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Distributed

Distributed systems fundamentals: consensus, simulation testing, fault injection, reliability engineering, and coordination primitives for large-scale services.

4 posts · ~28 min of reading

Jul 8, 2026

How Ring Attention eliminates the memory wall for long-context transformers by overlapping blockwise attention computation with KV-cache communication in a ring topology, enabling near-linear context scaling across devices.

distributed-systems transformers attention 6 min

Jul 7, 2026

For years, every database built on object storage needed a DynamoDB table or a ZooKeeper cluster on the side just to answer "who is the writer?" In late 2024, S3 quietly shipped If-Match and If-None-Match support on PutObject, turning the object store itself into a compare-and-swap register. Here is why that one HTTP header changes how you architect storage systems, and how projects like SlateDB use it for formally verified writer fencing.

distributed-systems object-storage databases 8 min

Jul 5, 2026

FoundationDB shipped a distributed database with essentially zero customer-reported bugs by running its entire cluster inside a single-threaded simulation driven by one random seed. TigerBeetle and Antithesis have since pushed the idea further. Here is how deterministic simulation testing works, why a seed is worth a thousand log files, and where the technique's real limits are.

distributed-systems testing reliability 7 min

Jul 5, 2026

Prefill and decode have opposite hardware profiles, and serving them on the same GPUs wastes both. A practical tour of DistServe and Mooncake, the two papers behind the biggest architecture shift in LLM inference.

llm-inference kv-cache distributed-systems 7 min