Author: Ajit

Menu close menu icon System Design Interview Questions Adobe System Design Interview Questions Top Atlassian System Design Interview Questions Top Amazon System Design Interview Questions Top Microsoft System Design Interview Questions Top Meta (Facebook) System Design Interview Questions Top Netflix System Design Interview Questions Top Uber System Design Interview Questions Top Google System Design Interview Questions Top Apple System Design Interview Questions Top Airbnb System Design Interview Questions Top 10 System Design Interview Questions Mobile App System Design Interview Questions Top 20 Stripe System Design Interview Questions Top Shopify System Design Interview Questions Top 20 System Design Interview Questions Top Advanced System Design Questions Most-Frequented System Design Questions in Big Tech Interviews What Interviewers Look for in System Design Questions Critical System Design Questions to Crack Any Tech Interview Top 20 API Design Questions for System Design Interviews Top 10 Steps to Create a System Design Portfolio for Developers Introduction to High-Level System Design What is System Design? Difference Between HLD and LLD Key Considerations in HLD System Design Fundamentals Functional vs. Non-Functional Requirements Scalability, Availability, and Reliability Latency and Throughput Considerations Load Balancing Strategies Architectural Patterns Monolithic vs. Microservices Architecture Layered Architecture Event-Driven Architecture Serverless Architecture Model-View-Controller (MVC) Pattern CQRS (Command Query Responsibility Segregation) Scaling Strategies Vertical Scaling vs. Horizontal Scaling Sharding and Partitioning Data Replication and Consistency Models Load Balancing Strategies CDN and Edge Computing Database Design in HLD SQL vs. NoSQL Databases CAP Theorem and its Impact on System Design Database Indexing and Query Optimization Database Sharding and Partitioning Replication Strategies API Design and Communication REST vs. GraphQL vs. gRPC Designing Scalable APIs Rate Limiting and Throttling Authentication & Authorization (OAuth, JWT) Caching Strategies Types of Caching Cache Invalidation Strategies Redis vs. Memcached Cache-Aside, Write-Through, and Write-Behind Strategies Message Queues and Event-Driven Systems Kafka vs. RabbitMQ vs. SQS Pub-Sub vs. Point-to-Point Messaging Handling Asynchronous Workloads Eventual Consistency in Distributed Systems Security in System Design Encryption (AES, RSA, TLS) API Security Best Practices Secure Data Storage and Access Control DDoS Protection and Rate Limiting Observability and Monitoring Logging Strategies (ELK Stack, Prometheus, Grafana) API Security Best Practices Secure Data Storage and Access Control DDoS Protection and Rate Limiting Real-World System Design Case Studies Distributed locking (Locking and its Types) Memory leaks and Out of memory issues HLD of YouTube HLD of WhatsApp close menu icon From Upload to Play: Understanding YouTube’s Scalable Architecture Quick Overview of What You’ll LearnYouTube’s global scale: 2.7 billion MAU, 122 million DAU, 1 billion hours watched daily, available in 100 countries/80 languages, 500 hours uploaded per minuteFinancial overview: $29.24 B ad revenue in 2022, with the U.S. video‑streaming market projected to reach $66.4 B by 2030, implying YouTube’s revenue could approach the $60 B rangeCore system components: CDN network, blob storage, transcoding pipeline (DAG), metadata DB (sharding + caching), API servers, load balancerKey workflows: chunked uploads with pre‑signed URLs, parallel DAG‑based transcoding, cache‑driven streaming, adaptive bitrate (HLS/DASH), multi‑region failoverCost & performance optimizations: on‑demand encoding, regional distribution, CDN partnerships, retry logic, auto‑scalingAdvanced patterns: UserID vs. VideoID sharding, Redis hot‑video cache, live‑streaming low‑latency protocols, DRM/encryption, pre‑signed URL securityFollow‑up topics & interview promptsWhat Are YouTube’s Key Usage Metrics in 2024 – 2025?YouTube now serves more than 2.7 billion logged‑in users each month, making it the second‑largest social platform after Facebook.On a daily basis, over 122 million people actively use YouTube, collectively streaming 1 billion hours of video worldwide every day.To support this global audience, YouTube is localized in over 100 countries and supports more than 80 languages. Creators upload more than 500 hours of new video content every minute, adding roughly 30,000 hours of footage each hour.How Profitable Is YouTube’s Ad Business?In 2022, YouTube generated $29.24 billion in advertising revenue, accounting for over 11 percent of Google’s total ad revenues that year.. More recent reports show YouTube ad income rose to $31.51 billion in 2023, an 8 percent increase year‑over‑year. Industry forecasts anticipate the U.S. video‑streaming market will reach US$66.4 billion by 2030 citeturn4search6, suggesting that YouTube’s global revenue, as the leading platform, may scale into the $60 billion range.Beyond Just Watching The Technology Powering YouTubeHow Does YouTube Handle Fast Video Uploads?Pre‑signed URLs grant clients direct, secure write access to blob storage without exposing credentials.Chunked uploads use GOP (Group of Pictures) alignment, enabling resumable transfers and parallelism for faster throughput.Completion queues decouple upload, transcoding, and metadata updates via message queues to ensure a loosely coupled architecture.If you’re preparing for system design interviews on large‑scale pipelines, explore our Master DSA, Web Dev & System Design course for real‑world case studies.What Is YouTube’s Transcoding Pipeline?YouTube’s transcoding service converts raw uploads into multiple streaming formats (HLS, MPEG‑DASH, etc.) for device compatibility and adaptive bitrate delivery:Preprocessor splits videos into GOP‑aligned segments and caches them for reliability.DAG scheduler builds a Directed Acyclic Graph of tasks (encoding, thumbnailing, watermarking).Resource manager allocates worker nodes from task and worker queues based on priority.Task workers run encoding and asset‑generation in parallel.Transcoded storage holds completed streams, which are then pushed to CDN edge caches.For a deep dive into parallel processing and DAG models, check out our DSA course to strengthen your algorithmic foundations.Back‑of‑the‑Envelope Estimation: Crunching YouTube’s ScaleHow Much Storage Do Daily Uploads Require?Assumptions: 5 million DAU, 5 videos per user, 10 % upload rate, 300 MB per videoDaily storage = 5 M × 10 % × 0.3 GB = 150 TB per day → over 1 PB per week just for raw uploadsWhat Would CDN Costs Look Like?Total streaming data = 5 M users × 5 videos/user × 0.3 GB = 7.5 M GB/dayCloudFront pricing ≈ $0.02/GB → $150,000 per day, ~$4.5 million per month.Crafting the Blueprint – High‑Level System DesignWhy Leverage Cloud Services Instead of Building In‑House?Time & cost efficiency: Proven blob storage and CDNs scale instantly.Reliability: Third‑party providers like AWS and Akamai guarantee SLAs.Industry precedent: Netflix uses AWS; Facebook uses Akamai. What Are the Core Components?Client (Web, iOS/Android, Smart TV)Load balancer → distributes requests toAPI servers (stateless, handle metadata, recommendations, auth)Metadata DB & cache (sharded MySQL + Redis)Original blob storage (raw uploads)Transcoding clusterTranscoded storageCDN edge (streaming delivery)Message queues (upload/transcode completion, notification)Video Uploading FlowStep‑by‑Step BreakdownClient fetches pre‑signed URL from API server.Client uploads chunks directly to blob storage.API server updates metadata DB/cache in parallel.Transcoding servers pick up raw files, process via DAG, store outputs.Completion handler updates metadata and pushes streams to CDN.API server notifies client: “Video ready for streaming.”How Does Video Streaming Work?Which Streaming Protocols Are Supported?MPEG‑DASH – adaptive bitrate streaming on most desktops.Apple HLS – required for iOS and Safari. Microsoft Smooth Streaming – legacy Windows devices.Adobe HDS – older Adobe‑based clients.Edge Delivery via CDNEdge servers cache transcoded segments close to users, minimizing latency and enabling instant playback.Database Schema for Video Metadata & User DataVideos Table (MySQL)ColumnTypeDescriptionVideoIDBIGINT PKUnique video identifierTitleVARCHAR(255)Video titleDescriptionTEXTDetailed descriptionSizeBIGINTFile size in bytesThumbnailVARCHAR(500)URL of thumbnailUploaderIDBIGINT FKReference to Users.UserIDLikesCountBIGINTTotal likesDislikesCountBIGINTTotal dislikesViewsCountBIGINTView countUploadTimeDATETIMEUpload timestampIndexes(VideoID, UploaderID) for fetching user videosFull‑text on (Title, Description) for searchComments TableColumnTypeDescriptionCommentIDBIGINT PKUnique comment IDVideoIDBIGINT FKReferences Videos.VideoIDUserIDBIGINT FKReferences Users.UserIDCommentTextTEXTComment contentCreatedAtDATETIMETimestampIndexes(VideoID, CreatedAt DESC) for recent comments(UserID, VideoID) for engagement analysisUsers TableColumnTypeDescriptionUserIDBIGINT PKUnique user identifierNameVARCHAR(255)Full nameEmailVARCHAR(320)Unique email for authenticationPasswordHashVARCHAR(500)Secure hashed passwordAddressVARCHAR(500)Optional locationAgeINTOptional ageRegistrationDateDATETIMEAccount creation timestampIndexes(Email) for login(UserID, RegistrationDate) for analyticsDesign Deep DiveVideo Transcoding Why transcoding?Device compatibility (MP4, WebM, HLS, DASH)Adaptive quality (144p→4K)Storage efficiency (multi‑bitrate) Common codecs & containers:Container: MP4, MKV, HLS TSVideo codecs: H.264, VP9, AV1Audio codecs: AAC, OpusParallel Processing with DAGTasks—splitting, encoding, thumbnailing—are represented as nodes in a Directed Acyclic Graph, executed concurrently where dependencies allow.Speed & Safety OptimizationsChunked, Parallel UploadsGOP splitting on the client accelerates uploads and enables resumability.Global upload centers route to nearest edge point, reducing latency.Secure Pre‑signed URLsClients upload directly to storage using URLs that expire, ensuring only authorized writes.Optimizing Video Streaming SystemsSecurity & DRMDRM: FairPlay, Widevine, PlayReady.AES Encryption for protected streams.Watermarks to identify content ownership.Cost‑Saving TechniquesOn‑demand encoding for infrequent videos.Regional CDN caching based on view patterns. Custom CDN partnerships to lower bandwidth fees.Error Handling & ReliabilityRetry logic for uploads and transcodes.Health‑monitoring load balancers that remove failed nodes.DB master‑slave failover and replicated caches (e.g., Redis).Metadata Sharding StrategiesShard by UserIDApproach: Hash UserID → assign all user videos to same shard.Pros: Easy user‑centric reads.Cons: Hotspots for popular creators.Mitigation: Consistent hashing, dynamic repartitioning.Shard by VideoIDApproach: Hash VideoID → evenly distribute across shards.Pros: Balanced writes.Cons: Aggregation overhead for user feeds.Enhancement: Cache hot videos in Redis to minimize cross‑shard reads.Wrapping Up: Designing Your Own Scalable Video ServiceBy combining:Pre‑signed URLs and chunked uploads for fast, secure ingestionDAG‑based transcoding for parallel, multi‑format outputGlobal CDN for low‑latency deliverySharded metadata + caching for high‑throughput reads/writesCost‑saving measures (on‑demand encoding, regional CDNs)you can architect a video‑platform that rivals YouTube in scale, reliability, and efficiency. How do I master the core data structures and algorithms for technical interviews? Start by building a strong foundation in arrays, linked lists, trees, graphs, sorting and searching techniques. Our DSA course offers hands‑on coding challenges, step‑by‑step explanations, and mock interview questions to help you ace your next interview. What’s the fastest way to become a proficient full‑stack web developer? Focus on both front‑end and back‑end technologies—HTML, CSS, JavaScript frameworks, RESTful APIs, and databases. Enroll in our Web Development course to learn modern stacks through real projects and mentorship from industry experts. Should I combine system design principles with DSA practice or tackle them separately? Integrating design patterns and algorithmic thinking accelerates your learning curve and prepares you for senior roles. Our Design + DSA Combined course merges system design workshops with algorithm deep‑dives for a cohesive experience. Which program covers advanced system design alongside web development and DSA? For a comprehensive curriculum that spans data structures, web frameworks, and large‑scale system architecture, check out our Master DSA, Web Dev & System Design course. It’s tailored for those aiming at high‑impact engineering roles. How can I apply data science techniques to solve real‑world problems? Learn how to preprocess data, build predictive models, and visualize insights using Python and machine learning libraries. Our Data Science course guides you through end‑to‑end projects and case studies to make your portfolio stand out. Start by building a strong foundation in arrays, linked lists, trees, graphs, sorting and searching techniques. Our DSA course offers hands‑on coding challenges, step‑by‑step explanations, and mock interview questions to help you ace your next interview.Focus on both front‑end and back‑end technologies—HTML, CSS, JavaScript frameworks, RESTful APIs, and databases. Enroll in our Web Development course to learn modern stacks through real projects and mentorship from industry experts.Integrating design patterns and algorithmic thinking accelerates your learning curve and prepares you for senior roles. Our Design + DSA Combined course merges system design workshops with algorithm deep‑dives for a cohesive experience.For a comprehensive curriculum that spans data structures, web frameworks, and large‑scale system architecture, check out our Master DSA, Web Dev & System Design course. It’s tailored for those aiming at high‑impact engineering roles.Learn how to preprocess data, build predictive models, and visualize insights using Python and machine learning libraries. Our Data Science course guides you through end‑to‑end projects and case studies to make your portfolio stand out. This insightful blog post is authored by Ajit Pedha, who brings his expertise and deep understanding of the topic to provide valuable perspectives. Ajit Pedha Full stack web developer | .Net Core, Azure, Angular, Devops, SQL, AI enthusiast Got Confusion ? Accelerate your Path to a Product based Career Boost your career or get hired at top product-based companies by joining our expertly crafted courses. Gain practical skills and real-world knowledge to help you succeed. Explore our flagship courses Reach Out Now If you have any queries, please fill out this form. We will surely reach out to you. Contact Email Reach us at the following email address. arun@getsdeready.com Phone Number You can reach us by phone as well. +91-97737 28034 Our Location Rohini, Sector-3, Delhi-110085

Author: Ajit

From Upload to Play: Understanding YouTube’s Scalable Architecture

Longest Consecutive Subsequence: O(n) Algorithm Optimization

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