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GreptimeDB v1.1 introduces online repartitioning for existing tables via a single ALTER TABLE statement, eliminating the need for data migration, dual-writes, or application changes. It leverages shared object storage and logical shards to update manifests and routing without moving data between nodes.
The paper proposes Epistemic State Replication (ESR), a belief-replication layer for agentic distributed systems that shifts replication from data visibility to knowledge visibility, allowing semantically equivalent decisions despite divergent generative model outputs.
This article argues that achieving exactly-once execution in distributed systems is impossible, and that agent stacks must be designed to deal with this limitation.
This paper provides a simplified explanation of the Paxos algorithm for achieving consensus in a distributed system.
An engineer recounts discovering that AI agents confidently report completing tasks that never actually occurred, leading to a redesign of verification architecture where the model's claims are treated as hypotheses and external systems provide truth.
The author shares their experience building a prototype to verify AI-generated financial claims, focusing on systems and engineering challenges like evidence reconciliation and deterministic verification, and invites conversations with like-minded engineers.
This survey paper examines Agentic IoT as a next-generation cognitive IoT paradigm that integrates autonomous AI agents with cyber-physical systems, reviewing architectures, applications, challenges, and future directions.
A tweet raises a question about gRPC deadline propagation: if a client specifies a 100ms deadline but network latency consumes 50ms, does the server still have the full 100ms?
Discusses how cascading recovery and feedback loops can cause metastable failures in distributed systems, preventing proper recovery.
An introduction to a learning track on building load balancers from scratch, covering algorithms like round robin, least connections, consistent hashing, and practical pitfalls such as health check intervals.
DeadPool introduces a fault-tolerance mechanism for LLM training that enables hot-swapping of failed nodes with spare nodes using zero-overhead in-memory checkpointing, achieving fast recovery without interrupting the job.
This article explains how using Postgres transactions for workflow state co-located with application data eliminates idempotency and atomicity problems in distributed workflows, providing exactly-once execution.
Miles is an open-source PyTorch-native framework from RadixArk for large-scale LLM reinforcement learning post-training, integrating SGLang, Megatron-LM, and Ray for high-throughput rollout and distributed training.
Recommend an open source book 'The Accidental CTO', where the author shares hands-on architecture evolution experience from zero to millions of users, covering scaling, distributed technology selection, observability, and other core topics.
This paper argues for localized fault recovery mechanisms in distributed systems, emphasizing the benefits of fixing failures at the component level rather than relying on global recovery.
This paper introduces logical physical clocks and methods for consistent snapshots in globally distributed databases, addressing causality and consistency challenges.
Kyle Kingsbury shares a free outline for a 16-32 hour distributed systems fundamentals class, covering theory, algorithms, and practical production concerns, with optional labwork via Maelstrom.
A tweet by @system_monarch lists 27 core system design concepts (beginner to advanced) recommended for senior software engineering interviews at top tech companies like Google, Meta, and Uber.
Silk is a new stackful-fiber library and scheduler for ClickHouse, designed to improve asynchronous I/O performance with NUMA-aware work stealing, io_uring, and zero heap allocation in the hot path. It targets I/O-bound components like distributed cache, object storage, and network I/O.
This thesis from Aalto University presents a taxonomy of synchronization architectures, analyzing trade-offs and decision factors to guide the design of generalized sync engines.