1745 posts · page 5 of 37
Master Kimball dimensional modeling: fact table types, advanced dimension techniques, the bus matrix, grain decisions, and a complete e-commerce example.
Build production-grade data pipelines using Kafka Connect, Debezium CDC, sink connectors, schema evolution, and dead letter queues for robust error handling.
Master event-driven architecture patterns including event sourcing, CQRS, and the saga pattern using Apache Kafka for real-world microservices systems.
Understand Kafka's three delivery guarantees, idempotent producers, transactional writes, and when you actually need exactly-once semantics in production.
Understand why Kafka is removing ZooKeeper, how KRaft consensus works, and master cluster operations including broker management and disaster recovery.
Learn the essential Kafka metrics to monitor, alerting strategies, operational tools like Prometheus and Grafana, and capacity planning for production clusters.
Explore how Netflix, Uber, LinkedIn, and others use Apache Kafka in production for recommendations, pricing, fraud detection, IoT, and log aggregation.
Master advanced dynamic programming patterns — interval DP, tree DP with rerooting, bitmask DP, digit DP, and optimization techniques like Knuth's and divide-and-conquer optimization.
A comprehensive comparison of data structures — arrays vs linked lists, hash maps vs trees vs tries, heaps vs BSTs, stacks vs queues, sets vs Bloom filters, with decision flowcharts and complexity tables.
The 15 most common competitive programming patterns — prefix sums, difference arrays, coordinate compression, meet in the middle, sqrt decomposition, sparse tables, binary lifting, and Mo's algorithm.
How real-world systems use data structures and algorithms — B-trees in databases, skip lists in Redis, inverted indexes in search, Dijkstra in routing, DAGs in Git, consistent hashing, and Bloom filters.
Deep dive into advanced graph algorithms — Tarjan's and Kosaraju's for SCCs, bridges and articulation points, Euler paths, network flow, and 2-SAT with real-world applications.
A complete framework for solving coding interview problems — the 5-step method, pattern recognition, handling stuck moments, communication strategies, common mistakes, and a 100-problem practice roadmap.
Master advanced string algorithms — Z-algorithm, Rabin-Karp rolling hash, suffix arrays, Aho-Corasick multi-pattern matching, Manacher's palindrome algorithm, and string hashing techniques.
Deep dive into advanced tree algorithms — heavy-light decomposition, Euler tour technique, centroid decomposition, LCA with binary lifting, tree DP with rerooting, and virtual trees.
Master API design with REST principles, GraphQL trade-offs, gRPC for microservices, pagination strategies, rate limiting, and authentication patterns. Learn why Stripe's API is the gold standard.
Master database replication patterns — single-leader, multi-leader, and leaderless. Learn about replication lag, conflict resolution, quorum reads, and how Slack handles replication at scale.
Deep dive into ACID properties, isolation levels, and distributed transactions. Understand dirty reads, phantom reads, two-phase commit, the saga pattern, and how Stripe handles payment consistency.
Understand what makes distributed systems hard. Learn consensus algorithms (Paxos, Raft), leader election, distributed locking, vector clocks, gossip protocols, and how CockroachDB achieves distributed SQL.
How Instagram scaled Django to 2B+ users. Covers feed generation, image processing pipelines, Stories architecture, and PostgreSQL sharding strategies.
An honest look at microservices vs monoliths. Learn service communication, API gateways, database-per-service, distributed tracing, and how Amazon's migration shaped the industry.
Understand the networking stack from TCP/IP to HTTP/3. Learn DNS resolution, the TLS handshake, WebSockets vs SSE, and how CDNs reduce latency — all through practical analogies.
How Netflix evolved from DVD rental to a global streaming platform serving 250M+ subscribers. Covers microservices, Open Connect CDN, recommendations, and Chaos Engineering.
Master scalability patterns including horizontal scaling, stateless services, read replicas, CQRS, database partitioning, and async processing. See how Instagram handles 2B+ users.
How Spotify streams 100M+ songs to 600M+ users. Covers audio streaming, Discover Weekly ML, the squad/tribe model, event-driven architecture, and offline mode.
Compare relational and non-relational databases from first principles. Learn ACID properties, NoSQL types, polyglot persistence, and when to pick each — with real migration stories from Uber and Netflix.
How Twitter delivers 500M tweets/day to 300M+ timelines. Covers the fanout problem, hybrid push/pull, real-time search with EarlyBird, and the celebrity tweet challenge.
How Uber matches millions of riders with drivers in real-time. Covers geospatial indexing with H3, surge pricing, ETA prediction, and their migration from Python to Go.
How WhatsApp served 2 billion users with just 50 engineers. Covers Erlang/BEAM concurrency, end-to-end encryption, message delivery, and extreme engineering efficiency.
How YouTube serves 1B+ hours of video per day. Covers the video upload pipeline, adaptive bitrate streaming, recommendation engine, and live streaming architecture.
Understand what system design is, why it matters for engineers, the core building blocks of scalable systems, and how to approach system design interviews.
Understand the architecture of Apache Airflow -- Scheduler, Web Server, Metadata Database, Executors, and Workers -- and learn which executor fits your workload.
Production-ready Airflow patterns covering DAG design, performance optimization, monitoring, testing, deployment strategies, and comparison with alternatives.
Master Airflow connections for external system credentials and variables for runtime configuration, including secrets backends for production deployments.
Learn how to implement conditional workflows in Airflow using BranchPythonOperator, ShortCircuitOperator, trigger rules, and the TaskFlow branch decorator.
Master Airflow DAGs -- learn the anatomy of a DAG file, scheduling with cron and presets, defining task dependencies, fan-out patterns, and task lifecycle states.
Master Apache Airflow operators from BashOperator to building your own custom operators with template fields and provider packages.
Learn how Airflow sensors pause tasks until conditions are met, including poke vs reschedule modes, custom sensors, and deferrable operators.
Understand Airflow XComs for inter-task communication including push/pull patterns, Jinja templates, size limits, and custom backends for production use.
Master the TaskFlow API with @dag and @task decorators, implicit XCom passing, dynamic task mapping, and dataset-aware scheduling in Airflow 2.0+.
Step-by-step guide to installing Apache Airflow using pip with constraints or Docker Compose, creating an admin user, and verifying your setup works correctly.
Learn what Apache Airflow is, why Airbnb created it, how DAGs work, and when to use Airflow for orchestrating data pipelines, ETL workflows, and ML operations.
Understand the difference between batch and stream processing, when to use each pattern, and how Lambda and Kappa architectures combine them.
Understand the differences between data lakes, data warehouses, and the modern lakehouse architecture — when to use each and how they work together.
A comprehensive guide to the modern data engineering tool landscape — ingestion, transformation, orchestration, storage, quality, and governance tools.
Learn Kimball, Inmon, and Data Vault modeling approaches for analytics — star schemas, normalized models, and modern patterns like the Activity Schema.
Learn the six dimensions of data quality, how to implement quality checks with Great Expectations and dbt, and the pillars of data governance.
Understand the difference between ETL and ELT pipeline patterns, when to use each, and how modern cloud warehouses changed the default choice.