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How would you handle massive data ingestion in a cloud environment?

System Design/Architecturehard0.1 min readPremium
Frequency
Low
Asked at 1 company
Category
179
questions in System Design/Architecture
Difficulty Split
15E|6M|158H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Wipro
Interview Pro Tip

Pro-Move: 'Kinesis Firehose to S3; Lambda/Spark for transform. 50M events/day. Auto-scale consumers; alert if lag >1000.'

Key Concepts Tested
partition
Expert AnswerPremium
29 wordsInterview-ready
**Streaming**: Kafka, Kinesis, Event Hubs. **Batch**: S3/GCS multipart, DataSync. **Parallelism**: Scale producers/consumers. **Buffering**: Queues for spikes. **Auto-scale**: Ingestion + processing. Use managed services; monitor throughput; backpressure; partition by date/source.
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Wipro. The answer also includes follow-up discussion points that interviewers commonly explore.

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