Google Distributed Systems Interview Questions 2026
Published July 22, 2026 · Updated July 22, 2026
6 real Distributed Systems interview questions asked at Google. Upvoted by engineers who cleared the loop. Covers System Design rounds.
6 questions
287 engineers asked
440 upvotes
Company: Google
Technology: Distributed Systems
All Distributed Systems Questions Asked at Google
Google
Hard
System Design round
Distributed SystemsRedis
Design Google Search autocomplete. As a user types "wea", suggest "weather", "weather today", "weather London".
Cover: trie vs inverted index, personalisation, freshness, latency budget (<100ms), and how you handle offensive query suggestions.
↑ 79 upvotes · 55 engineers asked this · SDE2
Google
Hard
System Design round
Distributed SystemsKafkaGCP
Design Google Maps ETA calculation.
How do you compute the fastest route for 1B+ users in real time? Cover: graph representation of road network, Dijkstra vs A* vs Contraction Hierarchies, live traffic data ingestion, and how you handle road closures.
↑ 72 upvotes · 48 engineers asked this · SDE2
Google
Hard
System Design round
Distributed SystemsGCP
Design Bigtable or a wide-column store from scratch. Explain SSTable, memtable, compaction strategies (size-tiered vs levelled), bloom filters for read optimisation, and how you handle tombstones for deletes.
↑ 53 upvotes · 31 engineers asked this · Staff
Google
Hard
System Design round
5–8 YearsSystem DesignDistributed Systems
Design a URL shortening service (like bit.ly) that handles 1 billion shortened URLs and 100K redirects per second.
↑ 134 upvotes · 107 engineers asked this · Senior SDE
Google
Hard
System Design round
4-7 yearsSystem DesignDistributed Systems
Design an autocomplete/typeahead system for a search engine handling 100K queries per second. Discuss the trie-based approach, how you would rank suggestions, and how you would keep the trie updated with trending queries without hurting read latency.
↑ 61 upvotes · 24 engineers asked this · Senior SDE
Google
Hard
System Design round
4-8 yearsSystem DesignDistributed Systems
Design a URL shortener that must handle 100M new URLs per day and 10x that in reads. Walk through your ID generation strategy and why a simple auto-increment counter breaks at this scale.
↑ 41 upvotes · 22 engineers asked this · Senior SDE
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Frequently asked questions
Design Google Search autocomplete. As a user types "wea", suggest "weather", "weather today", "weather London".
Design Google Search autocomplete. As a user types "wea", suggest "weather", "weather today", "weather London".
Cover: trie vs inverted index, personalisation, freshness, latency budget (<100ms), and how you handle offensive query suggestions.
Design Google Maps ETA calculation.
Design Google Maps ETA calculation.
How do you compute the fastest route for 1B+ users in real time? Cover: graph representation of road network, Dijkstra vs A* vs Contraction Hierarchies, live traffic data ingestion, and how you handle road closures.
Design Bigtable or a wide-column store from scratch. Explain SSTable, memtable, compaction strategies (size-tiered vs levelled), bloom filters for read optimisation, and how you handle tombstones for deletes.
Design Bigtable or a wide-column store from scratch. Explain SSTable, memtable, compaction strategies (size-tiered vs levelled), bloom filters for read optimisation, and how you handle tombstones for deletes.
Design a URL shortening service (like bit.ly) that handles 1 billion shortened URLs and 100K redirects per second.
Design a URL shortening service (like bit.ly) that handles 1 billion shortened URLs and 100K redirects per second.
Design an autocomplete/typeahead system for a search engine handling 100K queries per second. Discuss the trie-based approach, how you would rank suggestions, and how you would keep the trie updated with trending queries without hurting read latency.
Design an autocomplete/typeahead system for a search engine handling 100K queries per second. Discuss the trie-based approach, how you would rank suggestions, and how you would keep the trie updated with trending queries without hurting read latency.
Design a URL shortener that must handle 100M new URLs per day and 10x that in reads. Walk through your ID generation strategy and why a simple auto-increment counter breaks at this scale.
Design a URL shortener that must handle 100M new URLs per day and 10x that in reads. Walk through your ID generation strategy and why a simple auto-increment counter breaks at this scale.