3 repository-uri
Educational resources on maintaining system stability, performance, and resilience under load.
Distinguishing note: Covers the theoretical and practical application of reliability concepts like backpressure, distinct from monitoring tools.
Explore 3 awesome GitHub repositories matching software engineering & architecture · System Reliability Principles. Refine with filters or upvote what's useful.
This project is a comprehensive educational resource focused on the principles, patterns, and trade-offs required to design scalable, reliable, and high-performance distributed systems. It provides a structured curriculum that covers the fundamental architectural strategies necessary for building modern software infrastructure, ranging from high-level system decomposition to low-level networking and data management. The repository distinguishes itself by offering deep dives into complex architectural patterns, such as microservices-based decomposition, event-driven communication, and command-
If queues start to grow significantly, the queue size can become larger than memory, resulting in cache misses, disk reads, and even slower performance. Backpressure can help by limiting the queue size, thereby maintaini
This project is a comprehensive educational framework designed to teach the design, deployment, and performance optimization of machine learning systems. It provides a structured curriculum that covers the full stack of artificial intelligence engineering, ranging from the construction of core framework components like tensors and automatic differentiation engines to the orchestration of large-scale distributed training clusters. The platform distinguishes itself through its integration of physics-grounded systems modeling and interactive simulation environments. Users can experiment with dis
Uses mathematical models and first-principles calculations to estimate performance, cost, and reliability of hardware architectures.
Drake is a robotics simulation framework and control system modeling tool used for designing, simulating, and verifying the dynamics of complex robotic systems. It functions as a multibody dynamics simulator and a mathematical optimization library, providing a suite of algorithms for trajectory optimization and the simulation of articulated robots. The framework is distinguished by its block-diagram system for composing dynamical subsystems and its ability to formulate and solve diverse mathematical programs, including linear, quadratic, and nonconvex nonlinear problems. It supports specializ
Constructs robotic systems by combining integrators, physics models, sensors, and controllers into a unified model.