — [`${CLAUDE_SKILL_DIR}/references/client-patterns.md`]: High-throughput tuning, error handling,

K8s deployment, UDS configuration

- **Backends** — [`${CLAUDE_SKILL_DIR}/references/backends.md`]: statsd_exporter config, Telegraf setup, migration

guides

## Metric Types

Wire format: `<metric_name>:<value>|<type>[|@<sample_rate>][|#<tags>]`

### Decision Matrix

| Question | Type |

| ------------------------------------- | ---------------------------------- |

| How many times did X happen? | Counter (`c`) |

| What is X right now? | Gauge (`g`) |

| How long did X take? | Timer (`ms`) |

| What is the distribution of X? | Histogram (`h`) |

| How many unique X occurred? | Set (`s`) |

| What is the global distribution of X? | Distribution (`d`, DogStatsD only) |

gauge produces meaningless rates.

### Counter (`|c`)

Measures rate of events over time. Server sums all values during flush interval, resets to 0 after flush, reports both

raw count and per-second rate.

- Use for: request counts, error counts, event occurrences (cache hits, logins)

- Sample rate correction: value multiplied by `1/rate`

- Supports sampling (`|@<rate>`)

### Gauge (`|g`)

Instantaneous value at a point in time. Server stores last value received, retains between flushes (sticky).

- Use for: queue depth, active connections, memory/CPU usage, thread pool size

- Signed values (`+N`, `-N`) modify current value incrementally

- Cannot set to a negative number directly — set to 0 first, then decrement

- **Do not sample gauges** — server cannot correct for sampling on point-in-time values

### Timer (`|ms`)

Duration of an operation in milliseconds. Server computes per flush interval: count, mean, upper (max), lower (min),

sum, stddev, median, configurable percentiles (p90, p95, p99).

- Use for: HTTP request latency, DB query duration, function execution time

- Supports sampling (`|@<rate>`)

### Histogram (`|h`)

Distribution of values over time. Identical to timer in most implementations. DogStatsD treats histograms as the native

distribution type.

- Use for: request payload sizes, response body sizes, batch sizes

- Conceptually: timers measure duration, histograms measure arbitrary distributions

### Set (`|s`)

Count of unique values per flush interval. Server tracks distinct values, reports cardinality at flush, resets.

- Use for: unique users, unique IPs, unique error codes per interval

- **Do not sample sets** — sampling breaks uniqueness tracking

### Distribution (`|d`) — DogStatsD Only

Global distribution across all hosts. Raw values sent to Datadog servers (not aggregated locally). Use when you need

accurate fleet-wide percentiles.

See `${CLAUDE_SKILL_DIR}/references/dogstatsd.md` for distributions vs histograms comparison and protocol version

details.

## Naming

Format: `<namespace>.<subsystem>.<target>.<metric>.<unit>`

Example: `myapp.api.request.duration.ms`, `myapp.cache.hit.count.total`

### Naming Rules

- Always namespace by service name — `myapp.api.requests` not just `requests`

- Use dot-delimited hierarchy

- Include the unit: `.ms`, `.bytes`, `.total`, `.items`

- Dimensions go in tags, not metric names (when tags are available)

- Use lowercase everywhere — some backends are case-sensitive

- Use underscores within path segments: `http_request` not `httpRequest`

- No dashes — they break Graphite navigation

See `${CLAUDE_SKILL_DIR}/references/naming.md` for Graphite namespace mapping, character rules table, and naming

anti-patterns.

## Tags (DogStatsD)

Format: `metric.name:1|c|#key1:value1,key2:value2` — comma-separated, no spaces.

### Tag Rules

- Use tags for dimensions you will filter or group by — not metric names

- Keep cardinality bounded — each unique tag combination creates a separate time series

- No spaces in tag values — use underscores: `region:us_east`

### Unified Service Tagging

Set these as global/constant tags on the client — attach to every metric automatically:

- **`env`** — Deployment environment (`env:production`)

- **`service`** — Service name (`service:payment-api`)

- **`version`** — Deployed version (`version:2.1.0`)

### Tag Cardinality

Rule of thumb: if a tag can have >1000 distinct values, do not use it. Use logs or traces for high-cardinality data.

- **`env:production`** — ~3-5 values: Yes

- **`method:GET`** — ~7 values: Yes

- **`status_code:200`** — ~20-50 values: Yes

- **`endpoint:/api/users`** — ~50-200 values: Caution

- **`user_id:12345`** — Unbounded: No

## Aggregation and Flush

The flush cycle determines metric resolution. Default: 10 seconds.

- Counters reset to 0 after flush; gauges are sticky (retain last value)

- If no counter values received during flush: behavior depends on `deleteCounters` config (default: send 0)

- Enable client-side aggregation for high-throughput applications (Go v5.0+, Java v3.0+, .NET v7.0+) — pre-aggregates

before sending to Agent

See `${CLAUDE_SKILL_DIR}/references/aggregation.md` for flush mechanics, Graphite downsampling rules, DogStatsD

aggregation details, and pre-aggregated timestamps.

## Client Patterns

### Initialization

- **One client instance per application** — do not create per-request

- **Set namespace prefix** — auto-prepends to all metric names

- **Set global/constant tags** — env, service, version set once

- **Close/flush on shutdown** — buffered metrics lost otherwise

### Buffering

Enable client-side buffering — packs multiple metrics into single UDP packets. Reduces syscall overhead in hot paths.

Most modern DogStatsD clients buffer by default. Call `flush()` before shutdown.

### Sampling

Client randomly decides whether to send each metric based on sample rate. Datagram includes `|@<rate>` so server

corrects the count.

- **< 1000 metrics/sec** — `rate=1.0` (no sampling)

- **1000-10000/sec** — `rate=0.5` to `0.1` for counters/timers

- **> 10000/sec** — `rate=0.1` or lower; enable client-side aggregation

**Never sample gauges or sets** — server cannot correct for these types.

See `${CLAUDE_SKILL_DIR}/references/client-patterns.md` for high-throughput tuning steps, error handling, and Kubernetes

deployment patterns.

## Backends

- **Simple, self-hosted graphing** — Graphite

- **Cloud monitoring + APM** — Datadog (DogStatsD)

- **Prometheus ecosystem integration** — statsd_exporter

- **Flexible multi-output pipeline** — Telegraf

- **Migrating StatsD to Prometheus** — statsd_exporter with relay

See `${CLAUDE_SKILL_DIR}/references/backends.md` for statsd_exporter configuration, Telegraf setup, and migration

guides.

## Application

When **writing** StatsD instrumentation:

- Choose the metric type based on what the value represents, not convenience.

- Apply naming conventions silently — don't narrate each rule.

- Always configure client-side buffering for production use.

When **reviewing** StatsD instrumentation:

- Check metric type correctness first — most common and most damaging mistake.

- Verify tag cardinality is bounded.

- Cite the specific issue and show the fix inline.

## Integration

The coding skill governs workflow; this skill governs StatsD instrumentation choices.