distributed-systems Interview Questions
45 interview questions in our bank cover distributed-systems, most of them System Design for ML. They average 3.9/5 difficulty — hard — and each one was reported by a candidate after a real interview. Companies known to ask about distributed-systems: Snowflake, Netflix, Microsoft, Apple, Roblox, and 15 more.
Practice these on the problems board →Companies that ask about distributed-systems
Question mix
- System Design for ML42
- Coding & Leetcode-style Questions3
Difficulty
- 3/5 — medium11
- 4/5 — hard27
- 5/5 — very hard7
Questions tagged distributed-systems
Design a Distributed Training Platform for Foundation Models
4/5Architect a massive, highly available distributed infrastructure designed to train giant foundation models across thousands of accelerators simultaneously, as featured in an OpenAI system design interview. This problem focuses on orchestrating synchronous workloads, handling rapid fault recovery, optimizing data pipelines, and managing model parallelism strategies like tensor and pipeline sharding. You will also tackle scheduling fairness and network bottlenecks. Unlock the full design breakdown and expert architectural solution with a subscription.
System Design for MLOpenAIDistributed Matrix Multiplication — DP and FSDP
4/5This advanced infrastructure coding assessment from xAI explores the principles of distributed model training by simulating device communication for matrix operations. Candidates must build both data-parallel and fully sharded strategies to handle heavy computational workloads across multiple nodes effectively. To unlock the full problem description, architectural insights, and the reference code, a subscription is required.
Coding & Leetcode-style QuestionsxAIDesign a Job Scheduler / ETL Pipeline
4/5Reported as a Microsoft system design question, this exercise focuses on engineering a dependable orchestration platform capable of running complex data workflows on strict chronological triggers. Candidates must devise mechanisms to handle job dependencies, automatic failure recovery, precise execution timing, and administrative oversight for thousands of concurrent tasks. The evaluation targets distributed locking, fault resilience, state management, and scalability under heavy spikes. Unlocking the complete system architecture and expert solution requires a paid subscription.
System Design for MLMicrosoftAds Frequency Cap and Limiter System
5/5Explore how to architect a real-time promotional delivery controller reminiscent of technical assessments at Netflix. This scenario requires balancing strict impression limits, budgeting constraints, and high-throughput evaluation while maintaining sub-millisecond response times. Candidates must navigate intricate data synchronization patterns, atomic caching mechanisms, and asynchronous reconciliation pipelines. Discover the complete architectural blueprint, underlying trade-offs, and expert-crafted reference solutions by unlocking full access to our comprehensive platform.
System Design for MLNetflixAds Audience Targeting / Custom Audience System
5/5This architectural challenge, frequently asked at Netflix, focuses on building a massive custom audience targeting platform capable of ingesting colossal advertiser datasets, matching hashed identifiers against a vast user base, and evaluating complex boolean segmentation rules in real time. Candidates are evaluated on their ability to design ultra-low latency lookups and scalable distributed pipelines. Access the complete system blueprint and expert solution by purchasing a subscription.
System Design for MLNetflixDistributed File System Metadata Layer with Strong Consistency
4/5Dive into a complex distributed systems architecture challenge inspired by technical interviews at Databricks. You will design the directory and file management metadata tier for a massive storage network, emphasizing strict consistency guarantees and fault tolerance over weak replication models. The exercise assesses your mastery of consensus protocols, hierarchical tree organization, and high-availability design principles. Unlock the complete system architecture blueprint and expert analysis with a subscription.
System Design for MLDatabricksCompute Resource Scheduling for ML Jobs
4/5Designing distributed workload orchestrators is a challenging architecture task frequently explored in machine learning infrastructure interviews at Netflix. This system design problem tests your capability to build a resource scheduler that efficiently allocates computational hardware across multiple clusters while maintaining high utilization and managing job lifecycles. You must address complex operational demands, including priority queuing, task preemption, resource quotas, and isolation against noisy neighbors. Unlock the complete problem statement and verified model solution with a subscription.
System Design for MLNetflixDesign and Implement a Rate Limiter
4/5Tackling rate limiter design challenges is a staple of Microsoft technical screenings, testing your ability to throttle request rates accurately while handling traffic spikes and high concurrency. This problem focuses on building robust traffic control mechanisms with precise sliding windows and distributed enforcement capabilities across scalable gateway architectures. You will explore various concurrency strategies and architectural trade-offs essential for modern backend systems. Unlock the complete system design blueprint, scaling strategies, and reference implementation by securing a subscription.
System Design for MLMicrosoftReal-time Market Data Distribution System
5/5This Bloomberg systems engineering interview question explores the architecture of a high-throughput distribution pipeline for live financial quotes. Candidates are tasked with designing a network topology where data collectors broadcast messages via user datagram protocols to numerous worker nodes that must overcome network dropouts, duplication, and sequencing anomalies. The exercise evaluates distributed systems knowledge, fault tolerance strategies, and reliable state persistence under heavy load. The comprehensive architectural breakdown and model solution are available with a paid subscription.
System Design for MLBloombergDesign a Stripe-like Payment Platform
4/5Tackle an open-ended system design challenge centered around building a robust financial transaction platform, akin to interviews conducted at ByteDance. You will explore how to architect payment intents, guarantee transactional integrity, and enforce strict idempotency to prevent duplicate charges during network failures or retries. The evaluation delves into asynchronous fund settlement pipelines and webhook notification mechanisms for merchants. Discover the comprehensive system architecture breakdown and expert design strategies by obtaining a subscription.
System Design for MLByteDanceDesign a Distributed Web Crawler
4/5This Microsoft system design interview question focuses on architecting a massive-scale web indexing pipeline capable of harvesting billions of network resources efficiently. You need to design resilient components that handle URLfrontier management, content deduplication, politeness throttling, and fault tolerance at scale. The exercise evaluates your capability to balance throughput requirements with strict domain-level access constraints and distributed failure recovery. Access to the comprehensive design document, architectural diagrams, and expert recommendations requires a paid subscription.
System Design for MLMicrosoftDesign a Network Throttling / Rate-Limiting System
4/5Inspired by real-world distributed systems challenges at Databricks, this system architecture task requires designing a robust traffic throttling and rate-limiting framework for both ingress and egress channels. You will explore multi-tenant traffic management, protective degradation strategies, and mechanisms to prevent cascading backend failures under heavy load. Read the exhaustive architectural guide and expert commentary by subscribing today.
System Design for MLDatabricksDesign a Distributed Task Scheduler
4/5This advanced system design challenge, frequently discussed in Apple engineering interviews, centers on building a robust distributed task scheduler capable of handling massive workloads reliably. Candidates must architect mechanisms for persistent storage, fault-tolerant worker coordination, duplicate prevention, and priority-based queue management. The discussion emphasizes scalability, load balancing, and handling node failures gracefully in a distributed environment. Gain access to the comprehensive architectural blueprint, trade-off analysis, and expert recommendations with a subscription.
System Design for MLAppleDesign an ACL Authorization Service
4/5Architecting low-latency authorization infrastructure is critical for secure, large-scale distributed systems. This reported Snowflake system design question asks you to construct a service capable of processing access control checks involving direct permissions as well as group and role hierarchies. The exercise focuses on meeting strict single-digit millisecond latency targets and handling massive request volumes without compromising audit logging. Discover the complete architectural requirements and comprehensive solution guide with a subscription.
System Design for MLSnowflakeDesign an S3-Style Blob Store with Deduplication
4/5This system architecture challenge focuses on designing a cloud object storage service engineered specifically to minimize storage redundancy through content-addressable deduplication. As a notable Snowflake interview question, it explores distributed storage principles, cryptographic hashing for identification, and maintaining transparent file paths. Unlocking the comprehensive design breakdown and expert architectural solutions requires an active subscription.
System Design for MLSnowflakeKubernetes Controller for Pod Balance
3/5Explore distributed orchestration architecture by designing a reconciliation control loop inspired by cloud-native infrastructure assessments at IBM. You will implement reactive logic that observes current cluster states, evaluates metrics against targets, and executes balancing actions to maintain optimal workload distribution. Additionally, you will discuss failure recovery strategies when core cluster management APIs become unavailable. Access the complete architectural requirements, system design principles, and expert solutions through a paid subscription.
System Design for MLIBMReliable Account Balance Service and Cross-Region Event Platform
5/5This advanced system design challenge, frequently encountered during senior evaluations at Capital One, requires architecting a highly resilient financial tracking service alongside a distributed event streaming platform. Candidates must address strict consistency guarantees, disaster recovery across geographic regions, and ledger reconciliation mechanics under heavy throughput. The exercise evaluates your capability to maintain zero data loss and minimal latency during infrastructure failures. To explore the full architectural blueprints and reference answers, a subscription is required.
System Design for MLCapital OneAsync Job Scheduler
3/5This distributed systems design exercise, reported at Figma, asks you to build a robust background task management platform capable of handling immediate executions as well as delayed triggers. The core challenge centers on fault tolerance, guaranteeing exactly-once task completion, and managing worker recovery gracefully if a node fails mid-operation. You must address concurrency, idempotency, and reliable queue administration at scale. Access the complete system requirements and expert design solution with a paid subscription.
System Design for MLFigmaDesign a Distributed Rate Limiter with Redis Lua
4/5Design a robust and scalable throttling service capable of protecting distributed backend infrastructure across a massive server fleet, a popular system design topic reported in Apple interviews. This challenge explores how to enforce strict usage thresholds per user or endpoint with minimal latency overhead by leveraging shared state mechanisms and atomic script execution. You will evaluate architectural patterns ranging from token buckets to sliding window counters while addressing high concurrency and sharding hurdles. Read the complete architectural guide and expert solution by securing a paid subscription.
System Design for MLAppleDesign Object Storage / File Sync (Dropbox / S3)
4/5Mastering large-scale distributed cloud storage architectures is essential for modern infrastructure roles, often featured in senior system design loops at top-tier organizations like Apple. This challenge requires engineering a robust object storage and file synchronization platform capable of handling massive daily ingestion volumes while guaranteeing high durability targets and low-latency update propagation. Candidates must address intricate architectural concerns including block-level deduplication, optimistic concurrency control for conflict resolution, efficient metadata management, and horizontal scaling strategies across multiple tiers. Access to the comprehensive problem breakdown and expert reference architecture requires an active subscription.
System Design for MLAppleDesign a Quota System
4/5Encountered during architectural interviews at Snowflake, this system design challenge focuses on building a resilient resource tracking platform that prevents quota overruns in highly concurrent environments. Candidates must architect APIs and consistency models capable of handling simultaneous balance updates without allowing overdrafts or sacrificing performance. To examine the complete architectural blueprint, scaling strategies, and expert design trade-offs, a subscription is required.
System Design for MLSnowflakeDesign a Distributed Job Scheduler with Cron, Pause, Resume
4/5Building reliable asynchronous systems is the core of this Snowflake interview question, which challenges you to design a distributed job scheduler with support for recurring cron execution, pauses, and graceful resumes. The scenario tests your ability to guarantee fault tolerance, state persistence across restarts, and exactly-once execution semantics under node failures. Designing such coordination frameworks highlights your expertise in scalable backend engineering and distributed synchronization. Unlocking the comprehensive system architecture and model implementation demands an active subscription.
System Design for MLSnowflakeJira AI Auto-Fix Pipeline
3/5Presented as a system design challenge at Snowflake, this problem centers on architecting an asynchronous AI pipeline that handles long-running tasks reliably. You are asked to design an infrastructure capable of ingesting event tickets, buffering requests through message queues, tracking states, and preventing duplicate processing during retries. This scenario tests your understanding of distributed systems, database schema design, fault tolerance, and scalability patterns. Access the full design breakdown and expert architectural solutions with a subscription.
System Design for MLSnowflakeDistributed Job Scheduler / Calendar Service
4/5This distributed systems design challenge, frequently reported from interviews at LinkedIn, focuses on building a highly scalable job scheduler and calendar service capable of managing millions of concurrent tasks with strict latency constraints. Candidates must design reliable worker pools, handling mechanisms for timezones, recurrence rules, and real-time dashboard updates. Access the comprehensive system architecture, trade-off analysis, and expert solutions with a paid subscription.
System Design for MLLinkedInJob Scheduler System Design
3/5As a classic senior-level system design prompt from Robinhood, this question requires architects to design a fault-tolerant distributed task scheduling platform. You must ensure rigorous adherence to service level agreements, visibility into execution logs, and strict at-most-once job processing semantics. This challenge tests your knowledge of distributed coordination, idempotency patterns, and robust failure recovery mechanisms. Subscribe to review the comprehensive architectural blueprint, component interactions, and expert evaluation criteria.
System Design for MLRobinhoodRate Limiter Algorithm Design
3/5This NVIDIA system design round focuses on architecting robust rate-limiting mechanisms to manage traffic flow in distributed environments. Rather than drawing full infrastructure diagrams, the discussion centers on comparing algorithms like token buckets, leaky buckets, and sliding windows while addressing state storage and concurrency trade-offs. It assesses your infrastructure intuition and scalability trade-offs. The complete architectural guide and expert discussion notes require a subscription.
System Design for MLNVIDIADistributed Key-Value Store Design
3/5Featured in Airbnb system design discussions, this challenge focuses on architecting a horizontally expandable distributed data store with support for time-to-live expiration and rapid retrieval speeds. You will need to address core architectural concerns including consistency, partitioning, and replication strategies. Review the complete system requirements and architectural blueprint by securing a subscription.
System Design for MLAirbnbDocument Store with Boolean Predicate Query
4/5As featured in Snowflake technical rounds, this systems-oriented coding challenge asks you to build a lightweight text-storage server capable of processing dynamic insertion commands and evaluating complex boolean logic queries against stored records. You must progress from basic keyword containment checks to parsing intricate logical expressions involving conjunctions and disjunctions over file collections. Efficiently retrieving matching documents requires moving from brute-force scanning to optimized inverted index implementations. The complete problem description and model solution require a subscription.
Coding & Leetcode-style QuestionsSnowflakeSystem Design — Event Ingestion + Top-K Aggregation
3/5Scaling a single-server architecture to handle massive request volumes while simultaneously tracking frequent occurrences is a common system design challenge frequently discussed in Oracle interviews. This scenario requires you to transition a basic event-reporting endpoint into a distributed, high-throughput pipeline capable of computing top-K aggregations efficiently in real-time. The evaluation focuses on your ability to address bottlenecks, design data streaming pipelines, and choose appropriate distributed data structures. Gain complete access to the comprehensive problem guide and expert architectural solutions by subscribing.
System Design for MLOracleDesign an Online Auction System with Concurrent Bidding
4/5Design a high-throughput, real-time bidding architecture in this classic Meta system design interview question modeled after major online auction platforms. You will address complex distributed systems challenges including concurrent bid ingestion, low-latency price broadcast mechanisms, anti-snipe deadline extensions, and definitive auction close-out semantics. The discussion highlights your capability to defend concurrency control strategies, estimate capacity requirements, and maintain consistency under heavy load. Read the complete architectural deep-dive and expert design solution by subscribing to the platform.
System Design for MLMetaCore Dump Collection System Design
4/5This architecture interview question, frequently reported at Amazon, challenges candidates to design a robust pipeline for gathering, storing, and analyzing crash diagnostics from distributed infrastructure. Participants must address massive scale, durable binary storage, metadata extraction for efficient querying, and strict security policies. The complete architectural blueprint and expert review require a subscription.
System Design for MLAmazonFile Backup System with Durable Manifest
5/5This advanced Netflix system design problem requires architecting a resilient file synchronization and backup pipeline capable of handling incremental updates and unexpected failures. You must design a solution that mirrors directory hierarchies, preserves file metadata, ensures data integrity, and resumes safely from a durable manifest after system crashes. The challenge evaluates your expertise in distributed storage reliability, atomicity guarantees, and fault-tolerant workflow design. Unlock the comprehensive system architecture guide and expert reference design by subscribing.
System Design for MLNetflixDesign an Audit Logs Service
3/5In this system design challenge reported at Snowflake, you are asked to architect a reliable audit logging service capable of recording user activity as an immutable transaction log while ensuring rapid, account-scoped retrieval. This scenario tests your expertise in database storage selection, indexing strategies for multi-tenant isolation, scaling for high-throughput writes, and enforcing strict read security. Review the full architecture blueprint and comprehensive system design guide by securing a subscription.
System Design for MLSnowflakeGlobal Config Deployment System
5/5This advanced Netflix system design question focuses on engineering a robust control plane capable of deploying versioned system configurations safely. You will learn how to orchestrate phased rollouts across various regions and cohorts, implement automated health checks, and execute instantaneous rollbacks when anomalies occur. This scenario evaluates distributed systems architecture and reliability engineering principles. Review the comprehensive architectural breakdown and complete solution by acquiring a subscription.
System Design for MLNetflixHPC Host Control Plane and Job Coordination
3/5Prepare for a challenging systems design interview question featured at NVIDIA, where you are tasked with architecting a robust infrastructure control plane to oversee numerous compute hosts and manage task distribution efficiently. This scenario evaluates your ability to handle heavy concurrent traffic, design appropriate database schemas, and maintain reliable real-time node state visibility across a large-scale cluster of approximately one thousand machines. Candidates must demonstrate deep knowledge of distributed communication patterns and performance optimization. The full problem and model solution require a subscription.
System Design for MLNVIDIADesign a Distributed Metrics System
4/5Tackle a distributed telemetry and observability challenge inspired by infrastructure interviews at Snowflake. This scenario assesses your competence in building high-throughput ingestion pipelines that can store massive volumes of time-series records efficiently while supporting low-latency analytical queries and alerting windows. You must consider storage formats, downsampling strategies, and horizontal scalability for heavy read-write workloads. The full problem and model solution require a subscription.
System Design for MLSnowflakeDesign a Delayed Virtual-Currency Payment Scheduler
4/5This architectural challenge, frequently featured in Roblox technical interviews, explores the creation of a delayed transfer mechanism for digital currencies. Candidates must design an infrastructure capable of handling high-volume scheduling while guaranteeing reliable, single-occurrence processing amidst potential system failures. You will examine strategies for maintaining precision when massive transaction queues trigger simultaneously. Access to the comprehensive guide and expert architectural blueprints requires an active subscription.
System Design for MLRobloxDesign a Web URL Crawler at Scale
4/5This Snowflake system design question challenges candidates to architect a web crawler capable of discovering domain-specific links starting from a seed URL. The problem progressively scales up to handle millions of pages concurrently while gracefully managing network errors and parsing failures. It tests your knowledge of distributed graph traversal, concurrency control, and robust fault tolerance. Get access to the full problem architecture and expert model solution with a subscription.
System Design for MLSnowflakeDistributed Tree Node Count
4/5Reported during Snowflake system design rounds, this problem asks you to build a resilient distributed algorithm for an N-ary tree where servers communicate asynchronously amidst potential network faults like message loss and duplication. You must engineer local node behaviors that allow the entire hierarchy to aggregate a global count safely while only the root outputs the final tally. This scenario evaluates your grasp of decentralized message-passing protocols, state synchronization, and fault-tolerant architecture. Unlock the complete technical breakdown, architecture patterns, and reference solution with a subscription.
System Design for MLSnowflakeThread-Safe Key Call Counter
3/5Presented during Citadel phone screens, this multi-stage problem requires designing a high-performance invocation counter that accurately tracks key frequencies in a concurrent environment. Candidates progress from implementing a basic increment utility to addressing thread safety, synchronization trade-offs, and scaling the architecture across multiple applications on a single host. The exercise evaluates concurrency primitives, system design principles, and inter-process communication concepts. Unlock the complete problem prompt and expert solution framework with a subscription.
Coding & Leetcode-style QuestionsCitadelDesign a Distributed Web Crawler
4/5Design a massive distributed web scraping architecture capable of processing billions of pages daily while respecting domain rate limits and handling dynamic JavaScript rendering, as commonly featured in Meta machine learning system design interviews. This challenge evaluates your capability to build robust URL frontiers, implement efficient content deduplication, and manage massive storage throughput under strict fault-tolerance requirements. Elevate your infrastructure design expertise for large-scale distributed environments. Access to the complete system architecture walkthrough and expert solutions requires a subscription.
System Design for MLMetaDesign a High-Throughput Distributed Cache
4/5During a Salesforce system design interview, candidates are challenged to architect an ultra-fast, memory-based caching tier capable of absorbing massive concurrent read volumes in front of a primary database. This problem evaluates advanced architectural concepts including memory eviction strategies, data consistency, sharding techniques, and hot key mitigation under heavy loads. Reviewing the detailed system architecture and expert commentary requires an active subscription.
System Design for MLSalesforceL6 Staff System Design Loop (Google)
5/5Prepare for senior technical evaluations with this comprehensive breakdown of a Google L6 Staff system design onsite loop. Focusing on both infrastructure and product scenarios, this guide examines complex architectural challenges ranging from global real-time notifications to scalable distributed rate limiters. You will learn how to structure high-level responses, address trade-offs effectively, and understand the specific evaluation criteria that separate L5 candidates from Staff engineers. Access the full architectural breakdown, detailed evaluations, and expert strategies by subscribing today.
System Design for MLGoogleDesign a ROS-like Pub/Sub System
4/5Engage with a distributed systems architecture challenge frequently discussed in infrastructure interviews at Roblox, focusing on publish-subscribe communication frameworks. Candidates must architect a message-passing pipeline that addresses service discovery, network transport layers, and delivery guarantees like at-least-once or exactly-once semantics. The discussion also requires handling backpressure mechanisms and system scalability under heavy messaging loads. Access to the complete architectural breakdown and expert reference designs requires a paid subscription.
System Design for MLRobloxDesign a Release Deployment Workflow with Staged Rollout
3/5Examine a sophisticated infrastructure design scenario featured in technical assessments at Roblox, focusing on the safe delivery of software updates across distributed environments. This challenge examines your knowledge of progressive rollout strategies, automated health monitoring, rapid rollback mechanisms, and cross-region synchronization. You will learn how to architect resilient deployment pipelines that minimize downtime and mitigate production risks during critical service releases. Master industry-standard reliability patterns and fault-tolerant system design principles for modern cloud applications. Unlock the comprehensive architecture guide and expert solution by securing a subscription.
System Design for MLRoblox
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distributed-systems interview FAQ
- How many distributed-systems interview questions are there?
- 45 reported questions, mostly System Design for ML.
- Which companies ask distributed-systems questions?
- Snowflake (10), Netflix (5), Microsoft (3), Apple (3), Roblox (3), Databricks (2), NVIDIA (2), Meta (2).
- How hard are distributed-systems questions?
- They average 3.9 out of 5: 11 at 3/5, 27 at 4/5, 7 at 5/5.