Edge-first evaluation
The Rust edge server keeps flag state in memory, streams updates from the backend, and removes database calls from the hot path.
Feature flag delivery platform
FluxGate
Governed feature rollouts with a Rust control plane, low-latency edge evaluation, approval workflows, kill switches, variants, analytics, and OpenFeature-ready integration paths.
Key features
Built for release control, not only flag storage
FluxGate focuses on the operational parts that matter after a flag exists: targeting order, rollout approvals, kill switches, live analytics, and fast evaluation close to the application.
Governed rollout workflows
Approval policies, stage changes, RBAC, dependency checks, and audit trails make production rollout decisions explicit.
Variants beyond booleans
Return strings, numbers, booleans, or JSON values for experiments, configuration, pricing tests, and controlled UI changes.
Real-time analytics
Evaluation rates, success rates, cache behavior, experiments, and rollout activity stream into dashboards for live operational visibility.
Kill switch with rollback
Disable risky features quickly, schedule automatic re-enable windows, and keep the action visible in the rollout dashboard.
SDK and standards path
Use direct edge calls, the Spring Boot starter, or the OpenFeature Remote Evaluation Protocol path for portable integration.
Product screenshots
A control room for rollout decisions
The current implementation includes dashboard, feature, variant, approval, traffic management, and analytics views.
Architecture
Control plane, streaming updates, edge evaluation
The backend remains the source of truth. Edge nodes subscribe to feature changes, evaluate requests locally, and send evaluation telemetry back for dashboards and analysis.
Explore the architectureReact UIREST + WebSocket
Rust backendPostgres + gRPC
Rust edgecached evaluation
Apps + SDKsREST / OFREP
telemetry returns to dashboards
Performance
The hot path stays local
FluxGate's edge layer evaluates from in-memory state. Project load tests include 10x scenarios at 5,000 evaluations per second with stable memory notes and sub-millisecond reported latency.
- No database call in the evaluation hot path
- gRPC stream keeps edge caches synchronized
- Metrics flush back asynchronously for dashboards
Why FluxGate
A stronger fit when feature flags are part of delivery governance
Many open-source flag tools are excellent for flag management, experimentation, or Git-native configuration. FluxGate is narrower and more operational: edge-side evaluation, approvals, rollback controls, dependencies, and live rollout telemetry are first-class.
Compare the fitAnswers
Direct answers for buyers and answer engines
Short answers make the product easier to evaluate, quote, and compare.
What makes FluxGate different from simple feature toggles?
FluxGate treats flags as a delivery workflow. It combines variants, criteria priority, approvals, dependency checks, kill switches, edge evaluation, and analytics in one system.
Can FluxGate run close to application services?
Yes. The edge server is designed for sidecar-style or shared edge deployment. It evaluates from cached state and streams updates from the backend.
What applications are a good fit?
FluxGate fits teams that need controlled production rollouts, tenant or user targeting, internal platform governance, Java/Spring integration, and measurable rollout decisions.
Build with ForgeOps LABS
Need feature flag delivery, platform tooling, or rollout automation?
FluxGate shows the kind of end-to-end software ForgeOps LABS builds: backend, UI, infrastructure, integration, and operational workflows.