The hottest Systems Substack posts right now

And their main takeaways
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Top Business Topics

All you need is Wide Events, not “Metrics, Logs and Traces”

A Song Of Bugs And Patches • 224 HN points • 15 Feb 24
🕹 Technology Observability Systems Events Metrics
  1. The concept of 'Wide Events' is proposed as a simpler and more effective approach to observability than the traditional 'Metrics, Logs, and Traces'.
  2. Older systems like Open Telemetry may contribute to confusion by categorizing data into distinct pillars, making observability seem complex.
  3. A system like Scuba, based on 'Wide Events', enables streamlined investigation and data exploration, emphasizing the importance of simplicity in observability tools.

LLM links, 2/27

In My Tribe • 91 implied HN points • 27 Feb 24
🕹 Technology AI Models Systems Predictions
  1. Compound AI systems are proving more effective than individual AI models, showing that combining different components can lead to better results.
  2. Providing extensive context can enhance AI capabilities, enabling new use cases and more effective training through models like Sora.
  3. The emergence of an AI computer virus is predicted to become a major concern, potentially causing widespread panic and technological shutdowns.
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TBM 205: "Process" vs. Systems & Habits

The Beautiful Mess • 1346 implied HN points • 12 Mar 23
💼 Business Management Processes Systems Habits Leadership
  1. Team A focuses on rushed, performative annual processes, while Team B prioritizes continuous improvement and thoughtful feedback.
  2. Team A's lack of customer-centricity and reactive approach leads to institutionalized mediocrity, while Team B's positive habits and systems drive effectiveness.
  3. Breaking the loop of reactive processes and establishing human-centric systems and valuable habits is crucial for better ways of working in organizations.

Biomimicry versus Top-Down Engineering

Risk Musings • 573 implied HN points • 22 Jul 23
🔬 Science Genetics Biology Innovation Systems
  1. Nature builds from the bottom up through evolution and mutations, unlike top-down engineering in human systems.
  2. Biomimicry offers inspiration across various fields by learning from nature's efficient and resilient systems.
  3. Bottom-up building, like in the human brain, involves countless interactions that lead to emergent solutions, unlike enforced top-down strategies.

Understanding Software Idempotency [Math Mondays]

Technology Made Simple • 119 implied HN points • 11 Dec 23
🕹 Technology Software Math Engineering Systems Programming
  1. Idempotency ensures the same output regardless of how many times an operation is executed, providing data consistency and preventing duplicate operations.
  2. Idempotency is crucial for resilience, scalability, performance, simplicity, and provability in software systems.
  3. Implementing idempotency involves using unique identifiers, versioning, transaction management, and leveraging HTTP methods, offering benefits like better error handling and faster response times.

Eventual Business Consistency

Software Design: Tidy First? • 134 HN points • 04 Aug 23
🕹 Technology Business Data Management Programming Systems Database
  1. The goal is to achieve eventual business consistency by closely matching what's in the system with real-world events.
  2. Different data storage methods like storing dated data or double-dated data come with trade-offs in complexity and accuracy.
  3. Bi-temporal systems use two dates to track when data changes occurred in reality and when they were recorded in the system for better business operations.

Diagram of an AI Image System

Cybernetic Forests • 119 implied HN points • 21 May 23
🕹 Technology AI Data Media Systems
  1. There is no definite definition of an AI image, as there are differing views on what AI and images truly are.
  2. Understanding different levels of AI image systems, such as data, interface, image, and media, is essential to navigating challenges within these systems.
  3. The intersection of AI images with human culture and media can perpetuate stereotypes and impact creators, leading to concerns about theft and ethical considerations.

The Physics of Intelligence

Breaking Smart • 99 implied HN points • 07 Apr 23
🔬 Science Physics AI Intelligence Systems Computation
  1. The physics of intelligence is not substrate dependent, similar to the physics of flight.
  2. The key questions in understanding the physics of intelligence relate to attention, memory, and the relationship between intelligence and information.
  3. Intelligence is not just about computation, but also about embodiment and specific interactions within the universe.

Seeing like a system

Perambulations • 3 implied HN points • 01 Mar 24
🔬 Science Systems Interdisciplinary Complexity Philosophy
  1. Systems often have hidden complexities that grow beyond their initial purpose, leading to unintended consequences.
  2. Systems can become rigid and resistant to change, focusing on perfecting past plans rather than adapting to new challenges.
  3. Understanding how systems function can help us critically analyze and navigate the systems we interact with in our daily lives.

Understanding the CAP theorem [Math Mondays]

Technology Made Simple • 99 implied HN points • 10 Jan 23
🕹 Technology Systems Tradeoffs Consistency
  1. The CAP theorem states that in a distributed system, you can only guarantee 2 out of 3 desirable traits: Consistency, Availability, and Partition Tolerance.
  2. Consistency in the CAP theorem ensures that all nodes in a network have the same data at the same time.
  3. Availability means that every read or write request will either succeed or receive an error message, with every node responding in a reasonable time.

System Design Concepts: An in-depth guide to Database sharding

Engineering At Scale • 29 implied HN points • 29 Jul 23
🕹 Technology Systems Databases Scaling Performance Architecture
  1. Database sharding splits a large dataset into chunks stored on different machines, increasing storage capacity and distributing queries for better performance.
  2. Sharding allows for high availability by avoiding a single point of failure and higher read/write throughput by distributing query load.
  3. Cost and maintenance overhead are drawbacks of sharding, and it differs from partitioning where data is stored on a single machine.

How to treat the people that built the system you work on

Bad Software Advice • 2 HN points • 26 Feb 24
🕹 Technology Development Software Coding Systems Tech industry
  1. When working on a system, it's common to face issues like downtime, scalability challenges, and the need for updates and cost optimization.
  2. It's important to address the existing problems systematically rather than blaming past developers and implying superiority.
  3. In a work environment, balancing necessary improvements with existing constraints can be tricky. Working towards gradual improvements and maintaining the system's functionality is crucial.

Slack's Email Classification Service

Arpit’s Newsletter • 39 implied HN points • 08 Mar 23
🕹 Technology Software Data Implementation Systems Infrastructure
  1. Slack has a feature to classify emails as internal or external during workspace invitations.
  2. Slack uses heuristics like domain matching to classify emails, but may face challenges in diverse email domains.
  3. Implementing a classification service involves maintaining a table with counts and eventual consistency for accurate classification.

Ground-truth-in-the-loop

Yuxi’s Substack • 19 implied HN points • 18 Jul 23
🕹 Technology AI Machine Learning Data Systems Models
  1. Ground-truth-in-the-loop is crucial for designing and evaluating systems, especially in AI and machine learning.
  2. For AI systems, having trustworthy training data, evaluation feedback, and a reliable world model is essential.
  3. Researchers should inform non-experts about limitations and potential issues when building systems without ground-truth.

The life and nature of a process

Building Rome(s) • 7 implied HN points • 18 Mar 23
🕹 Technology Processes Systems Organizational Culture
  1. Processes and systems are not necessarily opposites; in reality, systems are formed by combining effective processes over time.
  2. In the journey from processes to culture, there's a struggle between different perspectives like hedgehogs and foxes which influence how processes evolve.
  3. Balancing attention to detail (hedgehog) and simplicity (fox) is key in progressing processes and becoming a successful Technical Program Manager.

Bonus: More details on how Bell Labs operated

FreakTakes • 3 implied HN points • 20 Apr 23
🕹 Technology Innovation Engineering Development Research Systems
  1. Mervin Kelly emphasized the three key groups at Bell Labs: Research and Fundamental Development, Systems Engineering, and Specific Systems and Facilities Development.
  2. Research and Fundamental Development focused on pushing research frontiers, with a balance between research and basic technology.
  3. Systems Engineers played a vital role in integrating new knowledge with existing systems, ensuring efficiency, and guiding the application of research ideas into profitable projects.

Scaling Extreme Programming: Dependencies

Software Design: Tidy First? • 1 HN point • 20 Feb 23
🕹 Technology Programming Systems Dependencies Scaling Organization
  1. Extreme Programming focuses on reducing irreversibility and promoting reversibility in projects.
  2. Scaling Extreme Programming to large organizations requires addressing inter-connections between teams and dependencies.
  3. To manage dependencies in organizations, consider strategies like awareness, team improvement, slack, waiting, prioritizing, and self-service.

Automation with a Human Touch

Maximum Tinkering • 1 HN point • 14 Apr 23
🕹 Technology AI Automation Workforce Systems Innovation
  1. Toyota's Production System introduces the concept of autonomation, where machines stop for human intervention when issues arise, reducing waste.
  2. Generative AI could benefit from autonomation by being used to automate tasks with human oversight to refine outputs and catch errors.
  3. The idea of multi-skilled workers might shift the labor market from specialized roles to more general ones, increasing efficiency and productivity.

Driving changes: how to deal with pushbacks

Teamwork in Tech • 0 implied HN points • 25 May 23
🕹 Technology Engineering Innovation Management Documentation Systems
  1. Pushbacks on initiatives can happen due to various reasons like disbelief in promised goals, dissatisfaction with implemented solutions, or disagreement on the importance of the problem.
  2. To prevent pushback, ensure clear communication, involve stakeholders in defining and solving problems, and provide supporting evidence and documentation.
  3. When facing pushback, focus on understanding the perspectives of those involved, address concerns proactively, and work collaboratively to find solutions that benefit everyone.