Hive is an open-source GraphQL platform designed to help teams manage, monitor, and secure their GraphQL APIs—whether they use federation, stitching, or standalone endpoints. Built by The Guild, it provides a schema registry that prevents breaking changes, tracks usage patterns, and integrates with CI/CD pipelines. With both cloud-hosted and self-hosted options, Hive empowers developers to gain visibility into their GraphQL APIs’ performance, evolution, and consumer behavior without vendor lock-in. It’s ideal for engineering teams managing complex GraphQL architectures at scale, especially those using GitHub Actions, GitLab CI, or similar tooling to enforce schema safety.
What You Get
- Schema Registry - Tracks and versionizes GraphQL schemas across federation and standalone APIs, with full change history and CDN-backed high availability via Cloudflare.
- Breaking Change Prevention - Automatically analyzes schema changes against live operations to detect breaking modifications before deployment, configurable via Slack, GitHub, or custom webhooks.
- Performance Monitoring - Collects real-time metrics including query latency, RPM, error rates, and active client counts to identify slow or problematic operations.
- CI/CD Integration - Hive CLI enforces schema validation in GitHub, BitBucket, and Azure DevOps pipelines using
hive schema:check to block merges on breaking changes.
- GitHub PR Status Checks - Native GitHub App automatically adds commit status checks to pull requests, showing schema validation results directly in the PR interface.
- Multi-Source Schema Support - Supports GraphQL Federation, Stitching, and standalone APIs with unified schema composition and visualization.
Common Use Cases
- Building a federated GraphQL gateway with multiple microservices - Teams using Apollo Federation or graphql-tools stitching use Hive to validate schema changes across services before deployment, ensuring compatibility and preventing runtime failures.
- Scaling a public GraphQL API with 10k+ daily queries - Monitoring features help identify high-latency operations and frequent errors, enabling proactive optimization before users are impacted.
- Problem: Breaking schema changes in PRs cause production outages → Solution: Hive’s GitHub App blocks merges if a schema change violates operational contracts, enforced via
hive schema:check in CI
- DevOps teams managing GraphQL APIs across multiple environments - Hive’s self-hosted option allows deployment on K8s with Postgres, Redis, and ClickHouse for centralized schema governance and analytics without relying on third-party SaaS.
Under The Hood
GraphQL Hive Console is a sophisticated platform designed for managing, monitoring, and governing GraphQL APIs at scale. It combines modern infrastructure patterns with a strong emphasis on observability, developer experience, and extensibility across distributed systems.
Architecture
The system follows a modular monorepo architecture that enables clear separation of concerns across libraries, services, and deployment configurations.
- The codebase is organized into distinct packages with well-defined roles for core functionality, tooling, and infrastructure.
- Extensive use of configuration-driven setups and custom span processors supports flexible and scalable deployment models.
- A robust API gateway and service integration layer facilitate communication between components and external systems.
Tech Stack
The project leverages a multi-language tech stack centered on TypeScript and Rust, integrating modern web and cloud-native tools.
- Built primarily with TypeScript and React/Next.js for frontend, complemented by Rust for performance-critical backend services.
- Integrates extensively with GraphQL-Hive ecosystem, OpenTelemetry, Pulumi, and cloud-native platforms like Kubernetes and AWS.
- Employs Turborepo for monorepo management, tsup and vitest for builds and tests, and Docker for containerized deployments.
Code Quality
The codebase reflects a mature approach to testing and error handling, with consistent patterns across modules.
- Comprehensive test coverage includes unit, integration, and end-to-end scenarios with Vitest and Cypress.
- Error handling is implemented using standard try/catch patterns, ensuring resilience in distributed environments.
- Code style and naming conventions are mostly consistent, although some structural complexity introduces maintainability challenges.
What Makes It Unique
GraphQL Hive Console distinguishes itself through its deep integration of observability, infrastructure flexibility, and developer-centric tooling.
- Offers modular deployment support across Kubernetes, Docker, and cloud services, enabling diverse operational models.
- Native integration with Grafana dashboards and OpenTelemetry extensions provides real-time schema and performance insights.
- Strong emphasis on secret management and configuration abstraction enables secure, dynamic handling of environment-specific settings.
- A TypeScript-first approach with rich UI components simplifies schema composition, usage tracking, and API governance for developers.