Go SDK Overview

The Shield360 Go SDK provides OpenTelemetry-native observability for Go applications using LLM APIs. It wraps your provider clients with lightweight instrumentation that automatically collects traces, metrics, and cost data without requiring any changes to your application logic.

Supported providers

OpenAI

Chat completions, streaming, embeddings, and image generation - with full token usage and cost tracking.

Anthropic

Claude messages and streaming - with cache token tracking and full OpenTelemetry semantic conventions.

vLLM

Chat completions and streaming against vLLM’s OpenAI-compatible API - with full token usage tracking.

What gets collected

Every instrumented call automatically records:

Distributed traces - spans with request/response details, model name, token counts, and cost
OTel metrics - gen_ai.client.token.usage, gen_ai.client.operation.duration, gen_ai.server.time_to_first_token, gen_ai.server.time_per_output_token, gen_ai.server.request.duration
Streaming metrics - time-to-first-chunk and per-chunk latency observations
Cost tracking - automatic cost calculation using the built-in pricing data

go get github.com/ThinkfleetAI/shield360-go

go get github.com/ThinkfleetAI/shield360-go@v1.2.3

Replace v1.2.3 with the version you want to install.

Quick start

package main

import (
    "context"
    "fmt"
    "log"

    shield360 "github.com/ThinkfleetAI/shield360-go"
    "github.com/ThinkfleetAI/shield360-go/instrumentation/openai"
)

func main() {
    // 1. Initialize Shield360 (once, at startup)
    if err := shield360.Init(shield360.Config{
        OtlpEndpoint:    "http://127.0.0.1:4318",
        ApplicationName: "my-ai-app",
        Environment:     "production",
    }); err != nil {
        log.Fatal(err)
    }
    defer shield360.Shutdown(context.Background())

    // 2. Create an instrumented client
    client := openai.NewClient("your-openai-api-key")

    // 3. Use it exactly like a normal client
    resp, err := client.CreateChatCompletion(context.Background(), openai.ChatCompletionRequest{
        Model: "gpt-4o",
        Messages: []openai.Message{
            {Role: "user", Content: "Hello, world!"},
        },
        MaxTokens: 100,
    })
    if err != nil {
        log.Fatal(err)
    }

    fmt.Println(resp.Choices[0].Message.Content)
}

Replace YOUR_OTEL_ENDPOINT with the URL of your OpenTelemetry backend, such as http://127.0.0.1:4318 for a local Shield360 deployment.

Configuration

Pass a Config struct to shield360.Init():

Field	Environment Variable	Description	Default
`OtlpEndpoint`	`OTEL_EXPORTER_OTLP_ENDPOINT`	OTLP backend URL	`http://127.0.0.1:4318`
`OtlpHeaders`	-	Additional HTTP headers for OTLP requests	`{}`
`ApplicationName`	-	Name of your application	`default`
`Environment`	-	Deployment environment label	`default`
`ServiceVersion`	-	Service version string	`""`
`DisableTracing`	-	Disable trace collection	`false`
`DisableMetrics`	-	Disable metrics collection	`false`
`DisableBatch`	-	Disable batch export (useful for testing)	`false`
`DisableCaptureMessageContent`	-	Omit prompt/completion text from spans	`false`
`DetailedTracing`	-	Enable component-level tracing detail	`false`
`DisablePricingFetch`	-	Skip fetching remote pricing data	`false`
`PricingEndpoint`	-	URL for custom pricing JSON	built-in
`PricingInfo`	-	In-process pricing overrides	`{}`
`TraceExporterTimeout`	-	Timeout for trace exports	`10s`
`MetricExporterTimeout`	-	Timeout for metric exports	`10s`
`MetricExportInterval`	-	Interval for metric exports	`30s`

Via environment variable

// If OTEL_EXPORTER_OTLP_ENDPOINT is set, no endpoint config is needed
shield360.Init(shield360.Config{
    ApplicationName: "my-ai-app",
})

export OTEL_EXPORTER_OTLP_ENDPOINT=http://127.0.0.1:4318

Getting started

OpenAI Integration

Monitor chat completions, streaming, embeddings, and image generation

Anthropic Integration

Monitor Claude messages and streaming with cache token tracking

vLLM Integration

Monitor chat completions and streaming against your vLLM server

Destinations

Send telemetry to Datadog, Grafana, New Relic, and other observability stacks

Configuration

Configure the Shield360 SDK according to your requirements