I started with the obvious stuff: watch for 5xx errors and 429s, track latency p99.
Start by clarifying requirements and constraints, then propose a high-level architecture with a routing layer, health monitors, and a circuit breaker. Explain the signals that trigger failover and how hysteresis, cooldowns, and health checks prevent flapping.
Pro tip: Emphasize that failover should be based on a combination of error rates, latency, and rate-limit headers, not just binary up/down. Use a state machine with half-open probing to safely test recovery and avoid flapping.
Ask about expected traffic volume, latency SLAs, provider diversity, cost considerations, and whether requests are idempotent. This shapes the design and trade-offs.
Outline components: request router, provider adapters, health monitor, circuit breaker, and fallback logic. Consider a control plane for configuration and a data plane for request handling.
Specify the signals that trigger failover: error rates (5xx, timeouts), latency percentiles, rate-limit headers (429), and provider health checks. Combine them into a health score.
Use a circuit breaker with states (closed, open, half-open). Implement hysteresis: require sustained failure to open and sustained success to close. Add cooldown periods and exponential backoff for probes.
Address trade-offs: latency vs. reliability, cost of fallback, data consistency, and observability. Mention monitoring, alerting, and gradual rollout of changes.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the gateway's role and logging requirements, then propose a structured data model with fields for request/response, trace context, and metadata. Discuss how metrics are derived from logs for dashboards, and address retention, PII, and fallback policy configuration with trade-offs between static and adaptive approaches.
Pro tip: Emphasize that logging should be designed for both operational debugging and product analytics, and that PII handling must be compliant and configurable per environment. Show awareness of cost and performance implications of high-volume logging.
Ask about scale, latency sensitivity, compliance needs, and existing infrastructure. Understand what the gateway does and what insights are needed from logs.
Define a schema with fields for request (method, path, headers, body), response (status, latency, body), trace/span IDs, user/session IDs, and timestamps. Use JSON for flexibility and include a version field.
Derive metrics like request rate, error rate, latency percentiles, and payload sizes. Surface them in dashboards for real-time monitoring and historical analysis, with drill-down to logs.
Implement tiered retention (hot/warm/cold) and anonymize or redact PII at ingestion. Use configurable policies per data type and comply with regulations like GDPR.
Choose between static (fixed thresholds) and adaptive (dynamic based on load/error rates) fallback. Explain trade-offs: static is predictable, adaptive is resilient but complex.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.