Resources related to distributed systems, system design, microservices, scalability and performance, etc

Guidance for building event-driven distributed systems and microservices in Go with NATS JetStream, gRPC and CockroachDB

Design Microservices Architecture with Patterns & Principles. Design Microservices Architecture with Design Patterns, Principles and the Best Practices. How to handle millions of request with designing system for high availability, high scalability, low latency, and resilience to network failures on distributed microservices.

A state-of-the-art distributed system using Reactive DDD as uncertainty modeling, Event Storming as subdomain decomposition, Event Sourcing as an eventual persistence mechanism, CQRS, Async Projections, Microservices for individual deployable units, Event-driven Architecture for efficient integration, and Clean Architecture as domain-centric design

Easiest-ever formal methods language! Designed for developers crafting distributed systems, microservices, and cloud applications

Learn how to build and leverage the latest technology in APIs, services, microservices, distributed systems, HATEOAS, query languages, circuit breakers, gateways, discombobulators, flux capacitors, spider monkeys...

Your coding agent can already code. Microbus teaches it to master the complex domain of distributed systems — the architecture, the patterns, the operational discipline — and produce enterprise-grade microservices, every time.

Laravel Microservices Event Bus using RabbitMQ. Seamlessly publish events and handle them across distributed systems.

MicroRabbit: A lightweight, asynchronous Python framework for RabbitMQ that simplifies building microservices and distributed systems. Features include easy message routing, plugin support, and intuitive client configuration.

Chronicle Queue is a Java-based, high-performance messaging queue with ultra-low latency and durable off-heap persistence. It supports multiple concurrent writers and lock-free readers, delivering microsecond latency for millions of messages per second. Perfect for microservices, trading systems, event streaming, and distributed architectures.

This repo uses three simple services to illustrate how most distributed microservice architecture systems work. We use Go for creating a reverse proxy and Java for service discovery and registering profiles. The services use heartbeats to stay registered. We use the MySQL database in service registry and profile.

Zipkin is a distributed tracing system. It helps gather timing data needed to troubleshoot latency problems in microservice architectures. It manages both the collection and lookup of this data.

Modern C++17 actor-based framework for building high-performance concurrent and distributed systems. Features asynchronous I/O, lock-free messaging, cross-platform support (Linux/macOS/Windows), and multi-core scaling. Perfect for real-time applications, microservices, and network servers.

[DEPRECATED] ✨ Observability designed for distributed systems, microservices, serverless apps, and everything in between

Vostok Hercules is an open-source distributed system based on Apache Kafka and used for reliable delivery of telemetry data from microservices to storage and analytics engines.

This is a microservices-based distributed e-commerce system template designed to leverage a wide range of advanced management tools and practices from 0 to 1.

Gocorex is a collection golang useful utils for golang application, distributed system and microservices.

A distributed system for real-time flight tracking over Brazil, built with modern technologies and microservices architecture.

This project provides a high-performance distributed RPC (Remote Procedure Call) system based on Spring Boot, Netty, and Zookeeper for efficient inter-service communication in microservices architectures.

Graph Framework for Microservices is a platform software stack that bootstraps and accelerates cloud-native microservice development, that is out-of-the-box ready to thrive in the ever challenging world of distributed systems and SaaS.

Build scalable microservices in Rust with #monorepo efficiency. Simplify development, enhance modularity, and streamline dependency management. Leverage Rust's #performance and #safety for resilient distributed systems. Ideal for new projects or service migrations.

EventBus is a .Net Standard library to achieve eventually consistent in distributed architectures system like SOA,MicroService. It is lightweight,easy to use and efficiently.

Youtube talks about APIs in the context of microservices and distributed systems

[Amigoscode, Nelson] Microservices and Distributed Systems [ENG, 2022]

BlipMQ simplifies real-time communication between microservices and distributed systems with a lightweight, blazing-fast broker that just works — no complex setup, no compromises.

Prepare to Technical Skills Here are the essential skills that a Machine Learning Engineer needs, as mentioned Read me files. Within each group are topics that you should be familiar with. Study Tip: Copy and paste this list into a document and save to your computer for easy referral. Computer Science Fundamentals and Programming Topics Data structures: Lists, stacks, queues, strings, hash maps, vectors, matrices, classes & objects, trees, graphs, etc. Algorithms: Recursion, searching, sorting, optimization, dynamic programming, etc. Computability and complexity: P vs. NP, NP-complete problems, big-O notation, approximate algorithms, etc. Computer architecture: Memory, cache, bandwidth, threads & processes, deadlocks, etc. Probability and Statistics Topics Basic probability: Conditional probability, Bayes rule, likelihood, independence, etc. Probabilistic models: Bayes Nets, Markov Decision Processes, Hidden Markov Models, etc. Statistical measures: Mean, median, mode, variance, population parameters vs. sample statistics etc. Proximity and error metrics: Cosine similarity, mean-squared error, Manhattan and Euclidean distance, log-loss, etc. Distributions and random sampling: Uniform, normal, binomial, Poisson, etc. Analysis methods: ANOVA, hypothesis testing, factor analysis, etc. Data Modeling and Evaluation Topics Data preprocessing: Munging/wrangling, transforming, aggregating, etc. Pattern recognition: Correlations, clusters, trends, outliers & anomalies, etc. Dimensionality reduction: Eigenvectors, Principal Component Analysis, etc. Prediction: Classification, regression, sequence prediction, etc.; suitable error/accuracy metrics. Evaluation: Training-testing split, sequential vs. randomized cross-validation, etc. Applying Machine Learning Algorithms and Libraries Topics Models: Parametric vs. nonparametric, decision tree, nearest neighbor, neural net, support vector machine, ensemble of multiple models, etc. Learning procedure: Linear regression, gradient descent, genetic algorithms, bagging, boosting, and other model-specific methods; regularization, hyperparameter tuning, etc. Tradeoffs and gotchas: Relative advantages and disadvantages, bias and variance, overfitting and underfitting, vanishing/exploding gradients, missing data, data leakage, etc. Software Engineering and System Design Topics Software interface: Library calls, REST APIs, data collection endpoints, database queries, etc. User interface: Capturing user inputs & application events, displaying results & visualization, etc. Scalability: Map-reduce, distributed processing, etc. Deployment: Cloud hosting, containers & instances, microservices, etc. Move on to the final lesson of this course to find lots of sample practice questions for each topic!

Inter-Service communication framework, support for microservice architecture and distributed system

This article documents the thought process and steps involved in refactoring a distributed monolith to microservices. We are going to remove API GW, use Amazon Event Bridge and implement BASE consistency in the system to truly decouple our microservices. We also impliment AWS native observability, monitoring and alerting services.

Microservice distributed e-commerce system based on Hertz and gRPC / 基于 Hertz 与 gRPC 的分布式微服务电商系统

Obelisk is a high-performance, fault-tolerant, distributed event log system designed to be the single source of truth for microservices, real-time systems, and event-driven architectures.