OpenTelemetry SDK for Dart

Dartastic is an OpenTelemetry SDK to add standard observability to Dart applications. Dartastic can be used with any OTel backend since it's standards-compliant.

Flutter developers should use the Flutterific OpenTelemetry SDK which builds on top of Dartastic OTel.

The Dartastic OTel SDK is in the process of being Donation to the CNCF to become the offical standard for Dart and Flutter OpenTelemetry.

Dartastic.io provides an OpenTelemetry support, training, consulting and an Observability backend customized for Flutter apps, Dart backends, and any other service or process that produces OpenTelemetry data.

Features

• 🚀 Friendly API: An easy to use, discoverable, immutable, typesafe API that feels familiar to Dart developers.
• 📐 Standards Compliant: Complies with the OpenTelemetry specification so it's portable and future-proof.
• 🌎 Ecosystem:
  • Dartastic.io is an OTel backend for Dart with a generous free tier, professional support and enterprise features.
  • Flutterrific OTel adds Dartastic OTel to Flutter apps with ease. Observe app routes, errors, web vitals and more with as few as two lines of code.
• 💪🏻 Powerful:
  • Propagate OpenTelemetry Context across async gaps and Isolates.
  • Pick from a rich set of Samplers including On/Off, probability and rate-limiting.
  • Automatically capture platform resources on initialization.
  • No skimping - If it's optional in the spec, it's included in Dartastic.
  • A pluggable and extensible API and SDK enables implementation freedom.
• 🧷 Typesafe Semantics: Ensure you're speaking the right language with a massive set of enums matching the OpenTelemetry Semantics Conventions.
• 📊 Excellent Performance:
  • Low overhead
  • Batch processing
  • Performance test suite for proven benchmarks
• 🐞 Well Tested: Very good test coverage (>90%).
• 📃 Quality Documentation: If it's not clearly documented, it's a bug. Extensive examples and best practices are provided. See the examples directory.
• 🎬 Demo The Wonderous OpenTelemetry Demo demonstrates
  gskinner's Wonderous App with instrumentation for OpenTelemetry.
• ✅ Supported Telemetry Signals and Features:
  • Tracing with span processors and samplers
  • Metrics collection and aggregation
  • Logs with log record processors and exporters
  • Context propagation
  • Baggage management and optional BaggageSpanProcessor to automatically copy baggage entries as span attributes
  • Logging is not available yet

Dartastic OTel is suitable for Dart backends, CLIs or any Dart application.

Dartastic OTel API is the API for the Dartastic OTel SDK. The dartastic_opentelemetry_api exists as a standalone library to strictly adhere to the OpenTelemetry specification which separates API and the SDK. All OpenTelemetry API classes on in dartastic_opentelemetry_api.

Flutterrific OTel adds Dartastic OTel to Flutter apps with ease.

Dartastic.io is an OpenTelemetry backend based on Elastic with a generous free tier.

Dartastic and Flutterrific OTel are made with 💙 by Michael Bushe at Mindful Software with support from:

• SEMPlicity, Inc., the Elastic experts, who provided the initial funding.
• The Anspar Foundation and CureHHT for support of Michael Bushe's OTel work and early adopter status in software used in FDA clinical trials.

Michael is eternally grateful for the individual developers and small companies for their contributions.

Michael explicitly expresses his disthanks for the massive commercial companies in telcom, healthcare, point of sale, and more who took time and provided nothing but requests for free software to support their billions of customers. Don't forget:

Mindful Software offers paid support, consulting and developing on Flutter, OpenTelemetry and AI-driven Product Development.

Getting started

Include this in your pubspec.yaml:

dependencies:
  dartastic_opentelemetry: ^1.0.0-alpha

The entrypoint to the SDK is the OTel class. OTel has static "factory" methods for all OTel API and SDK objects. OTel needs to be initialized first to point to an OpenTelemetry backend. Initialization does a lot of work under the hood including gathering a rich set of standard resources for any OS that Dart runs in. It prepares for the creation of the global default TracerProvider with the serviceName and a default Tracer, both created on first use.

All configuration, include Trace and Metric exporters, can be made in code via OTel.initialize().
Codeless configuration can be done with standard OpenTelemetry environmental variables either through POSIX variable or -D or --define for Dart or with --dart-define for Flutter apps.

Environment Variables

Dartastic OpenTelemetry supports for all standard OpenTelemetry environment variables as defined in the OpenTelemetry Specification.

Environment variables provide a convenient way to configure OpenTelemetry without hardcoding values. All environment variable names are available as strongly-typed constants in the SDK for compile-time safety and IDE autocomplete. See lib/src/environment/env_constants.dart for a complete list.

How It Works

Dart environment variables can be set in two ways:

1. System Environment Variables (Non-web only): Traditional POSIX environment variables

   export OTEL_SERVICE_NAME=my-service
   dart run
   

2. Compile-time Constants (All platforms including Flutter web): Passed during compilation/execution

   For Dart commands (dart run, dart compile, dart test):

   # Using --define (or -D shorthand)
   dart run --define=OTEL_SERVICE_NAME=my-service
   dart compile exe -D=OTEL_SERVICE_NAME=my-service -o myapp
   dart test -DOTEL_SERVICE_NAME=my-service
   

   For Flutter commands:

   # Flutter uses --dart-define (note the different flag name)
   flutter run --dart-define=OTEL_SERVICE_NAME=my-service
   flutter build apk --dart-define=OTEL_SERVICE_NAME=my-service
   

Priority: Compile-time constants (--define or --dart-define) take precedence over system environment variables. Explicit parameters to OTel.initialize() override both. Thus, POSIX env vars cannot override --dart-defines and neither POSIX env vars nor --dart-defines can override code. This is sensible and reduces security vectors.

Web Support: Flutter web and Dart web only support compile-time constants (--define or --dart-define), as browser environments don't have access to system environment variables.

Using Environment Variable Constants

All OpenTelemetry environment variable names are available as typed constants:

import 'package:dartastic_opentelemetry/dartastic_opentelemetry.dart';

void main() {
  // Reference constants instead of strings
  final serviceName = EnvironmentService.instance.getValue(otelServiceName);
  final endpoint = EnvironmentService.instance.getValue(otelExporterOtlpEndpoint);
  
  print('Service: $serviceName');
  print('Endpoint: $endpoint');
}

Constants are defined for all 74 OpenTelemetry environment variables. See lib/src/environment/env_constants.dart for the complete list.

Supported Environmental Variables

Service Configuration

Constant	Environment Variable	Description	Example
otelServiceName	OTEL_SERVICE_NAME	Sets the service name	my-dart-app
otelResourceAttributes	OTEL_RESOURCE_ATTRIBUTES	Additional resource attributes	environment=prod,region=us-west
otelLogLevel	OTEL_LOG_LEVEL	SDK internal log level	INFO, DEBUG, WARN, ERROR

OTLP Exporter Configuration

Constant	Environment Variable	Description	Default	Example
otelExporterOtlpEndpoint	OTEL_EXPORTER_OTLP_ENDPOINT	OTLP endpoint URL	http://localhost:4318	https://otel-collector:4317
otelExporterOtlpProtocol	OTEL_EXPORTER_OTLP_PROTOCOL	Transport protocol	http/protobuf	grpc, http/protobuf, http/json
otelExporterOtlpHeaders	OTEL_EXPORTER_OTLP_HEADERS	Headers (key=value,...)	None	api-key=secret,tenant=acme
otelExporterOtlpTimeout	OTEL_EXPORTER_OTLP_TIMEOUT	Timeout in milliseconds	10000	5000
otelExporterOtlpCompression	OTEL_EXPORTER_OTLP_COMPRESSION	Compression algorithm	None	gzip

Signal-Specific Configuration

Traces

Constant	Environment Variable	Description
otelTracesExporter	OTEL_TRACES_EXPORTER	Trace exporter type
otelExporterOtlpTracesEndpoint	OTEL_EXPORTER_OTLP_TRACES_ENDPOINT	Traces-specific endpoint
otelExporterOtlpTracesProtocol	OTEL_EXPORTER_OTLP_TRACES_PROTOCOL	Traces-specific protocol
otelExporterOtlpTracesHeaders	OTEL_EXPORTER_OTLP_TRACES_HEADERS	Traces-specific headers

Metrics

Constant	Environment Variable	Description
otelMetricsExporter	OTEL_METRICS_EXPORTER	Metrics exporter type
otelExporterOtlpMetricsEndpoint	OTEL_EXPORTER_OTLP_METRICS_ENDPOINT	Metrics-specific endpoint
otelExporterOtlpMetricsProtocol	OTEL_EXPORTER_OTLP_METRICS_PROTOCOL	Metrics-specific protocol
otelExporterOtlpMetricsHeaders	OTEL_EXPORTER_OTLP_METRICS_HEADERS	Metrics-specific headers

Logs

Constant	Environment Variable	Description
otelLogsExporter	OTEL_LOGS_EXPORTER	Logs exporter type (otlp, console, none)
otelExporterOtlpLogsEndpoint	OTEL_EXPORTER_OTLP_LOGS_ENDPOINT	Logs-specific endpoint
otelExporterOtlpLogsProtocol	OTEL_EXPORTER_OTLP_LOGS_PROTOCOL	Logs-specific protocol
otelExporterOtlpLogsHeaders	OTEL_EXPORTER_OTLP_LOGS_HEADERS	Logs-specific headers

Batch LogRecord Processor (BLRP)

Constant	Environment Variable	Default	Description
otelBlrpScheduleDelay	OTEL_BLRP_SCHEDULE_DELAY	1000	Delay between exports (milliseconds)
otelBlrpExportTimeout	OTEL_BLRP_EXPORT_TIMEOUT	30000	Export timeout (milliseconds)
otelBlrpMaxQueueSize	OTEL_BLRP_MAX_QUEUE_SIZE	2048	Maximum queue size
otelBlrpMaxExportBatchSize	OTEL_BLRP_MAX_EXPORT_BATCH_SIZE	512	Maximum batch size per export

LogRecord Limits

Constant	Environment Variable	Default	Description
otelLogrecordAttributeValueLengthLimit	OTEL_LOGRECORD_ATTRIBUTE_VALUE_LENGTH_LIMIT	No limit	Maximum length of attribute values
otelLogrecordAttributeCountLimit	OTEL_LOGRECORD_ATTRIBUTE_COUNT_LIMIT	128	Maximum number of attributes

For the complete list of all supported environment variables with full documentation, see lib/src/environment/env_constants.dart.

Usage Examples

Dart Application with Environment Variables

Note the ',' in OTEL_RESOURCE_ATTRIBUTES for POSIX env vars but a ';' for --dart-define. This is due to a Dart quirk.

# Set environment variables
export OTEL_SERVICE_NAME=my-backend-service
export OTEL_RESOURCE_ATTRIBUTES="service.version=1.2.3,deployment.environment=prod"
export OTEL_EXPORTER_OTLP_ENDPOINT=https://otel-collector:4318
export OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf
export OTEL_EXPORTER_OTLP_HEADERS=api-key=your-key
export OTEL_LOG_LEVEL=DEBUG

# Run your application
dart run bin/my_app.dart

Flutter Application with --dart-define

flutter run \
  --dart-define=OTEL_SERVICE_NAME=my-flutter-app \
  --dart-define=OTEL_RESOURCE_ATTRIBUTES="service.version=1.2.3;deployment.environment=prod"
  --dart-define=OTEL_EXPORTER_OTLP_ENDPOINT=https://otel-collector:4317 \
  --dart-define=OTEL_EXPORTER_OTLP_PROTOCOL=grpc \
  --dart-define=OTEL_EXPORTER_OTLP_HEADERS=api-key=your-key

Flutter Web (requires --dart-define)

# Web MUST use --dart-define (environment variables don't work in browsers)
flutter run -d chrome \
  --dart-define=OTEL_SERVICE_NAME=my-web-app \
  --dart-define=OTEL_EXPORTER_OTLP_ENDPOINT=https://collector:4318

Combining Both (--dart-define wins)

# Environment variable
export OTEL_SERVICE_NAME=from-environment

# --dart-define takes precedence
dart run --dart-define=OTEL_SERVICE_NAME=from-dart-define

# Result: Uses "from-dart-define"

In Code

import 'package:dartastic_opentelemetry/dartastic_opentelemetry.dart';

void main() async {
  // OTel.initialize() automatically reads environment variables
  // when parameters are not explicitly provided
  await OTel.initialize();
  
  // Environment variables are read automatically:
  // - OTEL_SERVICE_NAME
  // - OTEL_EXPORTER_OTLP_ENDPOINT
  // - OTEL_EXPORTER_OTLP_PROTOCOL
  // - And 90+ others...
  
  // Explicit parameters override environment variables
  await OTel.initialize(
    serviceName: 'explicit-service',  // Overrides OTEL_SERVICE_NAME
    endpoint: 'https://override:4318', // Overrides OTEL_EXPORTER_OTLP_ENDPOINT
  );
  
  // You can also read environment variables directly
  final endpoint = EnvironmentService.instance.getValue(otelExporterOtlpEndpoint);
  print('Using endpoint: $endpoint');
}

Testing with Environment Variables

Integration tests can use real environment variables:

# Run tests with environment variables
OTEL_SERVICE_NAME=test-service dart test

# Run tests with --dart-define
dart test --dart-define=OTEL_SERVICE_NAME=test-service

# Run the provided integration test script
./tool/test_env_vars.sh

The SDK includes an integration test suite (test/integration/environment_variables_test.dart) and a test script (tool/test_env_vars.sh) that demonstrates proper environment variable usage.

Minimal Code Example

import 'package:dartastic_opentelemetry/dartastic_opentelemetry.dart';

void main() async {
  // Initialize - automatically reads environment variables
  await OTel.initialize();

  // Get the default tracer
  final tracer = OTel.tracer();

  // Create a span
  final span = tracer.startSpan('my-operation');
  
  try {
    // Your code here
    await doWork();
  } catch (e, stackTrace) {
    span.recordException(e, stackTrace: stackTrace);
    span.setStatus(SpanStatusCode.error, 'Operation failed');
  } finally {
    span.end();
  }
}

Since dartastic_opentelemetry exports all the classes of opentelemetry_api, refer to opentelemetry_api for documentation of API classes.

See the /example folder for more examples.

OpenTelemetry Tracing API

The Tracing API is the primary signal in OpenTelemetry. A trace represents the end-to-end journey of a request through your system. Each trace is composed of spans — individual units of work with a name, timing, attributes, and parent-child relationships.

Concepts

• TracerProvider: Entry point to the tracing API, responsible for creating Tracers and configuring the tracing pipeline
• Tracer: Creates Spans for a particular instrumentation scope (library, package, or module)
• Span: Represents a single operation — tracks its name, start/end time, attributes, events, links, and status
• SpanProcessor: Handles span lifecycle events (start, end) and manages export
• SpanExporter: Sends finished spans to a backend (OTLP, console, etc.)
• Sampler: Decides which spans to record and export
• Context: Carries the active span and baggage across async boundaries and service boundaries

Basic Tracing

import 'package:dartastic_opentelemetry/dartastic_opentelemetry.dart';

Future<void> main() async {
  await OTel.initialize(serviceName: 'my-service');

  // Get the default tracer
  final tracer = OTel.tracer();

  // Create a span
  final span = tracer.startSpan(
    'main-operation',
    kind: SpanKind.server,
    attributes: OTel.attributesFromMap({
      'user.id': 'user-123',
      'request.type': 'example',
    }),
  );

  try {
    await doWork();
    span.setStatus(SpanStatusCode.Ok);
  } catch (e, stackTrace) {
    span.recordException(e, stackTrace: stackTrace);
    span.setStatus(SpanStatusCode.Error, e.toString());
  } finally {
    span.end();
  }

  await OTel.shutdown();
}

Parent-Child Spans

Spans form a tree by linking child spans to parent spans via context:

final parentSpan = tracer.startSpan('parent-operation');

// Create a child span linked to the parent
final childSpan = tracer.startSpan(
  'database.query',
  kind: SpanKind.client,
  context: OTel.context(spanContext: parentSpan.spanContext),
  attributes: OTel.attributesFromMap({
    'db.system': 'postgresql',
    'db.operation': 'SELECT',
  }),
);

try {
  await queryDatabase();
  childSpan.setStatus(SpanStatusCode.Ok);
} finally {
  childSpan.end();
}
parentSpan.end();

Automatic Span Management

The Tracer provides convenience methods that automatically end spans and capture exceptions:

// Synchronous — span is ended and exceptions recorded automatically
final result = tracer.recordSpan(
  name: 'compute-result',
  fn: () => computeExpensiveValue(),
);

// Async version
final data = await tracer.recordSpanAsync(
  name: 'fetch-data',
  kind: SpanKind.client,
  fn: () => httpClient.get('/api/data'),
);

// Active span — sets the span in Context automatically
tracer.startActiveSpan(
  name: 'process-request',
  fn: (span) {
    // span is active in Context.current
    span.setStringAttribute('request.id', 'abc-123');
    return processRequest();
  },
);

Span Attributes

Attributes are typed key-value pairs on spans. OTel restricts values to String, bool, int, double, and Lists of those types.

// Type-safe individual attributes
final span = tracer.startSpan('operation', attributes: OTel.attributes([
  OTel.attributeString('http.method', 'GET'),
  OTel.attributeInt('http.status_code', 200),
  OTel.attributeBool('http.is_error', false),
  OTel.attributeDouble('http.duration_ms', 123.45),
  OTel.attributeStringList('http.headers', ['Accept', 'Content-Type']),
]));

// Or from a map (types are inferred automatically)
final span = tracer.startSpan('operation',
  attributes: OTel.attributesFromMap({
    'http.method': 'GET',
    'http.status_code': 200,
  }),
);

// Add attributes after creation
span.setStringAttribute('http.url', 'https://api.example.com/data');
span.setIntAttribute('http.response_content_length', 1024);
span.addAttributes(OTel.attributesFromMap({'processing.stage': 'complete'}));

Span Events

Events are time-stamped annotations on a span:

span.addEvent(OTel.spanEventNow(
  'cache.hit',
  OTel.attributesFromMap({'cache.key': 'user:123'}),
));

span.addEventNow('validation.passed');

Span Links

Links connect spans across traces — useful for batch processing or fan-out patterns:

final link = OTel.spanLink(
  otherSpan.spanContext,
  attributes: OTel.attributesFromMap({'link.type': 'triggers'}),
);

final span = tracer.startSpan('batch-process', links: [link]);

SpanKind

Classifies the relationship between a span and its remote counterpart:

SpanKind	Description	Example
internal	Default; internal operation with no remote side	Business logic, local computation
server	Server handling an incoming request	HTTP server endpoint
client	Client making an outgoing request	HTTP client call, DB query
producer	Producer enqueuing a message	Kafka producer, queue publisher
consumer	Consumer processing a message	Kafka consumer, queue subscriber

Samplers

Samplers control which spans are recorded and exported. Configure via OTel.initialize() or per-Tracer.

Sampler	Description	Use Case
AlwaysOnSampler	Samples every span (default)	Development, debugging
AlwaysOffSampler	Never samples	Disable tracing without code changes
TraceIdRatioSampler	Samples by trace ID ratio (consistent per trace)	Production with consistent sampling
ProbabilitySampler	Samples by random probability	Testing, non-critical sampling
ParentBasedSampler	Respects parent span's sampling decision	Distributed tracing across services
RateLimitingSampler	Limits sampled traces per second (token bucket)	Controlling overhead
CountingSampler	Samples every Nth request	Periodic sampling
CompositeSampler	Combines samplers with AND/OR logic	Complex sampling policies

// Sample 10% of traces consistently
await OTel.initialize(
  serviceName: 'my-service',
  sampler: TraceIdRatioSampler(0.1),
);

// Respect parent decisions, sample 50% of new root traces
await OTel.initialize(
  serviceName: 'my-service',
  sampler: ParentBasedSampler(TraceIdRatioSampler(0.5)),
);

// Rate-limit to 100 traces/second
await OTel.initialize(
  serviceName: 'my-service',
  sampler: RateLimitingSampler(100),
);

Span Processors

Processors handle span lifecycle and export:

// SimpleSpanProcessor — exports each span immediately (good for debugging)
await OTel.initialize(
  spanProcessor: SimpleSpanProcessor(ConsoleExporter()),
);

// BatchSpanProcessor — batches spans for efficient production export
await OTel.initialize(
  spanProcessor: BatchSpanProcessor(
    OtlpGrpcSpanExporter(OtlpGrpcExporterConfig(endpoint: 'localhost:4317')),
    BatchSpanProcessorConfig(
      maxQueueSize: 2048,
      scheduleDelay: Duration(milliseconds: 5000),
      maxExportBatchSize: 512,
    ),
  ),
);

Span Exporters

Exporter	Protocol	Description
ConsoleExporter	stdout	Prints spans to console for debugging
OtlpGrpcSpanExporter	gRPC	Exports via OTLP/gRPC (production)
OtlpHttpSpanExporter	HTTP/protobuf	Exports via OTLP/HTTP (web-compatible)

// Console (development)
final exporter = ConsoleExporter();

// OTLP gRPC (production)
final exporter = OtlpGrpcSpanExporter(OtlpGrpcExporterConfig(
  endpoint: 'otel-collector:4317',
  headers: {'api-key': 'your-key'},
  compression: true,
));

// OTLP HTTP (web-compatible)
final exporter = OtlpHttpSpanExporter(OtlpHttpExporterConfig(
  endpoint: 'https://otel-collector:4318',
  headers: {'api-key': 'your-key'},
));

Context Propagation

Propagate trace context across service boundaries using W3C Trace Context and Baggage:

final propagator = CompositePropagator<Map<String, String>, String>([
  W3CTraceContextPropagator(),
  W3CBaggagePropagator(),
]);

// Inject into outgoing HTTP headers
final headers = <String, String>{};
propagator.inject(Context.current, headers, MapTextMapSetter(headers));
// Send headers with your HTTP request...

// Extract from incoming HTTP headers
final extractedContext = propagator.extract(
  OTel.context(),
  incomingHeaders,
  MapTextMapGetter(incomingHeaders),
);

// Create a child span in the extracted context
await extractedContext.run(() async {
  final span = tracer.startSpan('handle-request');
  // This span is part of the same distributed trace
  span.end();
});

Context also propagates across Dart async gaps and Isolates:

// Across Isolates
final result = await Context.current.runIsolate(() async {
  // Context is automatically restored in the new Isolate
  final span = tracer.startSpan('isolate-work');
  try {
    return await computeInIsolate();
  } finally {
    span.end();
  }
});

OpenTelemetry Metrics API

The Metrics API in OpenTelemetry provides a way to record measurements about your application. These measurements can be exported later as metrics, allowing you to monitor and analyze the performance and behavior of your application.

Concepts

• MeterProvider: Entry point to the metrics API, responsible for creating Meters
• Meter: Used to create instruments for recording measurements
• Instrument: Used to record measurements
  • Synchronous instruments: record measurements at the moment of calling their APIs
  • Asynchronous instruments: collect measurements on demand via callbacks

Instrument Types

• Counter: Synchronous, monotonic increasing counter (can only go up)
• UpDownCounter: Synchronous, non-monotonic counter (can go up or down)
• Histogram: Synchronous, aggregable measurements with statistical distributions
• Gauge: Synchronous, non-additive value that represents current state
• ObservableCounter: Asynchronous version of Counter
• ObservableUpDownCounter: Asynchronous version of UpDownCounter
• ObservableGauge: Asynchronous version of Gauge

Usage Pattern

Similar to the Tracing API, the metrics API follows a multi-layered factory pattern:

1. API Layer: Defines interfaces and provides no-op implementations
2. SDK Layer: Provides concrete implementations
3. Flutter Layer: Adds UI-specific functionality

The API follows the pattern of using factory methods for creation rather than constructors:

// Get a meter from the meter provider
final meter = OTel.meterProvider().getMeter('component_name');

// Create a counter instrument
final counter = meter.createCounter('my_counter');

// Record measurements
counter.add(1, {'attribute_key': 'attribute_value'});

For asynchronous instruments:

// Create an observable counter
final observableCounter = meter.createObservableCounter(
  'my_observable_counter',
  () => [Measurement(10, {'attribute_key': 'attribute_value'})],
);

Understanding Metric Types and When to Use Them

Instrument Type	Use Case	Example
Counter	Count things that only increase	Request count, completed tasks
UpDownCounter	Count things that can increase or decrease	Active requests, queue size
Histogram	Measure distributions	Request durations, payload sizes
Gauge	Record current value	CPU usage, memory usage
ObservableCounter	Count things that only increase, collected on demand	Total CPU time
ObservableUpDownCounter	Count things that can increase or decrease, collected on demand	Memory usage
ObservableGauge	Record current value, collected on demand	Current temperature

OpenTelemetry Logs API

The Logs API provides structured logging that integrates with traces and metrics. Unlike traditional logging frameworks, OpenTelemetry logs are first-class telemetry signals that carry context, severity, attributes, and can be correlated with the span that was active when the log was emitted.

Concepts

• LoggerProvider: Entry point to the logs API, responsible for creating Loggers
• Logger: Used to emit log records
• LogRecord: Represents a single log event with body, severity, attributes, timestamps, and trace context
• LogRecordProcessor: Processes log records before export
• LogRecordExporter: Exports log records to backends

Quick Start

import 'package:dartastic_opentelemetry/dartastic_opentelemetry.dart';

void main() async {
  // Initialize with logs enabled (default)
  await OTel.initialize(
    serviceName: 'my-service',
    enableLogs: true,  // Default is true
  );

  // Get a logger
  final logger = OTel.logger('my-component');

  // Emit log records
  logger.emit(
    body: 'Application started',
    severityNumber: Severity.INFO,
  );

  // Log with attributes
  logger.emit(
    body: 'User logged in',
    severityNumber: Severity.INFO,
    attributes: OTel.attributesFromMap({
      'user.id': 'user123',
      'user.role': 'admin',
    }),
  );

  // Log an error with exception
  try {
    throw Exception('Something went wrong');
  } catch (e, stackTrace) {
    logger.emit(
      body: 'Operation failed: $e',
      severityNumber: Severity.ERROR,
      attributes: OTel.attributesFromMap({
        'exception.type': e.runtimeType.toString(),
        'exception.stacktrace': stackTrace.toString(),
      }),
    );
  }
}

Intercepting print() Calls

Dartastic OpenTelemetry can automatically capture print() calls and convert them to OpenTelemetry logs:

await OTel.initialize(
  serviceName: 'my-service',
  logPrint: true,  // Enable print interception
  logPrintLoggerName: 'dart.print',  // Optional custom logger name
);

// Use runWithPrintInterception to capture prints
OTel.runWithPrintInterception(() {
  print('This will be captured as an OTel log');
  print('So will this');
});

// For async code
await OTel.runWithPrintInterceptionAsync(() async {
  print('Async print captured');
  await someAsyncOperation();
});

Log Severity Levels

Severity	Use Case
Severity.TRACE / Severity.TRACE2-4	Fine-grained debugging
Severity.DEBUG / Severity.DEBUG2-4	Debug information
Severity.INFO / Severity.INFO2-4	General information
Severity.WARN / Severity.WARN2-4	Warning conditions
Severity.ERROR / Severity.ERROR2-4	Error conditions
Severity.FATAL / Severity.FATAL2-4	Critical failures

Basic Logging

// Get a logger from the default provider
final logger = OTel.loggerProvider().getLogger('my-service');

// Emit a simple log
logger.emit(
  severityNumber: Severity.INFO,
  body: 'User successfully logged in.',
  attributes: OTel.attributesFromMap({
    'user.id': 'user-123',
    'auth.method': 'oauth',
  }),
);

// Warning log
logger.emit(
  severityNumber: Severity.WARN,
  body: 'Cache miss for requested key.',
  attributes: OTel.attributesFromMap({
    'cache.key': 'profile_42',
    'cache.region': 'us-east-1',
  }),
);

// Error log
logger.emit(
  severityNumber: Severity.ERROR,
  body: 'Failed to connect to database.',
  attributes: OTel.attributesFromMap({
    'db.system': 'postgresql',
    'error.type': 'ConnectionTimeout',
  }),
);

Log-to-Trace Correlation

Logs can be linked to the active span through Context, enabling powerful correlation in your backend:

final span = tracer.startSpan('process-order');
try {
  logger.emit(
    severityNumber: Severity.INFO,
    body: 'Processing order.',
    context: Context.current, // Links this log to the active span
    attributes: OTel.attributesFromMap({'order.id': 'order-789'}),
  );
  await processOrder();
} finally {
  span.end();
}

Custom Log Exporters

// Use a custom exporter
final customExporter = OtlpHttpLogRecordExporter(
  OtlpHttpLogRecordExporterConfig(
    endpoint: 'https://my-collector:4318',
    headers: {'Authorization': 'Bearer token'},
  ),
);

await OTel.initialize(
  serviceName: 'my-service',
  logRecordExporter: customExporter,
);

Console Logging (Development)

// Use console exporter for development
await OTel.initialize(
  serviceName: 'my-service',
  logRecordProcessor: SimpleLogRecordProcessor(ConsoleLogRecordExporter()),
);

Configuration via Environment Variables

Logs can be configured via environment variables:

# Set logs exporter (otlp, console, or none)
export OTEL_LOGS_EXPORTER=otlp

# Set logs-specific endpoint
export OTEL_EXPORTER_OTLP_LOGS_ENDPOINT=https://logs-collector:4318

# Configure batch processor
export OTEL_BLRP_SCHEDULE_DELAY=5000
export OTEL_BLRP_MAX_QUEUE_SIZE=4096

# Set log record limits
export OTEL_LOGRECORD_ATTRIBUTE_COUNT_LIMIT=128

Severity Levels

OpenTelemetry defines a fine-grained 24-level severity scale, grouped into standard levels:

Level	Severities	Use Case
TRACE	TRACE, TRACE2-4	Finest-grained debugging information
DEBUG	DEBUG, DEBUG2-4	Debugging information
INFO	INFO, INFO2-4	Normal operational messages
WARN	WARN, WARN2-4	Warning conditions
ERROR	ERROR, ERROR2-4	Error conditions
FATAL	FATAL, FATAL2-4	System is unusable

Severity levels support comparison operators for filtering:

if (severity >= Severity.WARN) {
  // Handle warning or above
}

Flexible Log Bodies

The body parameter accepts diverse types — not just strings:

// String body
logger.emit(body: 'Simple message.');

// Structured body (Map)
logger.emit(body: {'event': 'batch_complete', 'items': 42});

// List body
logger.emit(body: [
  {'job': 'resize_images', 'status': 'ok'},
  {'job': 'generate_thumbnails', 'status': 'failed'},
]);

Named Events

Use eventName to categorize logs as discrete events:

logger.emit(
  eventName: 'user_signup',
  severityNumber: Severity.INFO,
  body: 'New user registered.',
  attributes: OTel.attributesFromMap({
    'user.email_domain': 'example.com',
    'signup.source': 'organic',
  }),
);

Integration with Dartastic/Flutterrific

All three signal APIs (Traces, Metrics, Logs) follow the same multi-layered factory pattern:

1. API Layer: Defines interfaces and provides no-op implementations
2. SDK Layer: Provides concrete implementations with export and processing
3. Flutter Layer: Adds UI-specific functionality (route observation, app lifecycle, etc.)

The creation of objects is managed through factory methods on OTel, ensuring a clear separation between API and SDK. Each signal can be used in no-op mode when the SDK is not initialized.

Roadmap

• Support for Zipkin, Jaeger exporters

CNCF Contribution and Alignment

This project aims to align with Cloud Native Computing Foundation (CNCF) best practices:

• Interoperability - Works with the broader OpenTelemetry ecosystem
• Specification compliance - Strictly follows the OpenTelemetry specification
• Vendor neutrality - Provides a vendor-neutral implementation

License

Apache 2.0 - See the LICENSE file for details.

Commercial Support

Mindful Software offers paid Dartastic support, and consulting and developing on Flutter, OpenTelemetry and UI Architecture.

Dartastic.io provides an OpenTelemetry support, training, consulting, enhanced private packages and an Observability backend customized for Flutter apps, Dart backends, and any other service or process that produces OpenTelemetry data. Dartastic.io is built on open standards, specifically catering to Flutter and Dart applications with the ability to show Dart source code lines and function calls from production errors and logs.

Dartastic.io offers:

• Free, paid, and enterprise support
• Packages with advanced features not available in the open source offering
• Native code integration and Real-Time User Monitoring for Flutter apps
• Multiple backends (Elastic, Grafana) customized for Flutter apps.

AI Usage

Practically all code in Dartastic was generated via Claude. EVERY character is reviewed by a human.

Additional information

• Flutter developers should use the Flutterific OTel SDK.
• Dart backend developers should use the Dartastic OTel SDK.
• Also see:
  • Dartastic.io the Flutter OTel backend
  • The OpenTelemetry Specification