LeanpubLift the Elephant: Scaling PostgreSQL Beyond Query Optimization by Alex Yarotsky is the featured book on Leanpub!
Link: https://leanpub.com/lift-the-elephant
#Databases #Postgresql #DistributedSystems #SoftwareEngineering
Caria Giovanni - HarpocratesI’ve been analyzing the current state of "secure" messaging, and my recent tests with Signal have highlighted some persistent vulnerabilities inherent to any stack relying on standard TCP/IP. Even with strong encryption, metadata leakage at the ISP/CDN level and the reliance on kernel-level interfaces like TUN/TAP remain significant privacy bottlenecks.
I’m curious to discuss the feasibility of a user-space only stack built in Rust that completely decouples identity, addressing, and transport to mitigate these leaks. My current architectural hypothesis involves an identity layer using hardware-backed Zero-Knowledge Proofs—via TEE or zkVM—to handle authentication without persistent identifiers or central registries. For addressing and routing, I'm thinking of a minimal RINA overlay where Distributed IPC Facilities (DIF) allow us to route between processes rather than nodes, effectively moving away from traditional IP-based addressing. This would all be wrapped in a "blind" transport, such as Ockam or shadowsocks-rust, to make the traffic indistinguishable from generic noise to any external observer.
I’m still weighing the practical hurdles, especially how to best bridge RINA's recursive logic with a user-space transport like Ockam without requiring root privileges. I'm open to suggestions on alternative technologies or implementations that might achieve this same level of isolation. If anyone has thoughts on the practical hurdles or existing foundations that could be leveraged here, I’d really value your perspective. Definitely feels like there's a lot to dig into.
#Rust #Rustlang #Infosec #Cryptography #Networking #Privacy #DistributedSystems #RINA #ZKP
Daniel James LeeWorking on a deterministic shared‑state transport layer inspired by entanglement. Trying to simplify distributed systems by removing consensus, metadata, and multi‑port noise.
N-gated Hacker NewsIn a groundbreaking revelation that nobody asked for, two authors claim language models are actually just like distributed systems... because, you know, both involve computers and math 🤯. They proceed to drown us in a sea of jargon and acronyms, leaving readers wondering if this paper is an elaborate AI-generated prank 😜.
https://arxiv.org/abs/2603.12229 #languagemodels #distributedsystems #AIresearch #jargonoverload #techhumor #HackerNews #ngated
https://arxiv.org/abs/2603.12229 #languagemodels #distributedsystems #AIresearch #jargonoverload #techhumor #HackerNews #ngated
Language Model Teams as Distributed Systems
Large language models (LLMs) are growing increasingly capable, prompting recent interest in LLM teams. Yet, despite increased deployment of LLM teams at scale, we lack a principled framework for addressing key questions such as when a team is helpful, how many agents to use, how structure impacts performance -- and whether a team is better than a single agent. Rather than designing and testing these possibilities through trial-and-error, we propose using distributed systems as a principled foundation for creating and evaluating LLM teams. We find that many of the fundamental advantages and challenges studied in distributed computing also arise in LLM teams, highlighting the rich practical insights that can come from the cross-talk of these two fields of study.
Hacker NewsLanguage Model Teams as Distrbuted Systems
https://arxiv.org/abs/2603.12229
#HackerNews #LanguageModelTeams #DistributedSystems #AIResearch #MachineLearning #HackerNews
Language Model Teams as Distributed Systems
Large language models (LLMs) are growing increasingly capable, prompting recent interest in LLM teams. Yet, despite increased deployment of LLM teams at scale, we lack a principled framework for addressing key questions such as when a team is helpful, how many agents to use, how structure impacts performance -- and whether a team is better than a single agent. Rather than designing and testing these possibilities through trial-and-error, we propose using distributed systems as a principled foundation for creating and evaluating LLM teams. We find that many of the fundamental advantages and challenges studied in distributed computing also arise in LLM teams, highlighting the rich practical insights that can come from the cross-talk of these two fields of study.
InfoQ#Uber redesigned its #MySQL fleet using a consensus-driven architecture based on MySQL Group Replication:
✅ Cluster failover dropped from minutes → seconds
✅ Leader election & failure detection now inside the database layer
✅ Improved availability, simpler orchestration, stronger consistency across thousands of production clusters
Learn more: https://bit.ly/4b8RWYL
#SoftwareArchitecture #DistributedSystems #Clusters #FaultTolerance #RelationalDatabases
SoftwareMillIs your Kafka lag dashboard lying? Learn how log compaction and retention silently manipulate reported timestamps to understate consumer delays and how to identify these inaccuracies and ensure your monitoring reflects actual system performance.
https://softwaremill.com/compaction-and-retention-edge-cases-that-make-your-kafkas-lag-metrics-inaccurate/
#ApacheKafka #DataEngineering #DistributedSystems #EventStreaming #Observability
InformationA Consenso Probabilístico Rápido - Fast Probabilistic Consensus (FPC)#Criptomonedas #Blockchain’s #ConsensusAlgorithms #Cryptocurrencies #DistributedSystems #FastProbabilisticConsensus #FaultTolerance #FPC #NetworkConsensus #ProbabilisticAlgorithms #Scalability O Fast Probabilistic Consensus (FPC) é um algoritmo de consenso rápido e eficiente, com base na teoria dos grafos probabilísticos. Esta abordagem oferece uma sol...
https://djltrading.com/fast-probabilistic-consensus-fpc/?fsp_sid=39657
https://djltrading.com/fast-probabilistic-consensus-fpc/?fsp_sid=39657
A Consenso Probabilístico Rápido - Fast Probabilistic Consensus (FPC)
O Fast Probabilistic Consensus (FPC) é um algoritmo de consenso rápido e eficiente, com base na teoria dos grafos probabilísticos. Esta abordagem oferece uma solução escalável e confiável para sistemas distribuídos.
Andrii SudakConcurrency Control: The Safety Net for Distributed Systems 🌐
In DevOps and cloud architecture, overlooking how shared resources are accessed across multiple nodes is a fast track to race conditions and data corruption.
When designing or debugging systems, always remember the two fundamental approaches to locking:
🔒 Pessimistic Locking
Approach: Acquire lock -> Modify -> Release.
Goal: Prevent conflicts before they happen. (e.g., DB FOR UPDATE).
🔄 Optimistic Locking (CAS/Version Checking)
Approach: Read -> Modify -> Commit with Version Check.
Goal: Detect conflicts at the end; retry if needed. (e.g., Kubernetes resourceVersion, HashiCorp Vault CAS).
Getting this right isn't just theory; it’s critical for stable CI/CD pipelines, state management, and high-availability systems. Don't let concurrency errors be the reason your system fails.
#DevOps #DistributedSystems #CloudComputing #SystemDesign #SoftwareEngineering #SRE
CAP theorem – Partition is a verb
http://mmudama.github.io/posts/2026/cap-partitions/
#HackerNews #CAPtheorem #PartitionVerb #DistributedSystems #TechInsights
CAP Theorem - Partition is a verb
People who’ve spent some time around databases usually have an intuitive sense of ACID, even if the acronym slips their mind. And if you work with distributed systems, you usually have a rough idea of the CAP Theorem, even if the details are fuzzy. The first thing you remember about CAP is probably, “Pick two out of three.” And maybe you can even remember the letters without a search engine …