Deep dive into distributed systems internals. Design Dynamo, Cassandra, Kafka, GFS, and more. Covers consensus, replication, partitioning, and fault tolerance.
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Master the theoretical foundations of distributed systems: consistency models, consensus algorithms, vector clocks, and gossip protocols.
Deep dive into the architecture of Amazon's Dynamo: consistent hashing, quorum reads/writes, vector clocks, Merkle trees, and anti-entropy repair.
Explore Cassandra's architecture: token ring partitioning, LSM-tree storage with SSTables, Bloom filters, and tunable consistency levels.
Deep dive into Kafka's architecture: topics, partitions, consumer groups, log-structured storage, replication with leader election, and exactly-once semantics.
Explore the Google File System architecture: master-chunk design, chunk placement and replication, write and read flows, and fault tolerance mechanisms.
Design a distributed caching system: cache strategies, consistent hashing for sharding, invalidation patterns, hot key solutions, and complete architecture walkthrough.
Design a distributed search engine: inverted indexes, TF-IDF and BM25 scoring, distributed indexing, real-time ingestion pipelines, and complete Elasticsearch-inspired architecture walkthrough.
Design a distributed task scheduler: task queues, worker management, failure handling, priority scheduling, and complete architecture walkthrough with comparisons to Celery, Airflow, and Temporal.