Design a weather data aggregation system that calls a third-party weather API and stores updates in a database every 10 minutes. Describe the architecture, scheduler design, rate-limiting and quota management, idempotency and deduplication, retries and backoff, schema design (hot vs. cold storage), caching strategy, data validation, multi-provider support, handling provider outages and delayed data, monitoring/alerting, and scalability across cities and regions.

This question evaluates competency in large-scale system design, distributed data ingestion, reliability engineering, rate-limiting and quota management, idempotency, and time-series data modeling specific to weather aggregation.

How do I approach System Design interview questions?

System Design questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master system design interviews.

What difficulty level is this interview question?

This is a hard difficulty System Design question, commonly asked during Onsite rounds at HubSpot.

What role is this question designed for?

This question is commonly asked for Software Engineer candidates at HubSpot during technical interviews.

Design a weather aggregation system | HubSpot Interview Question

System Design: Weather Data Aggregation (10-minute Updates)

Context

Build a service that periodically fetches weather data from third-party providers for many cities/regions, stores and serves the data reliably, and scales with growth. Assume near–real-time use cases (dashboards, alerts, APIs) and historical analytics.

Requirements

Design and describe the following aspects:

Architecture and data flow end-to-end.
Scheduler that triggers updates every 10 minutes across many cities and providers.
Rate-limiting and quota management for third-party APIs.
Idempotency and deduplication across retries and providers.
Retry strategy, backoff, circuit breaking, and dead-letter handling.
Schema design for hot vs. cold storage and partitioning.
Caching strategy for read performance and cost control.
Data validation, normalization, and quality checks.
Multi-provider support, abstraction, and result blending/failover.
Handling provider outages and delayed/late-arriving data.
Monitoring, alerting, and SLOs.
Scalability across cities and regions, including capacity planning.

State any assumptions you need and justify key trade-offs.

Requirements

Design and describe the following aspects:

Architecture and data flow end-to-end.

Scheduler that triggers updates every 10 minutes across many cities and providers.

Rate-limiting and quota management for third-party APIs.

Idempotency and deduplication across retries and providers.

Retry strategy, backoff, circuit breaking, and dead-letter handling.

Schema design for hot vs. cold storage and partitioning.

Caching strategy for read performance and cost control.

Data validation, normalization, and quality checks.

Multi-provider support, abstraction, and result blending/failover.

Handling provider outages and delayed/late-arriving data.

Monitoring, alerting, and SLOs.

Scalability across cities and regions, including capacity planning.

State any assumptions you need and justify key trade-offs.

Design a weather aggregation system

Quick Overview

System Design: Weather Data Aggregation (10-minute Updates)

Context

Requirements

Solution

Submit Your Answer to Earn 20XP

Design a weather aggregation system

Quick Overview

System Design: Weather Data Aggregation (10-minute Updates)

Context

Requirements

Solution

Submit Your Answer to Earn 20XP