How to Keep Flight Fares Fresh with Starlink in Real Time

You’re an AI assistant helping travel agencies build a real-time flight pricing engine for airlines that push fare feeds over a Starlink-based internet connection. The goal is to guarantee that the fares shown to customers are always up-to-date within a one-minute window, even though different providers refresh their feeds at irregular intervals and the satellite link suffers from variable latency. **Objectives** 1. Pull dynamic fare feeds from the Starlink API endpoint. 2. Compensate for latency and differing update cycles using an adaptive algorithm. 3. Maintain a local fallback cache that predicts expected rates when the live feed is delayed. 4. Expose a clean, JSON-based interface for the front-end to display current fares. **Required Inputs** - `[feed_api_endpoint]`: The HTTPS URL of the Starlink flight fare feed. - `[latency_threshold_ms]`: The maximum acceptable latency in milliseconds before the system switches to fallback logic. - `[refresh_interval_seconds]`: How often (in seconds) the system should poll the feed. - `[cache_ttl_seconds]`: Time-to-live for the local predictive cache. - `[provider_id]`: Identifier for the airline provider. **Step-by-Step Process** 1. **Initialization**: Configure the HTTP client with retry logic, exponential backoff, and set the maximum concurrent connections based on the provider’s throttle limits. 2. **Feed Retrieval**: Every `[refresh_interval_seconds]`, send a GET request to `[feed_api_endpoint]` with headers including an API key and timestamp. 3. **Latency Measurement**: Record round-trip time. If the measured latency > `[latency_threshold_ms]`, tag the response as *delayed*. 4. **Data Validation**: Verify the response schema (price, currency, flight number, timestamp). Log any anomalies. 5. **Compensation Algorithm**: - For *on-time* feeds: update the in-memory store and push a change event to the front-end via WebSocket. - For *delayed* feeds: calculate an expected price by interpolating between the last two on-time values. Store this in the fallback cache. 6. **Cache Management**: Prune entries older than `[cache_ttl_seconds]`. Persist the cache to a fast key-value store (Redis) for high availability. 7. **API Output**: Expose a `/current-fares` endpoint that returns `{ "provider_id": "XYZ", "flights": [...] }` in JSON.