Send Swift logs and traces to Bronto via OpenTelemetry

This page covers instrumenting a Swift application with the OpenTelemetry SDK to send logs and traces to Bronto over OTLP/HTTP via a local OTel Collector.

If you don’t have a Collector and want to export directly from your application to Bronto, see Direct export to Bronto at the bottom of this page.

Prerequisites

Swift 5.7 or later
Xcode 14 or later, or Swift Package Manager on Linux
A running OTel Collector configured to forward logs and traces to Bronto — see Connect Open Telemetry to Bronto
OpenTelemetry Swift SDK repository

Install dependencies

Add the opentelemetry-swift package to your Package.swift:

Package.swift

// swift-tools-version: 5.7
import PackageDescription

let package = Package(
    name: "MyApp",
    dependencies: [
        .package(
            url: "https://github.com/open-telemetry/opentelemetry-swift",
            from: "1.10.0"
        ),
    ],
    targets: [
        .executableTarget(
            name: "MyApp",
            dependencies: [
                .product(name: "OpenTelemetryApi",  package: "opentelemetry-swift"),
                .product(name: "OpenTelemetrySdk",  package: "opentelemetry-swift"),
                .product(name: "OtlpHttpExporter",  package: "opentelemetry-swift"),
                .product(name: "ResourceExtension", package: "opentelemetry-swift"),
            ]
        ),
    ]
)

Product	Purpose
`OpenTelemetryApi`	Core OTel API
`OpenTelemetrySdk`	SDK — `LoggerProvider`, processors
`OtlpHttpExporter`	OTLP/HTTP exporter
`ResourceExtension`	Helpers for building `Resource`

Configure the log bridge

Set up a LoggerProvider with an OTLP exporter and register it as the global OTel logs provider.

OtelLogging.swift

import Foundation
import OpenTelemetryApi
import OpenTelemetrySdk
import OtlpHttpExporter
import ResourceExtension

func configureOtelLogging() {
    let resource = DefaultResources().get()
        .merging(other: Resource(attributes: [
            ResourceAttributes.serviceName.rawValue:
                AttributeValue.string("my-service"),
            ResourceAttributes.serviceNamespace.rawValue:
                AttributeValue.string("my-team"),
            "deployment.environment":
                AttributeValue.string("production"),
        ]))

    let exporterEndpoint = URL(string: "http://localhost:4318/v1/logs")!
    let exporter = OtlpHttpLogExporter(endpoint: exporterEndpoint)

    let processor = BatchLogRecordProcessor(
        logRecordExporter: exporter,
        scheduleDelay: 5.0
    )

    let loggerProvider = LoggerProviderBuilder()
        .with(resource: resource)
        .with(processors: [processor])
        .build()

    OpenTelemetry.registerLoggerProvider(loggerProvider: loggerProvider)
}

Call configureOtelLogging() once at application startup, before the first log emission.

Configure the OTLP exporter

The exporterEndpoint in the snippet above connects to the OTel Collector on localhost:4318. If your Collector runs on a different host or port, update the URL accordingly.

Set resource attributes

Resource attributes are attached to every log record exported from this process. Two attributes drive how Bronto organises incoming logs:

OTel attribute	Bronto concept	Description
`service.name`	Dataset	Groups logs from one service
`service.namespace`	Collection	Groups related services or a team’s services

These are set via Resource(attributes:) in the setup above.

Complete example

main.swift

import OpenTelemetryApi

configureOtelLogging()

let logger = OpenTelemetry.instance.loggerProvider
    .loggerBuilder(instrumentationScopeName: "my-service")
    .build()

var record = ReadableLogRecord()
record.body = AttributeValue.string("Application started")
record.severity = .info
logger.emit(logRecord: record)

var warnRecord = ReadableLogRecord()
warnRecord.body = AttributeValue.string("Low disk space")
warnRecord.severity = .warn
warnRecord.attributes = ["disk_free_gb": AttributeValue.double(2.1)]
logger.emit(logRecord: warnRecord)

A direct bridge to Apple’s os.Logger (Unified Logging) is not yet available in the official SDK. The example above emits log records via the OTel Logs API directly. For apps targeting Apple platforms, you can emit to both os.Logger and OTel from a thin wrapper function.

Verify delivery

After running your application, check both signals in Bronto:

Logs: open the Search page and filter by the dataset name you set in service.name — your log records should appear within a few seconds.
Traces: open the Explore Traces page and filter by the same service.name — your spans should appear within a few seconds.

If no logs appear, check:

The OTel Collector is running and reachable at the configured endpoint.
The Collector’s pipeline includes a logs pipeline with an otlp receiver and the Bronto exporter — see Connect Open Telemetry to Bronto.
configureOtelLogging() is called before the first log emission.
The BatchLogRecordProcessor exports on a background timer — ensure your process does not exit before the first flush interval.

Traces

Auto-instrumentation for Swift is currently limited. Check the OpenTelemetry Swift registry for available community instrumentation packages. For URLSession and networking, community wrappers exist that create spans automatically.

Install tracing dependencies

Add StdoutExporter or OtlpHttpTraceExporter from the same opentelemetry-swift package — no additional Swift Package Manager entries are needed. Add OpenTracingShim if you need OpenTracing compatibility:

Package.swift

.product(name: "OpenTelemetrySdk",   package: "opentelemetry-swift"),
.product(name: "OtlpHttpExporter",   package: "opentelemetry-swift"),

Configure the tracer provider

OtelTracing.swift

import OpenTelemetryApi
import OpenTelemetrySdk
import OtlpHttpExporter

func configureOtelTracing(resource: Resource) {
    let traceEndpoint = URL(string: "http://localhost:4318/v1/traces")!
    let traceExporter = OtlpHttpTraceExporter(endpoint: traceEndpoint)

    let spanProcessor = BatchSpanProcessor(spanExporter: traceExporter)

    let tracerProvider = TracerProviderBuilder()
        .with(resource: resource)
        .with(processors: [spanProcessor])
        .build()

    OpenTelemetry.registerTracerProvider(tracerProvider: tracerProvider)
}

Pass the same resource used for logging so both signals share service.name and service.namespace.

Creating spans

let tracer = OpenTelemetry.instance.tracerProvider
    .get(instrumentationName: "my-service", instrumentationVersion: nil)

let span = tracer.spanBuilder(spanName: "process-payment").startSpan()
span.setAttribute(key: "payment.amount", value: AttributeValue.double(99.99))
// your code here
span.end()

GenAI semantic conventions

If your application calls an LLM, OpenTelemetry defines GenAI semantic conventions. There is no first-party GenAI auto-instrumentation package for Swift yet — set the attributes yourself around each LLM call:

This page was verified on July 17, 2026. GenAI libraries and semantic conventions are evolving rapidly, so package configuration and emitted attributes can change between releases. Keep your instrumentation current and verify the fields emitted by the version you deploy.

let tracer = OpenTelemetry.instance.tracerProvider
    .get(instrumentationName: "my-service", instrumentationVersion: nil)

let span = tracer.spanBuilder(spanName: "chat gpt-4o-mini").startSpan()
span.setAttribute(key: "gen_ai.provider.name", value: AttributeValue.string("openai"))
span.setAttribute(key: "gen_ai.request.model", value: AttributeValue.string("gpt-4o-mini"))
span.setAttribute(key: "gen_ai.usage.input_tokens", value: AttributeValue.int(33))
span.setAttribute(key: "gen_ai.usage.output_tokens", value: AttributeValue.int(74))
span.setAttribute(key: "gen_ai.response.finish_reasons", value: AttributeValue.stringArray(["stop"]))
span.end()

Message content (gen_ai.input.messages / gen_ai.output.messages) is opt-in by convention in languages with auto-instrumentation, off by default. Since you’re setting attributes by hand here, apply the same discipline — gate prompt/response content behind your own config flag rather than always sending it.

See LLM Observability for the full recommended attribute set and how to search and aggregate GenAI fields in Bronto.

Direct export to Bronto

If you are not using an OTel Collector, export directly to Bronto by replacing the exporter configurations with the Bronto OTLP endpoints and your API key:

let config = OtlpConfiguration(
    timeout: TimeInterval(10),
    headers: [("x-bronto-api-key", "<YOUR_API_KEY>")]
)

let logExporter = OtlpHttpLogExporter(
    endpoint: URL(string: "https://ingestion.eu.bronto.io/v1/logs")!, // or ingestion.us.bronto.io
    config: config
)

let traceExporter = OtlpHttpTraceExporter(
    endpoint: URL(string: "https://ingestion.eu.bronto.io/v1/traces")!, // or ingestion.us.bronto.io
    config: config
)

Region	Logs endpoint	Traces endpoint
EU	`https://ingestion.eu.bronto.io/v1/logs`	`https://ingestion.eu.bronto.io/v1/traces`
US	`https://ingestion.us.bronto.io/v1/logs`	`https://ingestion.us.bronto.io/v1/traces`

See API Keys for how to create a key with ingestion permissions. No other changes to the rest of the setup are required.

Overview

Ingest with agents

Ingest from AWS

Ingest from Azure

Ingest from CDN and edge

Ingest from apps and platforms

Ingest from infrastructure and databases

Ingest OpenTelemetry data

Send Swift logs and traces to Bronto via OpenTelemetry

Prerequisites

Install dependencies

Configure the log bridge

Configure the OTLP exporter

Set resource attributes

Complete example

Verify delivery

Traces

Install tracing dependencies

Configure the tracer provider

Creating spans

GenAI semantic conventions

Direct export to Bronto

​Prerequisites

​Install dependencies

​Configure the log bridge

​Configure the OTLP exporter

​Set resource attributes

​Complete example

​Verify delivery

​Traces

​Install tracing dependencies

​Configure the tracer provider

​Creating spans

​GenAI semantic conventions

​Direct export to Bronto

Prerequisites

Install dependencies

Configure the log bridge

Configure the OTLP exporter

Set resource attributes

Complete example

Verify delivery

Traces

Install tracing dependencies

Configure the tracer provider

Creating spans

GenAI semantic conventions

Direct export to Bronto