docker.recipes

HyperDX

intermediate

Open-source observability platform unifying logs, metrics, traces, and session replays.

Overview

HyperDX is an open-source observability platform that provides unified monitoring by combining logs, metrics, traces, and session replays into a single interface. Launched as an alternative to expensive commercial solutions like Datadog, HyperDX offers natural language search capabilities and automatic correlation between different telemetry data types, making it easier for developers to debug and monitor their applications without switching between multiple tools. This deployment uses a single all-in-one HyperDX container that includes built-in ClickHouse for analytics storage and MongoDB for metadata management. The container exposes both the web interface on port 8080 and an OpenTelemetry Protocol (OTLP) endpoint on port 4318, allowing applications to send telemetry data directly using standard OpenTelemetry SDKs. The setup provides persistent data storage and requires only an API key for authentication. This configuration is ideal for development teams, DevOps engineers, and organizations seeking cost-effective observability without vendor lock-in. The unified interface eliminates the complexity of managing separate logging, tracing, and monitoring tools while providing enterprise-grade features like distributed tracing correlation and session replay analysis.

Key Features

  • Unified search interface across logs, traces, metrics, and session replays with natural language queries
  • Built-in OpenTelemetry Protocol (OTLP) endpoint for direct integration with OpenTelemetry SDKs
  • Automatic correlation between logs, traces, and user sessions for faster root cause analysis
  • Real-time distributed tracing visualization with dependency mapping
  • Session replay functionality to reproduce user interactions during errors
  • ClickHouse-powered analytics engine for high-performance log aggregation and queries
  • Custom dashboards and alerts with support for complex queries and filtering
  • API-driven architecture enabling programmatic access to observability data

Common Use Cases

  • 1Development teams needing unified observability during application debugging and performance optimization
  • 2Startups and small companies seeking cost-effective alternatives to expensive commercial APM solutions
  • 3Organizations migrating from proprietary monitoring tools to open-source observability platforms
  • 4DevOps teams implementing comprehensive monitoring for microservices architectures
  • 5Support teams requiring correlated telemetry data to resolve customer-reported issues quickly
  • 6Engineering teams building custom monitoring solutions with API-driven observability data access
  • 7Companies needing on-premises observability solutions due to compliance or data sovereignty requirements

Prerequisites

  • Docker and Docker Compose installed with minimum 4GB RAM allocated to Docker
  • Available ports 8080 and 4318 on the host system for web interface and OTLP ingestion
  • Valid HYPERDX_API_KEY environment variable configured for authentication and data ingestion
  • Applications instrumented with OpenTelemetry SDKs or compatible logging frameworks
  • Basic understanding of observability concepts including logs, traces, and metrics correlation
  • At least 10GB available disk space for telemetry data storage and ClickHouse analytics

For development & testing. Review security settings, change default credentials, and test thoroughly before production use. See Terms

docker-compose.yml

docker-compose.yml
1services:
2 hyperdx:
3 image: hyperdx/hyperdx:latest
4 container_name: hyperdx
5 restart: unless-stopped
6 environment:
7 HYPERDX_API_KEY: ${HYPERDX_API_KEY}
8 ports:
9 - "8080:8080"
10 - "4318:4318"
11 volumes:
12 - hyperdx_data:/data
13 networks:
14 - hyperdx-network
15
16volumes:
17 hyperdx_data:
18
19networks:
20 hyperdx-network:
21 driver: bridge

.env Template

.env
1HYPERDX_API_KEY=your-api-key

Usage Notes

  1. 1Docs: https://www.hyperdx.io/docs
  2. 2Dashboard at http://localhost:8080 - unified search across logs/traces/metrics
  3. 3OTLP endpoint on port 4318 - use OpenTelemetry SDKs
  4. 4Auto-correlates logs, traces, and session replays
  5. 5Search with natural language or structured queries
  6. 6Open-source alternative to Datadog with similar UX

Quick Start

terminal
1# 1. Create the compose file
2cat > docker-compose.yml << 'EOF'
3services:
4 hyperdx:
5 image: hyperdx/hyperdx:latest
6 container_name: hyperdx
7 restart: unless-stopped
8 environment:
9 HYPERDX_API_KEY: ${HYPERDX_API_KEY}
10 ports:
11 - "8080:8080"
12 - "4318:4318"
13 volumes:
14 - hyperdx_data:/data
15 networks:
16 - hyperdx-network
17
18volumes:
19 hyperdx_data:
20
21networks:
22 hyperdx-network:
23 driver: bridge
24EOF
25
26# 2. Create the .env file
27cat > .env << 'EOF'
28HYPERDX_API_KEY=your-api-key
29EOF
30
31# 3. Start the services
32docker compose up -d
33
34# 4. View logs
35docker compose logs -f

One-Liner

Run this command to download and set up the recipe in one step:

terminal
1curl -fsSL https://docker.recipes/api/recipes/hyperdx/run | bash

Troubleshooting

  • Container fails to start with 'API key invalid' error: Verify HYPERDX_API_KEY environment variable is set correctly in your .env file
  • Web interface shows 'No data available' despite sending telemetry: Check that applications are sending data to port 4318 using OTLP protocol, not other formats
  • High memory usage and container restarts: Increase Docker memory limits to at least 4GB as ClickHouse requires substantial RAM for analytics processing
  • OTLP endpoint connection refused on port 4318: Ensure the port is properly exposed and not blocked by firewall rules or conflicting services
  • Search queries return incomplete results: Allow time for data indexing in ClickHouse, especially for large log volumes or complex trace spans
  • Session replays not appearing in interface: Verify frontend applications have HyperDX browser SDK installed and configured with correct API endpoint

Community Notes

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