OpenTelemetry Transformation Language (OTTL) expert. Use when writing or debugging OTTL expressions for any OpenTelemetry Collector component that supports OTTL (processors, connectors, receivers, exporters). Triggers on tasks involving telemetry transformation, filtering, attribute manipulation, data redaction, sampling policies, routing, or Collector configuration. Covers syntax, contexts, functions, error handling, and performance.
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OTTL is not limited to the transform and filter processors. Processors (transform, filter, tailsampling, logdedup) and connectors (routing, count, sum, signaltometrics) accept OTTL expressions. See components for the full list with use cases.
Navigate telemetry data using dot notation:
span.name
span.attributes["http.method"]
resource.attributes["service.name"]Contexts (first path segment): resource, scope, span, spanevent, metric, datapoint, log.
Use int64 constants for enumeration fields:
span.status.code == STATUS_CODE_ERROR
span.kind == SPAN_KIND_SERVERAssignment: = — Comparison: ==, !=, >, <, >=, <= — Logical: and, or, not
Converters (uppercase, return values):
ToUpperCase(span.attributes["http.request.method"])
Substring(log.body.string, 0, 1024)
Concat(["prefix", span.attributes["request.id"]], "-")
IsMatch(metric.name, "^k8s\\..*$")Editors (lowercase, modify data in-place):
set(span.attributes["region"], "us-east-1")
delete_key(resource.attributes, "internal.key")
limit(log.attributes, 10, [])See function-reference for the full list of editors and converters.
Use where to apply transformations conditionally:
span.attributes["db.statement"] = "REDACTED" where resource.attributes["service.name"] == "accounting"Use nil for absence checking (not null):
resource.attributes["service.name"] != nilotelcol validate --config=config.yaml to catch compilation errors before starting the Collector.debug exporter and inspect the output:exporters:
debug:
verbosity: detailed
service:
pipelines:
traces:
receivers: [otlp]
processors: [transform]
exporters: [debug] # swap in production exporter once validatederror_mode: ignore in production — see Error handling.debug with the production exporter.Occur during processor initialization and prevent Collector startup:
Occur during telemetry processing:
Always set error_mode explicitly; the default differs by component.
The transform and filter processors default to ignore since Collector Contrib v0.153.0 and to propagate before it.
The routing and signaltometrics connectors default to propagate.
The count and sum connectors have no error_mode key and always propagate errors.
| Mode | Behavior | When to use |
|---|---|---|
ignore | Logs the error and continues to the next statement | Production and general use — the default for the transform and filter processors |
propagate | Returns the error up the pipeline, dropping the payload from the Collector | Development and strict environments where you want to catch every error |
silent | Ignores errors without logging | High-volume pipelines with known-safe transforms where error logs are noise |
processors:
transform:
error_mode: ignore
trace_statements:
- set(span.attributes["parsed"], ParseJSON(span.attributes["json_body"]))Statements are a flat list; the Collector infers the context (span, metric, datapoint, log, and so on) from the path prefixes.
Use the object form with an explicit context: only when a statement group mixes paths that cannot be inferred to a single context, or when you need a group-level condition or error_mode.
Use where clauses to skip items early.
# BAD — runs replace_pattern on every span
replace_pattern(span.attributes["url.path"], "/\\d+", "/{id}")
# GOOD — skips spans that lack the attribute
replace_pattern(span.attributes["url.path"], "/\\d+", "/{id}") where span.attributes["url.path"] != nildash0hq/agent-skills
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last in sync Aug 6, 2026
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