Open Issues Need Help
View All on GitHubAI Summary: This issue proposes the implementation of a webhook system to notify external systems about changes to feature flags. The system will allow administrators to register webhook URLs, trigger notifications on flag creation, update, or deletion, and filter events by specific flags, projects, or environments. It will also include features for retry logic, signature verification, and delivery tracking.
AI Summary: This issue proposes building a Go-based CLI tool named 'flagship' to streamline feature flag management for operations and CI/CD pipelines. The tool will support CRUD operations, bulk import/export, environment switching, validation, and configuration management, addressing current pain points like verbose cURL commands and lack of automation.
AI Summary: This issue proposes implementing a flexible targeting system for feature flags, moving beyond simple on/off or percentage rollouts. It aims to allow targeting based on user attributes, geography, and complex logical combinations using an expression DSL, with JSON Logic or CEL being considered as potential solutions.
AI Summary: This issue proposes the implementation of a feature rollout engine that supports gradual rollouts, deterministic user assignment, and variant splits for A/B testing. The solution involves using consistent hashing on user IDs and flag keys to assign users to buckets, which are then compared against defined rollout percentages.
AI Summary: This issue proposes adding comprehensive automated tests for ETag and Server-Sent Events (SSE) semantics in the codebase. The goal is to improve reliability, prevent regressions, and increase confidence in refactoring by introducing unit, integration, SSE, ETag, and concurrency tests.
AI Summary: This issue proposes to refactor the persistence layer by introducing a unified `Store` interface. This interface will abstract away the underlying storage mechanism, allowing for interchangeable implementations like an in-memory store for development and a PostgreSQL store for production. The goal is to improve abstraction, feature parity, efficiency, and flexibility for persistence operations.