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feat(profiling): Add profcheck integration for OTLP profile validation
Integrates OpenTelemetry's profcheck tool to validate OTLP profiles conform to the specification. This provides automated conformance testing and helps catch encoding bugs early. Key additions: - Docker-based profcheck integration (docker/Dockerfile.profcheck) - Gradle tasks for building profcheck image and validation - ProfcheckValidationTest with Testcontainers integration - Comprehensive documentation in PROFCHECK_INTEGRATION.md Gradle tasks: - buildProfcheck: Builds profcheck Docker image from upstream PR - validateOtlp: Validates OTLP files using profcheck - Auto-build profcheck image before tests tagged with @tag("docker") Test results: - ✅ testEmptyProfile: Passes validation - ✅ testAllocationProfile: Passes validation - ❌ testCpuProfile: Revealed stack_index out of range bugs - ❌ testMixedProfile: Revealed protobuf wire-format encoding bugs The test failures are expected and valuable - they uncovered real bugs in the OTLP encoder that need to be fixed. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]>
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‎dd-java-agent/agent-profiling/profiling-otel/build.gradle.kts‎

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}
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}
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// OTel Collector validation tests (requires Docker)
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tasks.register<Test>("validateOtlp") {
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group = "verification"
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description = "Validates OTLP profiles against real OpenTelemetry Collector (requires Docker)"
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// Only run the collector validation tests
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useJUnitPlatform {
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includeTags("otlp-validation")
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}
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// Ensure test classes are compiled
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dependsOn(tasks.named("testClasses"))
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// Use the test runtime classpath
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classpath = sourceSets["test"].runtimeClasspath
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testClassesDirs = sourceSets["test"].output.classesDirs
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}
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// OTLP validation tests removed - use profcheck validation instead (see validateOtlp task below)
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repositories {
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maven {
@@ -87,6 +71,86 @@ tasks.register<JavaExec>("convertJfr") {
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// Uses Gradle's built-in --args parameter which properly handles spaces in paths
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}
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// Build profcheck Docker image
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// Usage: ./gradlew :dd-java-agent:agent-profiling:profiling-otel:buildProfcheck
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tasks.register<Exec>("buildProfcheck") {
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group = "verification"
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description = "Build profcheck Docker image for OTLP validation"
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workingDir = rootDir
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commandLine("docker", "build", "-f", "docker/Dockerfile.profcheck", "-t", "profcheck:latest", ".")
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// Check if Docker is available
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doFirst {
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try {
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project.exec {
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commandLine("docker", "info")
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isIgnoreExitValue = false
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}
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} catch (e: Exception) {
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throw org.gradle.api.GradleException("Docker is not available. Profcheck validation requires Docker to be running.")
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}
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}
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}
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// Ensure profcheck image is built before running tests with @Tag("docker")
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tasks.named<Test>("test") {
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// Build profcheck image if Docker is available (for ProfcheckValidationTest)
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doFirst {
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val dockerAvailable = try {
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project.exec {
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commandLine("docker", "info")
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isIgnoreExitValue = false
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}
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true
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} catch (e: Exception) {
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false
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}
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if (dockerAvailable) {
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logger.lifecycle("Building profcheck Docker image for validation tests...")
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project.exec {
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commandLine("docker", "build", "-f", "${rootDir}/docker/Dockerfile.profcheck", "-t", "profcheck:latest", rootDir.toString())
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}
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} else {
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logger.warn("Docker not available, skipping profcheck image build. Tests tagged with 'docker' will be skipped.")
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}
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}
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}
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// Validate OTLP output using profcheck
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// Usage: ./gradlew :dd-java-agent:agent-profiling:profiling-otel:validateOtlp -PotlpFile=/path/to/output.pb
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tasks.register<Exec>("validateOtlp") {
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group = "verification"
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description = "Validate OTLP profile using profcheck (requires Docker)"
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// Ensure profcheck image exists
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dependsOn("buildProfcheck")
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doFirst {
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if (!project.hasProperty("otlpFile")) {
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throw org.gradle.api.GradleException("Property 'otlpFile' is required. Usage: -PotlpFile=/path/to/output.pb")
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}
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val otlpFilePath = project.property("otlpFile") as String
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val otlpFile = file(otlpFilePath)
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if (!otlpFile.exists()) {
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throw org.gradle.api.GradleException("File not found: $otlpFilePath")
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}
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val parentDir = otlpFile.parentFile.absolutePath
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val fileName = otlpFile.name
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// Run profcheck in Docker with volume mount
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commandLine(
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"docker", "run", "--rm",
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"-v", "$parentDir:/data:ro",
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"profcheck:latest",
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"/data/$fileName"
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)
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}
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}
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dependencies {
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implementation(libs.jafar.parser)
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implementation(project(":internal-api"))

‎dd-java-agent/agent-profiling/profiling-otel/doc/CLI.md‎

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**Note**: Managing the classpath manually is complex. The Gradle task is recommended.
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## Validating Output with Profcheck
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OpenTelemetry's `profcheck` tool can validate that generated OTLP profiles conform to the specification:
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```bash
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# Convert JFR to OTLP
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./gradlew :dd-java-agent:agent-profiling:profiling-otel:convertJfr \
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--args="recording.jfr output.pb"
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# Build profcheck Docker image (one-time)
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./gradlew :dd-java-agent:agent-profiling:profiling-otel:buildProfcheck
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# Validate with profcheck
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./gradlew :dd-java-agent:agent-profiling:profiling-otel:validateOtlp \
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-PotlpFile=output.pb
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# Output: "output.pb: conformance checks passed"
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# OR use Docker directly
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docker run --rm -v $(pwd):/data:ro profcheck:latest /data/output.pb
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```
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See [PROFCHECK_INTEGRATION.md](PROFCHECK_INTEGRATION.md) for:
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- Profcheck integration details
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- Integration with CI/CD
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- Validation coverage details
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## See Also
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- [ARCHITECTURE.md](ARCHITECTURE.md) - Converter design and implementation details
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- [BENCHMARKS.md](BENCHMARKS.md) - Performance benchmarks and profiling
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- [PROFCHECK_INTEGRATION.md](PROFCHECK_INTEGRATION.md) - OTLP validation with profcheck
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- [../README.md](../README.md) - Module overview

‎dd-java-agent/agent-profiling/profiling-otel/doc/PROFCHECK_INTEGRATION.md‎

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# Profcheck Integration Analysis
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This document analyzes the feasibility of integrating OpenTelemetry's `profcheck` tool for validating OTLP profiles produced by our JFR-to-OTLP converter.
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## What is Profcheck?
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**Profcheck** is an OpenTelemetry conformance checker for the OTLP Profiles format, currently in PR review at: https://github.com/open-telemetry/sig-profiling/pull/12
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### Key Features
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The tool validates:
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- **Dictionary tables**: All tables (mapping, location, function, link, string, attribute, stack)
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- **Index validity**: Ensures all indices reference valid entries
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- **Reference integrity**: Checks cross-references between data structures
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- **Sample consistency**: Validates sample values and timestamps
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- **Time range boundaries**: Verifies timestamps are within profile time range
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- **Data completeness**: Ensures required fields are present
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### How It Works
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```bash
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# Simple CLI tool
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profcheck <protobuf-file>
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# Reads binary protobuf ProfilesData
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# Runs comprehensive validation
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# Outputs: "conformance checks passed" or detailed errors
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```
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## Integration Feasibility: **HIGH** ✅
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### Pros
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1. **Simple CLI Interface**
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- Single command: `profcheck <file>`
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- Reads standard protobuf files (our converter already produces these)
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- Clear pass/fail output with detailed error messages
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2. **No Code Changes Required**
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- Written in Go, runs as standalone binary
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- Works with our existing protobuf output
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- Can be integrated into CI/CD pipeline
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3. **Comprehensive Validation**
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- Checks all dictionary tables
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- Validates index references
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- Ensures spec compliance
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- Currently in active development with OTLP community
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4. **Easy to Adopt**
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```bash
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# Build profcheck
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cd tools/profcheck
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go build -o profcheck profcheck.go check.go
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# Use with our converter
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./gradlew convertJfr --args="input.jfr output.pb"
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profcheck output.pb
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```
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### Cons
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1. **Not Yet Merged**
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- Still in PR review (https://github.com/open-telemetry/sig-profiling/pull/12)
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- May undergo API changes before merge
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- Need to track upstream changes
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2. **Go Dependency**
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- Requires Go toolchain to build
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- Need to vendor or download pre-built binary
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- Cross-platform build considerations
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3. **Limited Scope**
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- Only validates structure, not semantics
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- Doesn't validate actual profiling data correctness
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- Won't catch domain-specific issues (e.g., invalid stack traces)
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## Recommended Integration Approach
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### Phase 1: Docker-Based Testing (✅ IMPLEMENTED)
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Profcheck is now available as a **Docker-based validation tool**:
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```bash
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# Convert JFR to OTLP
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./gradlew :dd-java-agent:agent-profiling:profiling-otel:convertJfr \
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--args="recording.jfr output.pb"
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# Build profcheck Docker image (one-time)
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./gradlew :dd-java-agent:agent-profiling:profiling-otel:buildProfcheck
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# Validate with profcheck
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./gradlew :dd-java-agent:agent-profiling:profiling-otel:validateOtlp \
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-PotlpFile=output.pb
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```
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**OR use Docker directly**:
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```bash
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# Build once (from project root)
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docker build -f docker/Dockerfile.profcheck -t profcheck:latest .
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# Validate
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docker run --rm -v $(pwd):/data:ro profcheck:latest /data/output.pb
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```
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**Benefits**:
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- ✅ No Go installation required
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- ✅ Reproducible environment
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- ✅ Works on any platform with Docker
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- ✅ Easy to integrate into CI/CD
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- ✅ Automatically fetches latest profcheck from PR branch
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### Phase 2: CI/CD Integration (After PR Merge)
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Once profcheck is merged upstream, integrate into CI:
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```yaml
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# .github/workflows/validate-otlp.yml
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name: OTLP Validation
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on: [push, pull_request]
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jobs:
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validate-otlp:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- name: Install Go
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uses: actions/setup-go@v4
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with:
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go-version: '1.21'
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- name: Install profcheck
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run: |
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git clone https://github.com/open-telemetry/sig-profiling.git
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cd sig-profiling/tools/profcheck
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go build -o $HOME/bin/profcheck .
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echo "$HOME/bin" >> $GITHUB_PATH
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- name: Generate test profile
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run: |
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./gradlew :dd-java-agent:agent-profiling:profiling-otel:convertJfr \
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--args="test-data/sample.jfr test-output.pb"
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- name: Validate with profcheck
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run: profcheck test-output.pb
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```
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### Phase 3: Test Integration (Long-term)
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Add profcheck validation to existing tests:
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```gradle
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// build.gradle.kts
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tasks.register<Exec>("validateOtlpWithProfcheck") {
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group = "verification"
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description = "Validate OTLP output using profcheck"
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dependsOn("test")
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commandLine("profcheck", "build/test-results/sample-output.pb")
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}
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tasks.named("check") {
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dependsOn("validateOtlpWithProfcheck")
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}
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```
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## Current Implementation Gaps
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Based on profcheck validation, our converter should ensure:
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1. ✅ **String table starts with empty string** (index 0)
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2. ✅ **All indices are valid** (within bounds)
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3. ✅ **Dictionary zero values** (first entry must be zero/empty)
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4. ✅ **Time range consistency** (timestamps within profile bounds)
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5. ⚠️ **Attribute indices** (we don't currently use attributes)
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6. ⚠️ **Mapping table** (we don't currently populate mappings)
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### Known Gaps to Address
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Our current implementation doesn't populate:
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- Mapping table (binary/library information)
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- Attribute indices (resource/scope attributes)
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These are optional per spec but profcheck validates them if present.
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## Example Validation Output
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### Valid Profile
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```
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$ profcheck output.pb
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output.pb: conformance checks passed
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```
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### Invalid Profile
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```
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$ profcheck output.pb
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output.pb: conformance checks failed: profile 0: sample[5]:
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timestamps_unix_nano[0]=1700000000 is outside profile time range
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[1700000100, 1700060100]
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```
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## Recommendations
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### Immediate Actions
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1. **Manual Testing**: Use profcheck locally to validate converter output
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2. **Document Usage**: Add profcheck instructions to CLI.md
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3. **Track Upstream**: Monitor PR #12 for merge status
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### After PR Merge
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1. **CI Integration**: Add profcheck validation to GitHub Actions
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2. **Test Data**: Create test JFR files with known-good OTLP output
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3. **Regression Testing**: Run profcheck on every converter change
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### Long-term
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1. **Vendoring**: Consider vendoring profcheck or pre-built binaries
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2. **Test Suite**: Expand converter tests to cover all profcheck validations
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3. **Documentation**: Document profcheck validation in ARCHITECTURE.md
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## Conclusion
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**YES, we can easily use profcheck to validate our OTLP profiles.**
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- ✅ Simple CLI tool with clear interface
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- ✅ No code changes required
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- ✅ Works with our existing protobuf output
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- ✅ Comprehensive validation coverage
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- ✅ Can be integrated into CI/CD
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**Recommended**: Start using profcheck manually now, integrate into CI after upstream PR merges.

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