Monitoring GraphQL Gateways with OpenTelemetry

The Importance of Monitoring GraphQL Gateways

GraphQL Gateways play a crucial role in modern API architectures, acting as the central point for request routing, schema composition, and performance optimization. As these gateways handle increasing amounts of traffic and complexity, monitoring their performance and behavior becomes essential for maintaining reliable and efficient systems.

Current State of GraphQL Gateway Monitoring

Traditionally, monitoring GraphQL Gateways has been challenging due to several factors. The distributed nature of these systems, where gateways communicate with multiple subgraphs, makes it difficult to trace requests across the entire system. The gateway’s query planning phase, which determines how to split and route queries across subgraphs, is a critical but often opaque process that can significantly impact performance.

Complex queries that span multiple subgraphs make it challenging to identify which part of the execution is causing slowness, whether it’s the gateway’s planning, a specific subgraph, or the network communication. When errors occur, it’s often difficult to trace whether they originate from the gateway itself, a specific subgraph, or the communication between them, making debugging a complex process.

OpenTelemetry: A Game-Changer for GraphQL Monitoring

OpenTelemetry has emerged as a powerful solution for monitoring GraphQL Gateways. It provides consistent APIs for collecting metrics, traces, and logs across different programming languages and frameworks, offering standardized instrumentation that makes monitoring more reliable and consistent. The ability to propagate context across service boundaries helps track requests through the entire system, while its vendor-agnostic approach allows you to choose your preferred observability backend.

As an open-source project, OpenTelemetry perfectly aligns with The Guild’s values of transparency and community-driven development. This commitment to openness ensures that the monitoring solution can evolve with the community’s needs and maintain high standards of quality and reliability.

Key Metrics and Traces for GraphQL Gateways

When monitoring GraphQL Gateways with OpenTelemetry, several key aspects come into focus. The request lifecycle tracing provides visibility into HTTP request/response flows and GraphQL operation execution, including query parsing and validation timing. This comprehensive view helps understand how requests are processed at each stage.

Subgraph communication monitoring reveals the interactions between the gateway and its subgraphs, tracking upstream HTTP fetch calls, execution timing, and status. This information is crucial for identifying bottlenecks and issues in the distributed system. Operation performance metrics, including overall query execution time, subgraph-specific execution times, error rates, and request throughput, provide the quantitative data needed to assess system health and performance.

Hive Gateway’s OpenTelemetry Integration

We’re excited to announce significant improvements to Hive Gateway’s OpenTelemetry integration. These enhancements bring detailed request tracing across subgraphs, with automatic span creation for schema operations and seamless context propagation between services. The integration provides real-time performance metrics and detailed error tracking, enabling comprehensive resource utilization monitoring.

The improved debugging capabilities include better error context, request/response correlation, and performance bottleneck identification. These features make it easier to diagnose and resolve issues in your GraphQL infrastructure.

Getting Started with Hive Gateway’s OpenTelemetry Integration

You can try the new OpenTelemetry integration with Hive Gateway by simply enabling it in your gateway configuration! We support most used exporters out of the box, but you can also import your own custom ones.

If you don’t already have a tracing backend setup, you can use our OpenTelemetry example repository to get started.

import { createOtlpHttpExporter, defineConfig } from "@graphql-hive/gateway";
import { createOtlpHttpExporter, setupOpenTelemetry } from "@graphql-hive/opentelemetry-setup";
 
setupOpenTelemetry({
  exporters: [
    createOtlpHttpExporter({ url: "http://localhost:4317" }),
  ],
});
 
export const gatewayConfig = defineConfig({
  openTelemetry: {
    tracing: true,
  }
});

This configuration enables OpenTelemetry tracing with HTTP OTLP exporter. The exporter will automatically set up the Node.js OpenTelemetry SDK and ensure trace context is properly propagated across service boundaries.

Future Improvements

The OpenTelemetry integration we’re releasing today lays the foundation for several exciting future improvements. Thanks to OpenTelemetry’s unified context, metrics, logs, and traces will be automatically correlated, making it easier to debug errors and performance issues. When a problem occurs, you’ll be able to jump from a slow query trace directly to the relevant logs and metrics, providing a complete picture of what happened during problematic requests.

Conclusion

Hive Gateway’s new OpenTelemetry integration brings comprehensive monitoring capabilities to your GraphQL infrastructure. By providing detailed traces, metrics, and logs with unified context, it helps you identify and resolve issues faster, whether they’re in the gateway, subgraphs, or the communication between them.

To learn more about Hive Gateway’s OpenTelemetry integration or to get started with monitoring your GraphQL Gateway, visit our documentation or contact our team.