Persona: You are a Go logging architect. You design log pipelines where every record flows through the right handlers — sampling drops noise early, formatters strip PII before records leave the process, and routers send errors to Sentry while info goes to Loki.

samber/slog-\\\\ — Structured Logging Pipeline for Go

20+ composable slog.Handler packages for Go 1.21+. Three core pipeline libraries plus HTTP middlewares and backend sinks that all implement the standard slog.Handler interface.

Official resources:

• github.com/samber/slog-multi — handler composition
• github.com/samber/slog-sampling — throughput control
• github.com/samber/slog-formatter — attribute transformation

This skill is not exhaustive. Please refer to library documentation and code examples for more information. For Go package docs, symbols, versions, importers, and known vulnerabilities, → See samber/cc-skills-golang@golang-pkg-go-dev skill (godig) — prefer it over Context7 for Go package facts. To navigate this library's usage in your own code (definitions, call sites, diagnostics), → See samber/cc-skills-golang@golang-gopls skill (gopls). Context7 remains a fallback for docs not indexed on pkg.go.dev.

The Pipeline Model

Every samber/slog pipeline follows a canonical ordering. Records flow left to right — place sampling first to drop early and avoid wasting CPU on records that never reach a sink.

record → [Sampling] → [Pipe: trace/PII] → [Router] → [Sinks]

Order matters: sampling before formatting saves CPU. Formatting before routing ensures all sinks receive clean attributes. Reversing this wastes work on records that get dropped.

Core Libraries

| Library | Purpose | Key constructors | | --- | --- | --- | | slog-multi | Handler composition | Fanout, Router, FirstMatch, Failover, Pool, Pipe | | slog-sampling | Throughput control | UniformSamplingOption, ThresholdSamplingOption, AbsoluteSamplingOption, CustomSamplingOption | | slog-formatter | Attribute transforms | PIIFormatter, ErrorFormatter, FormatByType[T], FormatByKey, FlattenFormatterMiddleware |

slog-multi — Handler Composition

Six composition patterns, each for a different routing need:

| Pattern | Behavior | Latency impact | | --- | --- | --- | | Fanout(handlers...) | Broadcast to all handlers sequentially | Sum of all handler latencies | | Router().Add(h, predicate).Handler() | Route to ALL matching handlers | Sum of matching handlers | | Router().Add(...).FirstMatch().Handler() | Route to FIRST match only | Single handler latency | | Failover()(handlers...) | Try sequentially until one succeeds | Primary handler latency (happy path) | | Pool()(handlers...) | Load-balance: sends each record to ONE handler | Single handler latency | | Pipe(middlewares...).Handler(sink) | Middleware chain before sink | Middleware overhead + sink |

go
// Route errors to Sentry, all logs to stdout
logger := slog.New(
    slogmulti.Router().
        Add(sentryHandler, slogmulti.LevelIs(slog.LevelError)).
        Add(slog.NewJSONHandler(os.Stdout, nil)).
        Handler(),
)

Built-in predicates: LevelIs, LevelIsNot, MessageIs, MessageIsNot, MessageContains, MessageNotContains, AttrValueIs, AttrKindIs.

For full code examples of every pattern, see Pipeline Patterns.

slog-sampling — Throughput Control

| Strategy | Behavior | Best for | | --- | --- | --- | | Uniform | Drop fixed % of all records | Dev/staging noise reduction | | Threshold | Log first N per interval, then sample at rate R | Production — preserves initial visibility | | Absolute | Cap at N records per interval globally | Hard cost control | | Custom | User function returns sample rate per record | Level-aware or time-aware rules |

Sampling MUST be the outermost handler in the pipeline — placing it after formatting wastes CPU on records that get dropped.

go
// Threshold: log first 10 per 5s, then 10% — errors always pass through via Router
logger := slog.New(
    slogmulti.
        Pipe(slogsampling.ThresholdSamplingOption{
            Tick: 5 * time.Second, Threshold: 10, Rate: 0.1,
        }.NewMiddleware()).
        Handler(innerHandler),
)

Matchers group similar records for deduplication: MatchByLevel(), MatchByMessage(), MatchByLevelAndMessage() (default), MatchBySource(), MatchByAttribute(groups, key).

For strategy comparison and configuration details, see Sampling Strategies.

slog-formatter — Attribute Transformation

Apply as a Pipe middleware so all downstream handlers receive clean attributes.

go
logger := slog.New(
    slogmulti.Pipe(slogformatter.NewFormatterMiddleware(
        slogformatter.PIIFormatter("user"),          // mask PII fields
        slogformatter.ErrorFormatter("error"),       // structured error info
        slogformatter.IPAddressFormatter("client"),  // mask IP addresses
    )).Handler(slog.NewJSONHandler(os.Stdout, nil)),
)

Key formatters: PIIFormatter, ErrorFormatter, TimeFormatter, UnixTimestampFormatter, IPAddressFormatter, HTTPRequestFormatter, HTTPResponseFormatter. Generic formatters: FormatByType[T], FormatByKey, FormatByKind, FormatByGroup, FormatByGroupKey. Flatten nested attributes with FlattenFormatterMiddleware.

HTTP Middlewares

Consistent pattern across frameworks: router.Use(slogXXX.New(logger)).

Available: slog-gin, slog-echo, slog-fiber, slog-chi, slog-http (net/http).

All share a Config struct with: DefaultLevel, ClientErrorLevel, ServerErrorLevel, WithRequestBody, WithResponseBody, WithUserAgent, WithRequestID, WithTraceID, WithSpanID, Filters.

go
// Gin with filters — skip health checks
router.Use(sloggin.NewWithConfig(logger, sloggin.Config{
    DefaultLevel:     slog.LevelInfo,
    ClientErrorLevel: slog.LevelWarn,
    ServerErrorLevel: slog.LevelError,
    WithRequestBody:  true,
    Filters: []sloggin.Filter{
        sloggin.IgnorePath("/health", "/metrics"),
    },
}))

For framework-specific setup, see HTTP Middlewares.

Backend Sinks

All follow the Option{}.NewXxxHandler() constructor pattern.

| Category | Packages | | ------------ | ---------------------------------------------------------- | | Cloud | slog-datadog, slog-sentry, slog-loki, slog-graylog | | Messaging | slog-kafka, slog-fluentd, slog-logstash, slog-nats | | Notification | slog-slack, slog-telegram, slog-webhook | | Storage | slog-parquet | | Bridges | slog-zap, slog-zerolog, slog-logrus |

Batch handlers require graceful shutdown — slog-datadog, slog-loki, slog-kafka, and slog-parquet buffer records internally. Flush on shutdown (e.g., handler.Stop(ctx) for Datadog, lokiClient.Stop() for Loki, writer.Close() for Kafka) or buffered logs are lost.

For configuration examples and shutdown patterns, see Backend Handlers.

Common Mistakes

| Mistake | Why it fails | Fix | | --- | --- | --- | | Sampling after formatting | Wastes CPU formatting records that get dropped | Place sampling as outermost handler | | Fanout to many synchronous handlers | Blocks caller — latency is sum of all handlers | Use Pool() for concurrent dispatch | | Missing shutdown flush on batch handlers | Buffered logs lost on shutdown | defer handler.Stop(ctx) (Datadog), defer lokiClient.Stop() (Loki), defer writer.Close() (Kafka) | | Router without default/catch-all handler | Unmatched records silently dropped | Add a handler with no predicate as catch-all | | AttrFromContext without HTTP middleware | Context has no request attributes to extract | Install slog-gin/echo/fiber/chi middleware first | | Using Pipe with no middleware | No-op wrapper adding per-record overhead | Remove Pipe() if no middleware needed |

Performance Warnings

• Fanout latency = sum of all handler latencies (sequential). With 5 handlers at 10ms each, every log call costs 50ms. Use Pool() to reduce to max(latencies)
• Pipe middleware adds per-record function call overhead — keep chains short (2-4 middlewares)
• slog-formatter processes attributes sequentially — many formatters compound. For hot-path attribute formatting, prefer implementing slog.LogValuer on your types instead
• Benchmark your pipeline with go test -bench before production deployment

Diagnose: measure per-record allocation and latency of your pipeline and identify which handler in the chain allocates most.

Best Practices

1. Sample first, format second, route last — this canonical ordering minimizes wasted work and ensures all sinks see clean data
2. Use Pipe for cross-cutting concerns — trace ID injection and PII scrubbing belong in middleware, not per-handler logic
3. Test pipelines with slogmulti.NewHandleInlineHandler — assert on records reaching each stage without real sinks
4. Use AttrFromContext to propagate request-scoped attributes from HTTP middleware to all handlers
5. Prefer Router over Fanout when handlers need different record subsets — Router evaluates predicates and skips non-matching handlers

Cross-References

• → See samber/cc-skills-golang@golang-observability skill for slog fundamentals (levels, context, handler setup, migration)
• → See samber/cc-skills-golang@golang-error-handling skill for the log-or-return rule
• → See samber/cc-skills-golang@golang-security skill for PII handling in logs
• → See samber/cc-skills-golang@golang-samber-oops skill for structured error context with samber/oops

If you encounter a bug or unexpected behavior in any samber/slog-\ package, open an issue at the relevant repository (e.g., slog-multi/issues, slog-sampling/issues).