OpenFeature at Dynatrace: Enhancing Confidence Through Feature Flagging

Introduction

Feature flagging has emerged as a critical tool for managing software development and deployment workflows, enabling teams to control feature availability dynamically. OpenFeature, an open-source initiative under the Cloud Native Computing Foundation (CNCF), provides a standardized framework for feature flagging, offering flexibility, scalability, and observability. This article explores how Dynatrace leveraged OpenFeature to address longstanding challenges in their feature flagging infrastructure, ultimately enhancing engineering confidence and operational efficiency.

Technical Overview of OpenFeature

OpenFeature is a vendor-agnostic framework designed to standardize feature flagging across diverse programming languages and environments. Its core components include:

• API Interface: A unified API for evaluating feature flags, allowing developers to integrate flags seamlessly into their applications.
• Providers: Mechanisms for sourcing flag configurations, such as databases, environment variables, or external services.
• flagd D: A real-time evaluation engine that supports dynamic flag updates, context-based targeting, and advanced roll-out strategies.

By abstracting the complexities of flag management, OpenFeature enables teams to focus on delivering value while maintaining control over feature visibility.

Key Features and Benefits

Performance and Scalability

OpenFeature is engineered for high throughput and low latency, with:

• Backend evaluation latency: <1 millisecond
• Frontend evaluation latency: ~20 milliseconds
• High-frequency support: Capable of handling up to 60,000 evaluations per second in development environments

These metrics ensure seamless integration into both small-scale and enterprise-grade applications.

Advanced Targeting and Experimentation

OpenFeature supports granular targeting rules, enabling:

• Context-based evaluation: Flags can be tailored to users, geographic regions, device types, or other attributes
• Gradual rollouts: Features can be released to subsets of users (e.g., 1%, 10%, 50%) for testing
• Observability: Built-in metrics and tracing capabilities for flag usage and impact analysis

Multi-language Support

By adopting OpenFeature, Dynatrace ensured consistency across their Java, React, and other language ecosystems, eliminating the fragmentation caused by legacy GitOps-based flag management.

Implementation at Dynatrace

Architecture and Workflow

Dynatrace implemented OpenFeature through a custom-built solution, integrating:

• flagd D: As the central flag evaluation engine, distributing flags to workloads via gRPC
• Custom database: Storing flag configurations with JSON-based rules and pseudo-random allocation
• Unified UI: A self-service platform for flag configuration, reducing reliance on GitOps workflows

The system leverages context injection (e.g., tenant IDs, geographic regions) and dynamic request headers to ensure accurate flag evaluation.

Migration Strategy

The transition from legacy systems involved:

1. Phased adoption: Encouraging teams to adopt OpenFeature while maintaining backward compatibility
2. UI simplification: Predefined attributes (e.g., cloud services, email domains) reduced configuration complexity
3. Provider flexibility: Supporting ConfigMap and environment variables eased migration for existing flag sources

Challenges and Solutions

Edge Case Management

Dynatrace encountered several challenges during implementation:

• Large numeric values: Storing nanoseconds or bytes led to Java overflow errors. This was resolved by enforcing strict type validation during flag creation.
• UI blocking: React SDKs experienced delays due to flag evaluation latency. Implementing timeouts and load indicators mitigated this issue.

Critical Incident Resolution

A critical incident occurred when flag evaluation failures caused 500 errors, leading to request pileups. Post-incident improvements included:

• Enhanced error handling: Automated retries and fallback mechanisms
• Monitoring enhancements: Real-time alerts for flag evaluation failures
• Validation pipelines: Pre-flight checks for flag values before deployment

Results and Impact

Adoption and Scalability

• Team adoption: 80+ teams now use OpenFeature, with flag counts approaching 1,000
• Performance: High-throughput environments sustain 60,000+ evaluations per second
• Use cases: Support for synchronous rollouts, threshold-based flags, and JavaScript Lambda ranges

Confidence and Operational Improvements

• Unified API: Reduced confusion across teams, improving collaboration
• Observability: Clear metrics enabled faster flag retirement and issue resolution
• Confidence boost: Engineers gained assurance in managing complex flag scenarios, reducing deployment risks

Conclusion

OpenFeature has transformed Dynatrace's approach to feature flagging, addressing scalability, performance, and operational challenges. By adopting this CNCF-standardized framework, the team achieved greater confidence in managing feature visibility, experimentation, and production stability. Key lessons include the importance of edge case validation, robust error handling, and maintaining a balance between flexibility and control. For organizations seeking to modernize their flagging infrastructure, OpenFeature offers a scalable, observable, and vendor-agnostic solution to enhance engineering confidence and operational efficiency.