Optimism vs Pessimism In Distributed Systems
- Marc Brooker tl;dr: Marc discusses the balance between optimistic and pessimistic assumptions. Optimistic assumptions, which anticipate successful outcomes without immediate coordination, contrast with pessimistic ones that proactively coordinate to prevent potential conflicts. The author exemplifies these concepts through distributed caches, Optimistic Concurrency Control, and leases. By identifying and categorizing these assumptions, developers can better understand and optimize system behavior.featured in #459
Hints for Distributed Systems Design
- Murat Demirbas tl;dr: “I have seen these hints successfully applied in distributed systems design throughout my 25 years in the field, starting from the theory of distributed systems, immersing into the practice of wireless sensor networks, and working on cloud computing systems both in the academia and industry ever since. These heuristic principles have been applied knowingly or unknowingly and has proven useful. I didn't invent any of these hints. These are collective products of distributed systems researchers and practitioners over many decades.”featured in #455
Clocks And Causality - Ordering Events In Distributed Systems
- Giridhar Manepalli tl;dr: In distributed systems, logical clocks play a key role in the ordering of system events. What are the various logical clock designs, and how do they help with event ordering? This article answers these questions.featured in #403
Fallacies Of Distributed Systems
tl;dr: "Fallacies of distributed systems are a set of assertions made by L Peter Deutsch and others at Sun Microsystems describing false assumptions that programmers new to distributed applications invariably make."featured in #371
The Distributed Computing Manifesto
- Werner Vogels tl;dr: "Today, I am publishing the Distributed Computing Manifesto, a canonical document from the early days of Amazon that transformed the architecture of Amazon’s e-commerce platform. It highlights the challenges we were facing at the end of the 20th century, and hints at where we were headed."featured in #370
Resiliency In Distributed Systems
- Gergely Orosz tl;dr: "Understanding the ins and outs of distributed systems is important for both backend engineers and for anyone working with large-scale systems. Large-scale systems can mean systems with high load and high queries per second (QPS), storing a large amount of data, or ones built with low latency and high reliability. These systems are pretty common across both Big Tech and high-growth startups."featured in #355
Fallacies Of Distributed Systems
- Mahdi Yusuf tl;dr: (1) The network is reliable, (2) Latency is zero, (3) Bandwidth is infinite, (4) The network is secure, (5) Topology doesn't change, (6) There is one administrator, (7) Transport cost is zero, (8) The network is homogeneous.featured in #323
Distributed Systems Shibboleths
- Joseph Lynch tl;dr: "Shibboleths are historically a word that indicate membership in a particular group or culture.... I have only studied and worked in the field for around a decade, but in that time I believe I have learned to recognize some key “distsys shibboleths” that help me recognize when I can trust what a vendor or other engineer is telling me."featured in #314
Building Robust Distributed Systems
- Kislay Verma tl;dr: "I have written before on this blog about what distributed systems are and how they can give us tremendous scalability at the cost of having to deal with a more complicated system design. Let’s discuss how we can make a distributed system resilient to random failures which get more common as the system gets larger."featured in #299
The Internet Was Designed With A Narrow Waist
- Andy Chu tl;dr: A narrow waist is concept, interface, or protocol that solves an interoperability problem. Picture an hourglass with M things on one side, N on the other, and an important concept in the middle. Andy illustrates how IP is an example, and how that impacts internet architecture.featured in #299