Static Sites, Dynamic Microservices, and Azure - How We Built Microsoft Docs and Learn
Explore Microsoft's JAMStack-based approach for building Docs and Learn, focusing on scalability, performance, and community contributions through GitHub integration.
Welcome to the State Machine
Explore sagas for modeling complex collaborative domains without distributed transactions, focusing on failure handling and eventual consistency in stateful systems.
Forget about HTTP
Explore alternatives to HTTP for microservices communication, including messaging and RPC. Learn benefits and challenges of different approaches for efficient, scalable, and resilient architectures.
Big Data Analytics in Near-Real-Time with Apache Kafka Streams
Explore near-real-time data analytics using Apache Kafka streams. Learn to process, aggregate, and distribute large volumes of data efficiently, moving beyond traditional ETL methods for instant insights.
Asynchronous Distributed Systems
Explore microservice architectures, comparing synchronous and asynchronous models. Learn patterns like CQRS and Event Sourcing, and strategies for evolving systems towards asynchronous communication.
Scaling Microservices with Message Queues, .NET, and Kubernetes
Explore microservices scaling using message queues, .NET, and Kubernetes. Learn to design, package, and deploy reliable applications with autoscaling for improved performance and robustness.
Architectural Patterns for the Cloud
Explore cloud architectural patterns for availability, resiliency, data management, performance, and scalability. Learn implementation strategies and considerations for each pattern to optimize your cloud applications.
Code the Future, Now
Discover techniques to integrate future requirements into current code, avoiding batch jobs and scaling efficiently. Learn to capture business logic as first-class citizens for seamless temporal integration.
Advanced Azure App Services
Discover advanced Azure App Services techniques for enterprise projects, covering security, deployment, performance, scalability, and resiliency best practices.
Building APIs Rapidly with Azure Functions
Learn to rapidly build scalable, OpenAPI-compliant APIs using Azure Functions. Discover how to create, extend, and maintain APIs efficiently, with practical demonstrations and comparisons to other frameworks.
Owl - Scale and Flexibility in Distribution of Hot Content
Explore Owl, Meta's high-scale content distribution system combining centralized control with peer-to-peer data transfer, offering improved speed and flexibility over traditional methods.
HeteroSketch - Coordinating Network-wide Monitoring in Heterogeneous and Dynamic Networks
Innovative framework for optimizing network-wide monitoring in diverse, dynamic environments. Reduces resource overhead while maintaining performance, coverage, and accuracy through automated profiling and task allocation.
InfiniFS - An Efficient Metadata Service for Large-Scale Distributed Filesystems
Explore InfiniFS, an efficient metadata service for large-scale distributed filesystems, addressing challenges like load balancing, path resolution, and near-root hotspots.
A Full GPU Virtualization Solution with Mediated Pass-Through
Explore GPU virtualization with gVirt, achieving 95% native performance and scalability up to 7 VMs through mediated pass-through technology for secure isolation and full feature support.
DART - A Scalable and Adaptive Edge Stream Processing Engine
Scalable, adaptive edge stream processing engine for IoT applications, enabling fast processing of concurrent queries in dynamic environments through dynamic dataflow abstraction and P2P overlay networks.
Aperture - A Non-Cooperative, Client-Side Load Balancing Algorithm
Explore Twitter's Aperture algorithm for client-side load balancing, addressing scalability challenges in large service clusters and improving RPC framework efficiency.
Large-Scale Graph Processing on Emerging Storage Devices
Explores efficient graph processing on emerging storage devices, proposing a new partitioning framework that leverages improved random access capabilities for 2X better performance than state-of-the-art solutions.
Dorylus - Affordable, Scalable, and Accurate GNN Training with Distributed CPU Servers and Serverless Threads
Distributed system for training Graph Neural Networks using serverless computing, offering affordable scalability for billion-edge graphs with improved performance-per-dollar compared to GPU servers.
ZeRO-Offload - Democratizing Billion-Scale Model Training
ZeRO-Offload: Enabling billion-scale model training on a single GPU by offloading data and compute to CPU, minimizing data movement, and optimizing efficiency. Scales to multiple GPUs and works with model parallelism.
UniStore - A Fault-Tolerant Marriage of Causal and Strong Consistency
Explores a fault-tolerant data store combining causal and strong consistency for geo-distributed systems, addressing liveness challenges and optimizing durability costs in multi-consistency environments.
Amazon DynamoDB - A Scalable, Predictably Performant, and Fully Managed NoSQL Database Service
Explore Amazon DynamoDB's architecture, scalability, and performance optimizations. Learn how it handles massive workloads, ensures reliability, and evolves to meet increasing demands.