1. Telemetry & Data Acquisition
FoxCloud OpenAPI
Vpp Flow
  • Vpp Flow
  • Full API Reference
  • What's New & Milestones
  • Getting Started
    • 1. Overview & Integration Scope
    • 2. Environments & Prerequisites
  • End-User Enrollment & OAuth Flow
    • 0. Introduction
    • 1. The User Authorization Journey
    • 2. OAuth Token Operating Model
    • 3. Implementation Guide
  • API Technical Specifications
    • 1. Universal Request Rules
    • 2. Rate Limiting Strategy
    • 3. Response Structure
    • 4. Error Code Reference
  • Telemetry & Data Acquisition
    • 1. Data Pipeline & Scaling Strategy
    • 2. Telemetry Data Query (Real-time)
    • 4. Telemetry Variable Dictionary
    • 5. System Performance & SLA
    • 3. Device Configuration & Settings: Pre-Dispatch State Awareness
  • Control Commands & Dispatch
    • 1. Core Dispatch Architecture: Scheduler V3
    • 2. Scheduler V3 Operations
    • 3. Real-time Device Settings
    • 4. Strategic Roadmap: Scaling for Massive Fleets
  • FAQ
    • Troubleshooting Quick Guide
  1. Telemetry & Data Acquisition

1. Data Pipeline & Scaling Strategy

FoxCloud provides robust data acquisition mechanisms tailored to different scales of VPP operations. While API Polling serves as the default entry point, our architecture is actively evolving to support massive-scale, low-latency data interactions via Kafka.

1.1 Current Modes: API Polling vs. Kafka Streaming#

FeatureAPI Polling (Default)Kafka Streaming (Advanced)
MechanismPull-based. Your platform requests data at fixed intervals.Push-based. FoxCloud pushes data to your Kafka topic immediately.
Latency5 Minutes1 Minute
Best ForSmall-scale pilots, Billing, Daily Reports.High-frequency Trading, Real-time Alarms, Large-scale Aggregation.
SetupReady to use after onboarding.Submit Kafka request form via Client App > Integration > Telemetry.

1.2 Future Roadmap: Kafka-Driven Scheduling#

Strategic Evolution for Large-Scale VPPs
While HTTP-based API calls are sufficient for standard telemetry, we recognize that pure HTTP polling creates significant service performance pressure in large-scale dispatching scenarios (e.g., managing tens of thousands of inverters simultaneously).
To address this, FoxCloud is actively developing and perfecting a Kafka-based Scheduling Solution. This next-generation architecture will allow your platform to:
Receive Real-time Telemetry: Push-based data delivery eliminates the overhead of high-frequency polling.
Execute High-Concurrency Dispatch: Send control commands via Kafka queues, ensuring reliable, low-latency delivery even during peak grid events.
Recommendation: If you are planning a large-scale VPP deployment or require sub-minute device action, we strongly recommend contacting our team early to discuss the roadmap and prepare for the upcoming Kafka scheduling capabilities.
Modified at 2026-07-07 14:56:21
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