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Add Dynamic Profiling Data Models and PostgreSQL Schemas

Summary

This PR contributes the foundational data model infrastructure for the dynamic profiling feature, including PostgreSQL database schemas and Python API models.

What's Included

Database Schema (scripts/setup/postgres/)

  • ProfilingRequests: Track start/stop profiling requests
  • ProfilingCommands: Store commands to be executed by agents
  • HostHeartbeats: Monitor agent health and status
  • ProfilingExecutions: Record profiling execution history
  • Supporting tables for namespace, service, container, and process mappings

API Models (src/gprofiler/backend/models/)

  • Pydantic models for request/response validation
  • Type-safe data structures for profiling operations
  • Support for host-level and process-level profiling

Documentation (docs/)

  • Comprehensive guide for dynamic profiling architecture
  • Database schema documentation with ERD
  • Setup and testing instructions

Tests (src/tests/)

  • Unit tests for profiling host status functionality
  • Test scripts for model validation

Benefits

  • ✅ Clean separation of dynamic profiling data from existing metrics
  • ✅ Support for both host-level and process-level profiling
  • ✅ Extensible schema for future profiling capabilities
  • ✅ Well-documented for easy onboarding

ashokbytebytego and others added 30 commits July 2, 2025 17:42
Adjust field name in hostheartbeat queries
Set debug port in docker
@ashokbytebytego ashokbytebytego force-pushed the dynamic_profiling_intel_sync branch from 8b18493 to 86e6ca7 Compare November 18, 2025 22:14
ashokbytebytego and others added 2 commits November 19, 2025 15:33
- Add PostgreSQL schemas for dynamic profiling tables
- Add Python Pydantic models for API requests/responses
- Add 4 REST API endpoints for dynamic profiling:
  * POST /api/metrics/profile_request
  * POST /api/metrics/heartbeat
  * POST /api/metrics/command_completion
  * GET /api/metrics/profiling/host_status
- Add comprehensive documentation and setup guides
- Add unit tests for profiling host status functionality
- Includes Slack notification support for profiling events

This contribution provides the complete dynamic profiling feature for
Intel's gprofiler-performance-studio, enabling start/stop profiling
commands, heartbeat monitoring, and host status tracking.

Co-authored-by: Pinterest Engineering <[email protected]>
@ashokbytebytego ashokbytebytego force-pushed the dynamic_profiling_intel_sync branch from 86e6ca7 to eb4cc45 Compare November 19, 2025 15:53
Remove files that are specific to Pinterest's infrastructure:
- .github/workflows/sync-upstream.yml (Pinterest CI/CD)
- DEPLOYMENT_CHECKLIST.md (Pinterest deployment docs)
- deploy/localstack_init/01_init_s3_sqs.sh (Pinterest testing)
- docs/METRICS_PUBLISHER_INDEXER_DOCUMENTATION.md (Pinterest metrics)
- docs/SLI_METRICS_IMPLEMENTATION.md (Pinterest SLI metrics)
- src/gprofiler/backend/utils/metrics_publisher.py (Pinterest code)
- src/gprofiler_indexer/metrics_publisher.go (Pinterest code)

These files are not part of the dynamic profiling contribution to Intel.
- Remove MetricsPublisher import from main.py
- Remove startup/shutdown event handlers for MetricsPublisher
- Remove all send_sli_metric() calls from profiles_routes.py

These are Pinterest-specific metrics tracking not needed for Intel PR.
- Remove MetricsPublisher configuration from args.go
- Remove metricsPublisher initialization from main.go
- Remove all SendSLIMetric() calls from queue.go and worker.go
- Remove related comments

These are Pinterest-specific metrics tracking not needed for Intel PR.
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Pull request overview

This PR implements the foundational infrastructure for a dynamic profiling feature in gProfiler Performance Studio, introducing PostgreSQL database schemas, Python API models, comprehensive testing framework, and frontend UI for remote profiling control.

Key Changes:

  • PostgreSQL database schemas for profiling requests, commands, heartbeats, and execution tracking
  • Pydantic API models for type-safe profiling operations (start/stop, host-level, process-level)
  • Comprehensive test infrastructure with Docker Compose orchestration and pytest-based unit/integration tests
  • Frontend UI for profiling status monitoring with filtering, auto-refresh, and profiler configuration

Reviewed changes

Copilot reviewed 70 out of 73 changed files in this pull request and generated 4 comments.

Show a summary per file
File Description
scripts/setup/postgres/gprofiler_recreate.sql Adds 4 core tables (ProfilingRequests, ProfilingCommands, HostHeartbeats, ProfilingExecutions) with indexes for dynamic profiling
src/gprofiler/backend/models/metrics_models.py Defines Pydantic models for profiling requests, heartbeats, and command completion with validation
src/gprofiler/backend/routers/metrics_routes.py Implements 4 REST endpoints for profiling lifecycle management (create request, heartbeat, completion, status)
test/docker-compose.yml Docker Compose configuration for test environment with all service dependencies
src/tests/unit/backend/test_profiling_host_status.py 22 unit tests validating filtering, performance, and data consistency for host status endpoint
src/tests/integration/backend_db/test_create_profile_request.py 9 end-to-end integration tests covering profiling workflows from API to database
src/gprofiler/frontend/src/components/console/ProfilingStatusPage.jsx React component implementing profiling control UI with real-time updates and advanced configuration

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AWS_SESSION_TOKEN=

# postgres:
TEST_TEST=
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The variable name TEST_TEST is unclear and appears to be a placeholder or typo. Consider renaming to something more descriptive like TEST_MODE or removing if unused.

Suggested change
TEST_TEST=

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Region: aws.String(args.AWSRegion),
Endpoint: aws.String(args.AWSEndpoint),
Region: aws.String(args.AWSRegion),
Endpoint: aws.String(args.AWSEndpoint),
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The addition of S3ForcePathStyle: aws.Bool(true) changes S3 path handling behavior but lacks explanation. Add a comment explaining why path-style addressing is required (e.g., for LocalStack compatibility or S3-compatible services).

Suggested change
Endpoint: aws.String(args.AWSEndpoint),
Endpoint: aws.String(args.AWSEndpoint),
// Use path-style addressing for S3 to support custom endpoints (e.g., LocalStack, MinIO, or other S3-compatible services)

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log.Infof("DEBUG: Sending metric record to channel - ServiceId=%d, HostName=%s, HTMLPath=%s",
serviceId, hostname, path)
pw.metricsRecords <- metricRecord
log.Infof("DEBUG: Metric record sent to channel successfully")
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Debug logging statements should be removed before merging to production. These appear to be temporary debugging code added during development.

Suggested change
log.Infof("DEBUG: Metric record sent to channel successfully")

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Comment on lines 297 to 306
log.Infof("DEBUG: hostname=%s, htmlBlobPath='%s', CPUAvg=%f, MemoryAvg=%f",
fileInfo.Metadata.Hostname, htmlBlobPath, fileInfo.Metrics.CPUAvg, fileInfo.Metrics.MemoryAvg)

if htmlBlobPath != "" || (fileInfo.Metrics.CPUAvg != 0 && fileInfo.Metrics.MemoryAvg != 0) {
log.Infof("DEBUG: Writing metrics for hostname=%s", fileInfo.Metadata.Hostname)
pw.writeMetrics(uint32(serviceId), fileInfo.Metadata.CloudInfo.InstanceType,
fileInfo.Metadata.Hostname, timestamp, fileInfo.Metrics.CPUAvg,
fileInfo.Metrics.MemoryAvg, htmlBlobPath)
} else {
log.Infof("DEBUG: SKIPPING metrics write for hostname=%s - condition failed", fileInfo.Metadata.Hostname)
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Multiple DEBUG logging statements should be removed or converted to proper debug level logging before production deployment.

Suggested change
log.Infof("DEBUG: hostname=%s, htmlBlobPath='%s', CPUAvg=%f, MemoryAvg=%f",
fileInfo.Metadata.Hostname, htmlBlobPath, fileInfo.Metrics.CPUAvg, fileInfo.Metrics.MemoryAvg)
if htmlBlobPath != "" || (fileInfo.Metrics.CPUAvg != 0 && fileInfo.Metrics.MemoryAvg != 0) {
log.Infof("DEBUG: Writing metrics for hostname=%s", fileInfo.Metadata.Hostname)
pw.writeMetrics(uint32(serviceId), fileInfo.Metadata.CloudInfo.InstanceType,
fileInfo.Metadata.Hostname, timestamp, fileInfo.Metrics.CPUAvg,
fileInfo.Metrics.MemoryAvg, htmlBlobPath)
} else {
log.Infof("DEBUG: SKIPPING metrics write for hostname=%s - condition failed", fileInfo.Metadata.Hostname)
log.Debugf("DEBUG: hostname=%s, htmlBlobPath='%s', CPUAvg=%f, MemoryAvg=%f",
fileInfo.Metadata.Hostname, htmlBlobPath, fileInfo.Metrics.CPUAvg, fileInfo.Metrics.MemoryAvg)
if htmlBlobPath != "" || (fileInfo.Metrics.CPUAvg != 0 && fileInfo.Metrics.MemoryAvg != 0) {
log.Debugf("DEBUG: Writing metrics for hostname=%s", fileInfo.Metadata.Hostname)
pw.writeMetrics(uint32(serviceId), fileInfo.Metadata.CloudInfo.InstanceType,
fileInfo.Metadata.Hostname, timestamp, fileInfo.Metrics.CPUAvg,
fileInfo.Metrics.MemoryAvg, htmlBlobPath)
} else {
log.Debugf("DEBUG: SKIPPING metrics write for hostname=%s - condition failed", fileInfo.Metadata.Hostname)

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Just reviewed few files yet. Will continue

```bash
# Test Case: Create profiling request with PerfSpect enabled
curl -X POST http://localhost:8080/api/metrics/profile_request \
-u "prashantpatel:password" \
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please delete the user id.

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Done

)
raise HTTPException(400, {"message": "Failed to register the new service"})
return ProfileResponse(message="ok", gpid=int(gpid))
# Server error - counts against SLO raise HTTPException(400, {"message": "Failed to register the new service"})
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Please check if commenting out "raise" and "return" statements is intentional.

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Hi @mlim19 , The raise and return statements are not commented out - they are fully active and functional.
The confusion may be coming from how GitHub displays the diff. The removed MetricsPublisher code (between the comment and the raise statement) might make it appear compressed in the diff view.

- Removed metricsPublisher initialization and cleanup calls from main.go
- This completes the cleanup of Pinterest-specific metrics code
- Indexer now builds successfully in Docker
- Fixed multiple statements on same line (syntax errors from previous cleanup)
- Split logger.error() and raise HTTPException() onto separate lines
- Fixed indentation after except blocks
- All services now build and run successfully
@skamerintel skamerintel self-requested a review December 17, 2025 17:06
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PR #78 - Required Fixes Before Approval

Date: December 16, 2024
PR: #78

The following issues must be resolved before this PR can be approved for merge:

  1. DEPLOYMENT CONFIGURATION (deploy/.env)

ISSUE 1.a: AWS Configuration Hardcoded

  • Lines 7, 35-38: AWS_REGION, BUCKET_NAME, and SQS URLs are hardcoded
  • REQUIRED FIX: Keep these fields empty/configurable as they were in master branch
  • RATIONALE: S3 bucket names must be globally unique; regions vary by deployment

ISSUE 1.b: LocalStack Configuration in Production File

  • Lines 49-68: LocalStack and test metrics configuration
  • REQUIRED FIX: Remove lines 49-68 entirely OR move to separate .env.local file
  • These include:
    • LocalStack endpoints (lines 53-55)
    • Metrics configuration with test values (lines 57-67)
  • RATIONALE: LocalStack is dev-only; metrics should default to disabled

ISSUE 1.c: Metrics Configuration

  • If metrics feature is retained, METRICS_ENABLED must default to "false"
  • Provide documentation for metrics host setup if this feature is included
  • Remove test UUIDs and localhost endpoints
  1. DOCKER COMPOSE SECURITY (deploy/docker-compose.yml)

ISSUE 2.a: PostgreSQL Port Exposed

  • Lines 58-59: Exposes database port 5432 to all network interfaces
  • REQUIRED FIX: Remove these lines or comment them out
  • RATIONALE: Containers communicate internally; external exposure is security risk

ISSUE 2.b: LocalStack as Production Dependency

  • Lines 96, 104, 119, 220, 233: LocalStack hardcoded in service configurations
  • Lines 242-266: LocalStack service definition
  • REQUIRED FIX:
    • Remove LocalStack from main docker-compose.yml
    • Create separate docker-compose.local.yml for development
    • Remove LocalStack from service dependencies
  • RATIONALE: Production should use real AWS services, not emulator
  1. DATABASE MIGRATION (scripts/setup/postgres/)

ISSUE 3.a: No Migration Strategy

  • dynamic_profiling_schema.sql adds 10+ new tables
  • No migration scripts for existing deployments
  • REQUIRED FIX:
    • Provide upgrade script: migrations/add_dynamic_profiling.up.sql
    • Provide rollback script: migrations/add_dynamic_profiling.down.sql
    • Document migration process
  • RATIONALE: Existing production deployments need safe upgrade path

ACCEPTANCE CRITERIA

[ ] deploy/.env has no hardcoded AWS values
[ ] deploy/.env has no LocalStack configuration
[ ] deploy/docker-compose.yml has no exposed database ports
[ ] deploy/docker-compose.yml has no LocalStack dependencies
[ ] Migration scripts provided for schema changes

- Remove hardcoded AWS config and LocalStack from deploy/.env
- Remove LocalStack service from deploy/docker-compose.yml
- Remove exposed PostgreSQL port from docker-compose.yml
- Add database migrations (up/down) for dynamic profiling
@ashokbytebytego
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@skamerintel I have addressed all review comments.

@ashokbytebytego
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@mlim19 @skamerintel Can you please review when you get some time? thank you

@mlim19
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mlim19 commented Jan 12, 2026

@ashokbytebytego and @prashantbytesyntax I successfully got the changes working in my local machine. It looks good so far but will evaluate with the changes in gprofiler agent side.
In the meantime, please address the outstanding CI build issues.

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7 participants