
Explore Apollo Federation for distributed GraphQL schemas, learn to split and reconnect micro-services, and discover core principles and architecture for efficient graph management.

Explore real-time distributed stream processing with Antimony, a Rust-based system designed to outperform Apache Storm, addressing architectural and efficiency issues.

Techniques for building reliable infrastructure in Rust: advanced testing methods, bias reduction, and maximizing bug detection efficiency for distributed systems and databases.

Explore common microservices pitfalls and anti-patterns to avoid pain and problems in distributed systems. Learn from industry mistakes to improve your architecture design.

Explore the Orleans Framework, a powerful tool for building scalable cloud services and distributed systems using the Virtual Actor model, with real-world examples from Microsoft products.

Explore the actor model and Akka.NET to build powerful, highly available systems for distributed programming in .NET, addressing modern development challenges and improving application performance.

Explore distributed computing with Azure Service Fabric, a platform for building scalable, resilient services. Learn to develop and manage enterprise-level applications efficiently.

Explore the Orleans Framework for building scalable cloud systems, focusing on virtual actors, stateful middle tiers, and its origins in Microsoft Research and game development.

Learn to build and deploy distributed systems using Apache Mesos, exploring frameworks like Marathon and Chronos. Gain insights into resource management and control in large-scale clusters for efficient application development.

Explore distributed caching to enhance .NET app scalability, remove bottlenecks, and improve performance. Learn key features, use cases, and hands-on examples for efficient data management.

Explore microservices design using message brokers and containers, focusing on decoupling, event sourcing, and scalability. Learn implementation techniques with Kafka, Docker, and Azure Container Service.

Explore architectural patterns for high-availability, high-throughput trading systems. Learn approaches to balance performance, scalability, and reliability in millisecond-critical environments.

Explore Serilog for efficient .NET application instrumentation, tracking complex behaviors across distributed systems while maintaining simple text logging productivity.

Explore how CRDTs and distributed editing enable offline collaboration for writers, empowering digital nomads to work together anywhere, even atop Half Dome.

Introduction to actor model for building reactive, scalable systems. Demonstrates Akka.NET backend with ASP.NET Core, React+Redux frontend, and real-time updates using distributed actors, including on Raspberry Pis.

Discover how to achieve strong eventual consistency in distributed systems using actor models and AWS, sidestepping the CAP theorem with simple rules and proven mathematical principles.

Explore distributed data processing frameworks for handling large-scale event streams. Learn about Apache Storm, Spark, and emerging platforms to build reliable, scalable systems for real-time data processing.

Explore high-performance process workflows using Akka Streams. Learn to define, integrate, and compose workflows at a higher level, replacing traditional actors with streamlined graph-based definitions in C#, F#, and Scala.

Learn to build resilient Azure applications using patterns and features like Traffic Manager and Service Bus. Explore redundancy, load balancing, and monitoring for fault-tolerant distributed systems.

Discover how to achieve strong eventual consistency in distributed systems using actor models and AWS. Learn practical techniques to sidestep the CAP theorem and ensure data integrity.

Explore challenges in distributed systems, examining failures in a simple checkout process and refactoring towards resilience while embracing distributed computing fallacies.